title: In Teacher We Trust: Learning Compressed Models for Pedestrian Detection

abstract:
  Deep convolutional neural networks continue to advance the state-of-the-art
in many domains as they grow bigger and more complex. It has been observed that
many of the parameters of a large network are redundant, allowing for the
possibility of learning a smaller network that mimics the outputs of the large
network through a process called Knowledge Distillation. We show, however, that
standard Knowledge Distillation is not effective for learning small models for
the task of pedestrian detection. To improve this process, we introduce a
higher-dimensional hint layer to increase information flow. We also estimate
the variance in the outputs of the large network and propose a loss function to
incorporate this uncertainty. Finally, we attempt to boost the complexity of
the small network without increasing its size by using as input hand-designed
features that have been demonstrated to be effective for pedestrian detection.
We succeed in training a model that contains $400\times$ fewer parameters than
the large network while outperforming AlexNet on the Caltech Pedestrian
Dataset.


title: Giant thermal magnetoresistance in plasmonic structures

abstract:
  A giant thermal magnetoresistance is predicted for the electromagnetic
transport of heat in magneto-optical plasmonic structures. In chains of InSb-Ag
nanoparticles at room temperature, we found that the resistance can be
increased by almost a factor of 2 with magnetic fields of 2 T. We show that
this important change results from the strong spectral dependence of localized
surface waves on the magnitude of the magnetic field.


title:
A Scalable and Adaptable Multiple-Place Foraging Algorithm for
  Ant-Inspired Robot Swarms

abstract:
  Individual robots are not effective at exploring large unmapped areas. An
alternate approach is to use a swarm of simple robots that work together,
rather than a single highly capable robot. The central-place foraging algorithm
(CPFA) is effective for coordinating robot swarm search and collection tasks.
Robots start at a centrally placed location (nest), explore potential targets
in the area without global localization or central control, and return the
targets to the nest. The scalability of the CPFA is limited because large
numbers of robots produce more inter-robot collisions and large search areas
result in substantial travel costs. We address these problems with the
multiple-place foraging algorithm (MPFA), which uses multiple nests distributed
throughout the search area. Robots start from a randomly assigned home nest but
return to the closest nest with found targets. We simulate the foraging
behavior of robot swarms in the robot simulator ARGoS and employ a genetic
algorithm to discover different optimized foraging strategies as swarm sizes
and the number of targets are scaled up. In our experiments, the MPFA always
produces higher foraging rates, fewer collisions, and lower travel and search
time compared to the CPFA for the partially clustered targets distribution. The
main contribution of this paper is that we systematically quantify the
advantages of the MPFA (reduced travel time and collisions), the potential
disadvantages (less communication among robots), and the ability of a genetic
algorithm to tune MPFA parameters to mitigate search inefficiency due to less
communication.


title:
Response to 'Comment on "Time delays in molecular photoionization"':
  Extended Discussion & Technical Notes

abstract:
  In a comment on our article Time delays in molecular photoionization [1],
Baykusheva & W\"orner reproduce canonical scattering theory, and assert that
our results are inconsistent with this well-established theory [2]. We
absolutely refute this assertion and the spirit of the comment, although we do
agree with Baykusheva & W\"orner that the textbook theory is correct. In a
short response, Response to Comment on "Time delays in molecular
photoionization" [3], we have already provided a clear rebuttal of the comment,
but gave no technical details. In this fuller response we extend those brief
comments in the spirit of completeness and clarity, and provide three clear
rebuttals to Baykusheva & W\"orner based on (1) logical fallacy (category
error), (2) theoretical details of the original article, (3) textural content
of the original article. In particular, rebuttal (1) clearly and trivially
points to the fact that there is no issue here whatsoever, with recourse to
theoretical details barely required to demonstrate this, as outlined in the
short version of our response. Our numerical results are correct and reproduce
known physical phenomena, as discussed in the original article hence, as
careful readers will recognise, the formalism used is canonical scattering
theory, and cannot be anything other. In fact, there is no new fundamental
physics here to dispute whatsoever, and nor was this the raison d'etre of the
original article. Additionally, rebuttal (2) provides the opportunity to
discuss, at length, some of these textbook aspects of photoionization theory,
and we hope this discussion might be of service to new researchers entering
this challenging field.


title:
Effective field theory approach to the gravitational two-body dynamics,
  at fourth post-Newtonian order and quintic in the Newton constant

abstract:
  Working within the post-Newtonian (PN) approximation to General Relativity,
we use the effective field theory (EFT) framework to study the conservative
dynamics of the two-body motion at fourth PN order, at fifth order in the
Newton constant. This is one of the missing pieces preventing the computation
of the full Lagrangian at fourth PN order using EFT methods. We exploit the
analogy between diagrams in the EFT gravitational theory and 2-point functions
in massless gauge theory, to address the calculation of 4-loop amplitudes by
means of standard multi-loop diagrammatic techniques. For those terms which can
be directly compared, our result confirms the findings of previous studies,
performed using different methods.


title:
A Large--Scale Spectroscopic Survey of Methanol and OH Line Emission
  from the Galactic Center: Observations and Data

abstract:
  Class I methanol masers are collisionally pumped and are generally correlated
with outflows in star forming sites in the Galaxy. Using the VLA in its A-array
configuration, we present a spectral line survey to identify methanol
$J=4_{-1}\rightarrow3_0E$ emission at 36.169~GHz. Over 900 pointings were used
to cover a region 66'x13'along the inner Galactic plane. A shallow survey of OH
at 1612, 1665, 1667 and 1720 MHz was also carried out over the area covered by
our methanol survey. We provide a catalog of 2240 methanol masers with narrow
line-widths of $\sim1$ km s$^{-1}$, spatial resolution of ~0.14"x0.05" and RMS
noise $\sim20$ mJy beam$^{-1}$ per channel. Lower limits on the brightness
temperature range from 27,000 K to 10,000,000 K showing the emission is of
non-thermal origin. We also provide a list of 23 OH (1612), 14 OH (1665), 5 OH
(1667) and 5 OH(1720 MHz) masers. The origin of such a large number of methanol
masers is not clear. Many methanol masers appear to be associated with infrared
dark clouds, though it appears unlikely that the entire population of masers
trace early phase of star formation in the Galactic center.


title: A Calculus of Cyber-Physical Systems

abstract:
  We propose a hybrid process calculus for modelling and reasoning on
cyber-physical systems (CPS{s}). The dynamics of the calculus is expressed in
terms of a labelled transition system in the SOS style of Plotkin. This is used
to define a bisimulation-based behavioural semantics which support
compositional reasonings. Finally, we prove run-time properties and system
equalities for a non-trivial case study.


title: Simulating with AcCoRD: Actor-Based Communication via Reaction-Diffusion

abstract:
  This paper introduces AcCoRD (Actor-based Communication via
Reaction-Diffusion) version 1.0. AcCoRD is a sandbox reaction-diffusion solver
designed for the study of molecular communication systems. It uses a hybrid of
microscopic and mesoscopic simulation models that enables scalability via user
control of local accuracy. AcCoRD is developed in C as an open source command
line tool and includes utilities to process simulation output in MATLAB. The
latest code and links to user documentation can be found at
https://github.com/adamjgnoel/AcCoRD/. This paper provides an overview of
AcCoRD's design, including the motivation for developing a specialized
reaction-diffusion solver. The corresponding algorithms are presented in
detail, including the computational complexity of the microscopic and
mesoscopic models. Other novel derivations include the transition rates between
adjacent mesoscopic subvolumes of different sizes. Simulation results
demonstrate the use of AcCoRD as both an accurate reaction-diffusion solver and
one that is catered to the analysis of molecular communication systems. A link
is included to videos that demonstrate many of the simulated scenarios.
Additional insights from the simulation results include the selection of
suitable hybrid model parameters, the impact of reactive surfaces that are in
the proximity of a hybrid interface, and the size of a bounded environment that
is necessary to assume that it is unbounded. The development of AcCoRD is
ongoing, so its future direction is also discussed in order to highlight
improvements that will expand its potential areas of application. New features
that are being planned at the time of writing include a fluid flow model and
more complex actor behavior.


title: AC conductivity for a holographic Weyl Semimetal

abstract:
  We study the AC electrical conductivity at zero temperature in a holographic
model for a Weyl semimetal. At small frequencies we observe a linear dependence
in the frequency. The model shows a quantum phase transition between a
topological semimetal (Weyl semimetal phase) with a non vanishing anomalous
Hall conductivity and a trivial semimetal. The AC conductivity has an
intermediate scaling due to the presence of a quantum critical region in the
phase diagram of the system. The phase diagram is reconstructed using the
scaling properties of the conductivity. We compare with the experimental data
of [1502.03807] obtaining qualitative agreement.


title: On the representation of $k$-free integers by binary forms

abstract:
  Let $F$ be a binary form with integer coefficients, non-zero discriminant and
degree $d$ with $d$ at least $3$ and let $r$ denote the largest degree of an
irreducible factor of $F$ over the rationals. Let $k$ be an integer with $k
\geq 2$ and suppose that there is no prime $p$ such that $p^k$ divides $F(a,b)$
for all pairs of integers $(a,b)$. Let $R_{F,k}(Z)$ denote the number of
$k$-free integers of absolute value at most $Z$ which are represented by $F$.
We prove that there is a positive number $C_{F,k}$ such that $R_{F,k}(Z)$ is
asymptotic to $C_{F,k} Z^{\frac{2}{d}}$ provided that $k$ exceeds $
\frac{7r}{18}$ or $(k,r)$ is $(2,6)$ or $(3,8)$.


title: Astrochemical Properties of Planck Cold Clumps

abstract:
  We observed thirteen Planck cold clumps with the James Clerk Maxwell
Telescope/SCUBA-2 and with the Nobeyama 45 m radio telescope. The N$_2$H$^+$
distribution obtained with the Nobeyama telescope is quite similar to SCUBA-2
dust distribution. The 82 GHz HC$_3$N, 82 GHz CCS, and 94 GHz CCS emission are
often distributed differently with respect to the N$_2$H$^+$ emission. The CCS
emission, which is known to be abundant in starless molecular cloud cores, is
often very clumpy in the observed targets. We made deep single-pointing
observations in DNC, HN$^{13}$C, N$_2$D$^+$, cyclic-C$_3$H$_2$ toward nine
clumps. The detection rate of N$_2$D$^+$ is 50\%. Furthermore, we observed the
NH$_3$ emission toward 15 Planck cold clumps to estimate the kinetic
temperature, and confirmed that most of targets are cold ($\lesssim$ 20 K). In
two of the starless clumps observe, the CCS emission is distributed as it
surrounds the N$_2$H$^+$ core (chemically evolved gas), which resembles the
case of L1544, a prestellar core showing collapse. In addition, we detected
both DNC and N$_2$D$^+$. These two clumps are most likely on the verge of star
formation. We introduce the Chemical Evolution Factor (CEF) for starless cores
to describe the chemical evolutionary stage, and analyze the observed Planck
cold clumps.


title: Digit Statistics of the First 22.4 Trillion Decimal Digits of Pi

abstract:
  The mathematical constant pi has recently been computed up to
22,459,157,718,361 decimal and 18,651,926,753,033 hexadecimal digits. As a
simple check for the normality of pi, the frequencies of all sequences with
length one, two and three in the base 10 and base 16 representations are
extracted. All evaluated frequencies are found to be consistent with the
hypothesis of pi being a normal number in these bases.


title:
Direct observation of coherent energy transfer in nonlinear
  micro-mechanical oscillators

abstract:
  Energy dissipation is an unavoidable phenomenon of physical systems that are
directly coupled to an external environmental bath. The ability to engineer the
processes responsible for dissipation and coupling is fundamental to manipulate
the state of such systems. This is particularly important in oscillatory states
whose dynamic response is used for many applications, e.g. micro and
nano-mechanical resonators or sensing and timing, qubits for quantum
engineering, and vibrational modes for optomechanical devices. In situations
where stable oscillations are required, the energy dissipated by the
vibrational modes is usually compensated by replenishment from external energy
sources. Consequently, if the external energy supply is removed, the amplitude
of oscillations start to decay immediately, since there is no means to
restitute the energy dissipated. Here, we demonstrate a novel strategy to
maintain stable oscillations, i.e. with constant amplitude and frequency,
without supplying external energy to compensate losses. The fundamental
intrinsic mechanism of mode coupling is used to redistribute and store
mechanical energy among vibrational modes and coherently transfer it back to
the principal mode when the external excitation is off. To experimentally
demonstrate this phenomenon that defies physical intuition, we exploit the
nonlinear dynamic response of microelectromechanical (MEMS) oscillators to
couple two different vibrational modes through an internal resonance. Since the
underlying mechanism describing the fundamentals of this new phenomenon is
generic and representative of a large variety of systems, the presented method
provides a new dissipation engineering strategy that would enable a new
generation of autonomous devices.


title: Gas Accretion and Giant Lyman-alpha Nebulae

abstract:
  Several decades of observations and discoveries have shown that high-redshift
AGN and massive galaxies are often surrounded by giant Lyman-alpha nebulae
extending in some cases up to 500 kpc in size. In this review, I discuss the
properties of the such nebulae discovered at z>2 and their connection with gas
flows in and around the galaxies and their halos. In particular, I show how
current observations are used to constrain the physical properties and origin
of the emitting gas in terms of the Lyman-alpha photon production processes and
kinematical signatures. These studies suggest that recombination radiation is
the most viable scenario to explain the observed Lyman-alpha luminosities and
Surface Brightness for the large majority of the nebulae and imply that a
significant amount of dense, ionized and cold clumps should be present within
and around the halos of massive galaxies. Spectroscopic studies suggest that,
among the giant Lyman-alpha nebulae, the one associated with radio-loud AGN
should have kinematics dominated by strong, ionized outflows within at least
the inner 30-50 kpc. Radio-quiet nebulae instead present more quiescent
kinematics compatible with stationary situation and, in some cases, suggestive
of rotating structures. However, definitive evidences for accretion onto
galaxies of the gas associated with the giant Lyman-alpha emission are not
unambiguously detected yet. Deep surveys currently ongoing using other bright,
non-resonant lines such as Hydrogen H-alpha and HeII1640 will be crucial to
search for clearer signatures of cosmological gas accretion onto galaxies and
AGN.


title: Random Field Quantization Method

abstract:
  Today it still remains a challenge whether quantum mechanics has an
underlying statistical explanation or not. While there are and were a lot of
models trying to explain quantum phenomena with statistical methods these all
failed on certain levels. In this paper a method is proposed that is not only
based on a classical statistical framework but it has an underlying physical
model behind it and it can explain some of the basic characteristics of quantum
mechanics. It will be shown that if look at the properties of a charged
particle in a random electric field one can obtain the discrete energy values
of the harmonic oscillator and the infinite potential well, and also gives a
good qualitative description of the double-slit experiment and measurement
theory. Also the side-effect of the model is the emergence of a constant with
an action dimension.


title:
High-accuracy power series solutions with arbitrarily large radius of
  convergence for fractional nonlinear differential equations

abstract:
  Fractional nonlinear differential equations present an interplay between two
common and important effective descriptions used to simplify high dimensional
or more complicated theories: nonlinearity and fractional derivatives. These
effective descriptions thus appear commonly in physical and mathematical
modeling. We present a new series method providing systematic controlled
accuracy for solutions of fractional nonlinear differential equations. The
method relies on spatially iterative use of power series expansions. Our
approach permits an arbitrarily large radius of convergence and thus solves the
typical divergence problem endemic to power series approaches. We apply our
method to the fractional nonlinear Schr\"odinger equation and its imaginary
time rotation, the fractional nonlinear diffusion equation. For the fractional
nonlinear Schr\"odinger equation we find fractional generalizations of cnoidal
waves of Jacobi elliptic functions as well as a fractional bright soliton. For
the fractional nonlinear diffusion equation we find the combination of
fractional and nonlinear effects results in a more strongly localized solution
which nevertheless still exhibits power law tails, albeit at a much lower
density.


title: How Kirkwood and Probability Distributions Differ: A Coxian Perspective

abstract:
  Kolmogorov's first axiom of probability is probability takes values between 0
and 1; however, in Cox's derivation of probability having a maximum value of
unity is arbitrary since he derives probability as a tool to rank degrees of
plausibility. Probability can then be used to make inferences in instances of
incomplete information, which is the foundation of Baysian probability theory.
This article formulates a rule, which if obeyed, allows probability to take
complex values and still be consistent with the interpretation of probability
theory as being a tool to rank plausibility. It is then shown that Kirkwood
distributions and the conditional complex probability distributions proposed by
Hofmann do not obey this rule and therefore cannot rank plausibility. Not only
do these quasiprobability distributions relax Kolmogorov's first axiom of
probability, they also are void of the defining property of a probability
distribution from a Coxian and Baysian perspective - they lack the ability to
rank plausibility.


title: Unusual void galaxy DDO68: implications of the HST resolved photometry

abstract:
  DDO68 (UGC5340) is an unusual dwarf galaxy with extremely low gas metallicity
(12+log(O/H) = 7.14) residing in the nearby Lynx-Cancer void. Despite its
apparent isolation, it shows both optical and HI morphological evidence for
strong tidal disturbance. Here, we study the resolved stellar populations of
DDO68 using deep images from the HST archive. We determined a distance of
12.75+-0.41 Mpc using the tip of the red giant branch (TRGB). The star
formation history reconstruction reveals that about 60 per cent of stars formed
during the initial period of star formation, about 12-14 Gyr ago. During the
next 10 Gyr DDO68 was in the quenched state, with only slight traces of star
formation. The onset of the most recent burst of star formation occurred about
300 Myr ago. We find that young populations with ages of several million to a
few hundred million years are widely spread across various parts of DDO68,
indicating an intense star formation episode with a high mean rate of 0.15
Msun/yr. A major fraction of the visible stars in the whole system (~80 per
cent) have low metallicities: Z = Zsun/50 - Zsun/20. The properties of the
northern periphery of DDO68 can be explained by an ongoing burst of star
formation induced by the minor merger of a small, gas-rich, extremely
metal-poor galaxy with a more typical dwarf galaxy. The current TRGB-based
distance of DDO68 implies a total negative peculiar velocity of ~500 km/s.


title: 3D Bounding Box Estimation Using Deep Learning and Geometry

abstract:
  We present a method for 3D object detection and pose estimation from a single
image. In contrast to current techniques that only regress the 3D orientation
of an object, our method first regresses relatively stable 3D object properties
using a deep convolutional neural network and then combines these estimates
with geometric constraints provided by a 2D object bounding box to produce a
complete 3D bounding box. The first network output estimates the 3D object
orientation using a novel hybrid discrete-continuous loss, which significantly
outperforms the L2 loss. The second output regresses the 3D object dimensions,
which have relatively little variance compared to alternatives and can often be
predicted for many object types. These estimates, combined with the geometric
constraints on translation imposed by the 2D bounding box, enable us to recover
a stable and accurate 3D object pose. We evaluate our method on the challenging
KITTI object detection benchmark both on the official metric of 3D orientation
estimation and also on the accuracy of the obtained 3D bounding boxes. Although
conceptually simple, our method outperforms more complex and computationally
expensive approaches that leverage semantic segmentation, instance level
segmentation and flat ground priors and sub-category detection. Our
discrete-continuous loss also produces state of the art results for 3D
viewpoint estimation on the Pascal 3D+ dataset.


title: Opioid Atlas: Mapping Access to Pain Medication

abstract:
  Opiates are some of the most effective pain relief medications available for
patients suffering from cancer and surgery-related pain. Despite the
affordability and effectiveness of these medications, access to opiates is
highly geographically variable. Pain researchers have attributed geographic
variation to various factors including the fear of opioid addiction, diversion
of legal opiods to the underground market and pharmaceutical industry
influences. However, the extent to which there is inequity in untreated cancer
and surgery-related pain is unknown. To help opioid investigators study these
questions, we designed a tool, the Opioid Atlas, for exploring data on legal
opioid consumption, by country and time, collected by the International
Narcotics Control Board. Our design borrows ideas from the data visualization
and multivariate statistics communities, especially the principles of linking
and dimensionality reduction. Our work is relevant to policymakers and pain
researchers who wish to systematically assess country-level factors that
contribute to differences in opioid access for patients with cancer and
surgery-related pain. The Opioid Atlas, and the code behind it, is freely
available with an open source license.


title:
Pathwise Stieltjes integrals of discontinuously evaluated stochastic
  processes

abstract:
  In this article we study the existence of pathwise Stieltjes integrals of the
form $\int f(X_t)\, dY_t$ for nonrandom, possibly discontinuous, evaluation
functions $f$ and H\"older continuous random processes $X$ and $Y$. We discuss
a notion of sufficient variability for the process $X$ which ensures that the
paths of the composite process $t \mapsto f(X_t)$ are almost surely regular
enough to be integrable. We show that the pathwise integral can be defined as a
limit of Riemann-Stieltjes sums for a large class of discontinuous evaluation
functions of locally finite variation, and provide new estimates on the
accuracy of numerical approximations of such integrals, together with a change
of variables formula for integrals of the form $\int f(X_t) \, dX_t$.


title:
Low rank approximate solutions to large-scale differential matrix
  Riccati equations

abstract:
  In the present paper, we consider large-scale continuous-time differential
matrix Riccati equations having low rank right-hand sides. These equations are
generally solved by Backward Differentiation Formula (BDF) or Rosenbrock
methods leading to a large scale algebraic Riccati equation which has to be
solved for each timestep. We propose a new approach, based on the reduction of
the problem dimension prior to integration. We project the initial problem onto
an extended block Krylov subspace and obtain a low-dimentional differential
algebraic Riccati equation. The latter matrix differential problem is then
solved by Backward Differentiation Formula (BDF) method and the obtained
solution is used to reconstruct an approximate solution of the original
problem. We give some theoretical results and a simple expression of the
residual allowing the implementation of a stop test in order to limit the
dimension of the projection space. Some numerical experiments will be given.


title: Object-Centric Representation Learning from Unlabeled Videos

abstract:
  Supervised (pre-)training currently yields state-of-the-art performance for
representation learning for visual recognition, yet it comes at the cost of (1)
intensive manual annotations and (2) an inherent restriction in the scope of
data relevant for learning. In this work, we explore unsupervised feature
learning from unlabeled video. We introduce a novel object-centric approach to
temporal coherence that encourages similar representations to be learned for
object-like regions segmented from nearby frames. Our framework relies on a
Siamese-triplet network to train a deep convolutional neural network (CNN)
representation. Compared to existing temporal coherence methods, our idea has
the advantage of lightweight preprocessing of the unlabeled video (no tracking
required) while still being able to extract object-level regions from which to
learn invariances. Furthermore, as we show in results on several standard
datasets, our method typically achieves substantial accuracy gains over
competing unsupervised methods for image classification and retrieval tasks.


title: Spatial Distribution of Mg-Rich Ejecta in LMC Supernova Remnant N49B

abstract:
  The supernova remnant (SNR) N49B in the Large Magellanic Cloud is a peculiar
example of a core-collapse SNR to show the shocked metal-rich ejecta enriched
only in Mg without evidence for a similar overabundance in O and Ne. Based on
archival Chandra data we present results from our extensive spatially-resolved
spectral analysis of N49B. We find that the Mg-rich ejecta gas extends from the
central regions of the SNR out to the southeastern outermost boundary of the
SNR. This elongated feature shows an overabundance for Mg similar to that of
the main ejecta region at the SNR center, and its electron temperature appears
to be higher than the central main ejecta gas. We estimate that the Mg mass in
this southeastern elongated ejecta feature is ~10% of the total Mg ejecta mass.
Our estimated lower limit of >0.1 M_sun on the total mass of the Mg-rich ejecta
confirms the previously-suggested large mass for the progenitor star (M > ~25
M_sun). We entertain scenarios of an SNR expanding into a non-uniform medium
and an energetic jet-driven supernova in an attempt to interpret these results.
However, with the current results, the origins of the extended Mg-rich ejecta
and the Mg-only-rich nature of the overall metal-rich ejecta in this SNR remain
elusive.


title: Box model of migration in channels of migration networks

abstract:
  We discuss a box model of migration in channels of networks with possible
application for modelling motion of migrants in migration networks. The channel
consists of nodes of the network (nodes may be considered as boxes representing
countries) and edges that connect these nodes and represent possible ways for
motion of migrants. The nodes of the migration channel have different
"leakage", i.e. the probability of change of the status of a migrant (from
migrant to non-migrant) may be different in the different countries along the
channel. In addition the nodes far from the entry node of the channel may be
more attractive for migrants in comparison to the nodes around the entry node
of the channel. We discuss below channels containing infinite number of nodes.
Two regimes of functioning of these channels are studied: stationary regime and
non-stationary regime. In the stationary regime of the functioning of the
channel the distribution of migrants in the countries of the channel is
described by a distribution that contains as particular case the Waring
distribution. In the non-stationary regime of functioning of the channel one
observes exponential increase or exponential decrease of the number of migrants
in the countries of the channel. It depends on the situation in the entry
country of the channel for which scenario will be realized. Despite the
non-stationary regime of the functioning of the channel the asymptotic
distribution of the migrants in the nodes of the channel is stationary. From
the point of view of the characteristic features of the migrants we discuss the
cases of (i) migrants having the same characteristics and (ii) two classes of
migrants that have differences in some characteristic (e.g., different
religions).


title: Multibrand geographic experiments

abstract:
  In a geographic experiment to measure advertising effectiveness, some regions
(hereafter GEOs) get increased advertising while others do not. This paper
looks at running $B>1$ such experiments simultaneously on $B$ different brands
in $G$ GEOs, and then using shrinkage methods to estimate returns to
advertising. There are important practical gains from doing this. Data from any
one brand helps to estimate the return of all other brands. We see this in both
a frequentist and Bayesian formulation. As a result, each individual experiment
could be made smaller and less expensive when they are analyzed together. We
also provide an experimental design for multibrand experiments where half of
the brands have increased spend in each GEO while half of the GEOs have
increased spend for each brand. For $G>B$ the design is a two level factorial
for each brand and simultaneously a supersaturated design for the GEOs.
Multiple simultaneous experiments also allow one to identify GEOs in which
advertising is generally more effective. That cannot be done in the single
brand experiments we consider.


title:
Understanding Divergent Thermal Conductivity in Single Polythiophene
  Chains using Modal Analysis and Sonification

abstract:
  We used molecular dynamics simulations, the Green-Kubo Modal Analysis (GKMA)
method and sonification to study the modal contributions to thermal
conductivity in individual polythiophene chains. The simulations suggest that
it is possible to achieve divergent thermal conductivity and the GKMA method
allowed for exact pinpointing of the modes responsible for the anomalous
behavior. The analysis showed that transverse vibrations in the plane of the
aromatic rings at low frequencies ~ 0.05 THz are primarily responsible. Further
investigation showed that the divergence arises from persistent correlation
between the three lowest frequency modes on chains. Sonification of the mode
heat fluxes revealed regions where the heat flux amplitude yields a somewhat
sinusoidal envelope with a long period similar to the relaxation time. This
characteristic in the divergent mode heat fluxes gives rise to the overall
thermal conductivity divergence, which strongly supports earlier hypotheses
that attribute the divergence to correlated phonon-phonon
scattering/interactions.


title:
Particle Model Predictive Control: Tractable Stochastic Nonlinear
  Output-Feedback MPC

abstract:
  We combine conditional state density construction with an extension of the
Scenario Approach for stochastic Model Predictive Control to nonlinear systems
to yield a novel particle-based formulation of stochastic nonlinear
output-feedback Model Predictive Control. Conditional densities given noisy
measurement data are propagated via the Particle Filter as an approximate
implementation of the Bayesian Filter. This enables a particle-based
representation of the conditional state density, or information state, which
naturally merges with scenario generation from the current system state. This
approach attempts to address the computational tractability questions of
general nonlinear stochastic optimal control. The Particle Filter and the
Scenario Approach are shown to be fully compatible and -- based on the time-
and measurement-update stages of the Particle Filter -- incorporated into the
optimization over future control sequences. A numerical example is presented
and examined for the dependence of solution and computational burden on the
sampling configurations of the densities, scenario generation and the
optimization horizon.


title: On the Cohomology of the Classifying Spaces of Projective Unitary Groups

abstract:
  Let $\mathbf{B}PU_{n}$ be the classifying space of $PU_n$, the projective
unitary group of order $n$, for $n>1$. We use the Serre spectral sequence
associated to a fiber sequence
$\mathbf{B}U_n\rightarrow\mathbf{B}PU_n\rightarrow K(\mathbb{Z},3)$ to
determine the ring structure of $H^{*}(\mathbf{B}PU_{n}; \mathbb{Z})$ up to
degree $10$, as well as a family of distinguished elements of
$H^{2p+2}(\mathbf{B}PU_{n}; \mathbb{Z})$, for each prime divisor $p$ of $n$. We
also study the primitive elements of $H^*(\mathbf{B}U_n;\mathbb{Z})$ as a
comodule over $H^*(K(\mathbb{Z},2);\mathbb{Z})$, where the comodule structure
is given by an action of $K(\mathbb{Z},2)\simeq\mathbf{B}S^1$ on $BU_n$
corresponding to the action of taking the tensor product of a complex line
bundle and an $n$ dimensional complex vector bundle.


title:
Electronic Non-adiabatic Dynamics in Enhanced Ionization of
  Isotopologues of H$_2^+$ from the Exact Factorization Perspective

abstract:
  It was recently shown that the exact potential driving the electron's
dynamics in enhanced ionization of H$_2^+$ can have large contributions arising
from dynamical electron-nuclear correlation, going beyond what any
electrostatics-based model can provide[1]. This potential is defined via the
exact factorization of the molecular wavefunction that allows the construction
of a Schr\"odinger equation for the electronic system, in which the potential
contains exactly the effect of coupling to the nuclear system and any external
fields. Here we study enhanced ionization in isotopologues of H$_2^+$ in order
to investigate nuclear-mass-dependence of these terms for this process. We
decompose the exact potential into components that naturally arise from the
conditional wavefunction, and also into components arising from the marginal
electronic wavefunction, and compare the performance of propagation on these
different components as well as approximate potentials based on the
quasi-static or Hartree approximation with the exact propagation. A
quasiclassical analysis is presented to help analyse the structure of different
non-electrostatic components to the potential driving the ionizing electron.


title: Transient science with the e-EVN

abstract:
  I briefly review transient research with the EVN, with particular emphasis on
the science that was (or is being) made possible with the latest real-time
e-VLBI developments.


title:
Detecting finite flat dimension of modules via iterates of the Frobenius
  endomorphism

abstract:
  It is proved that a module $M$ over a Noetherian ring $R$ of positive
characteristic $p$ has finite flat dimension if there exists an integer $t\ge
0$ such that $\operatorname{Tor}_i^R(M, {}^{f^{e}}\!R)=0$ for $t\le i\le t+\dim
R$ and infinitely many $e$. This extends a result of Herzog, who proved it when
$M$ is finitely generated, and strengthens a result of the third author and
Webb in the case $M$ is arbitrary. It is also proved that when $R$ is a
Cohen-Macaulay local ring, it suffices that the Tor vanishing holds for one
$e\ge \log_{p}e(R)$, where $e(R)$ is the multiplicity of $R$.


title: Anomalies in weak decays of H-like ions

abstract:
  We investigate the emergence of oscillations in the decay law of unstable
systems. We discuss in particular the case of the so-called GSI anomaly seen in
the electron capture decays of H-like ions and prove that such oscillations
cannot be explained by neutrino oscillations. We then discuss how such
anomalies could be intimately related to the decay law of unstable systems in
the case in which their spectral function deviates from a Breit-Wigner shape.


title:
Anatomy of the Inert Two Higgs Doublet Model in the light of the LHC and
  non-LHC Dark Matter Searches

abstract:
  The inert Two Higgs Doublet Model (i2HDM) is a theoretically well-motivated
example of a minimal consistent Dark Matter(DM) model which provides mono-jet,
mono-Z, mono-Higgs and Vector-Boson-Fusion+Missing Transverse Momentum
signatures at the LHC, complemented by signals in direct and indirect DM search
experiments. In this paper we have performed a detailed analysis of the
constraints in the full 5D parameter space of the i2HDM, coming from
perturbativity, unitarity, electroweak precision data, Higgs data from LHC, DM
relic density, direct/indirect DM detection and LHC mono-jet analysis, as well
as implications of experimental LHC studies on disappearing charged tracks
relevant to high DM mass region. We demonstrate the complementarity of the
above constraints and present projections for future LHC data and direct DM
detection experiments to probe further i2HDM parameter space. The model is
implemented into the CalcHEP and micrOMEGAs packages, which are publicly
available at the HEPMDB database, and is ready for a further exploration in the
context of the LHC, relic density and DM direct detection.


title:
Hartman-Wintner growth results for sublinear functional differential
  equations

abstract:
  In this paper, we determine rates of growth to infinity of scalar autonomous
nonlinear functional and Volterra differential equations. In these equations,
the right-hand side is a positive continuous linear functional of a nonlinear
function of the state. We assume the nonlinearity grows sublinearly at
infinity, leading to subexponential growth in the solutions. Our main results
show that the solutions of the functional differential equations are asymptotic
to those of an auxiliary autonomous ordinary differential equation when the
nonlinearity grows more slowly than a critical rate. If the nonlinearity grows
more rapidly than this rate, the ODE dominates the FDE. If the nonlinearity
tends to infinity at exactly this rate, the FDE and ODE grow at the same rate,
modulo a constant non-unit factor. Finally, if the nonlinearity grows more
slowly than the critical rate, then the ODE and FDE grow at the same rate
asymptotically. We also prove a partial converse of the last result. In the
case when the growth rate is slower than that of the ODE, we calculate sharp
bounds on the solutions.


title: Gas Accretion and Angular Momentum

abstract:
  In this chapter, we review the role of gas accretion to the acquisition of
angular momentum, both in galaxies and in their gaseous halos. We begin by
discussing angular momentum in dark matter halos, with a brief review of tidal
torque theory and the importance of mergers, followed by a discussion of the
canonical picture of galaxy formation within this framework, where halo gas is
presumed to shock-heat to the virial temperature of the halo, following the
same spin distribution as the dark matter halo before cooling to the center of
the halo to form a galaxy there. In the context of recent observational
evidence demonstrating the presence of high angular momentum gas in galaxy
halos, we review recent cosmological hydrodynamic simulations that have begun
to emphasize the role of "cold flow" accretion---anisotropic gas accretion
along cosmic filaments that does not shock-heat before sinking to the central
galaxy. We discuss the implications of these simulations, reviewing a number of
recent developments in the literature, and suggest a revision to the canonical
model as it relates to the expected angular momentum content of gaseous halos
around galaxies.


title:
Poincar\'e, modified logarithmic Sobolev and isoperimetric inequalities
  for Markov chains with non-negative Ricci curvature

abstract:
  We study functional inequalities for Markov chains on discrete spaces with
entropic Ricci curvature bounded from below. Our main results are that when
curvature is non-negative, but not necessarily positive, the spectral gap, the
Cheeger isoperimetric constant and the modified logarithmic Sobolev constant of
the chain can be bounded from below by a constant that only depends on the
diameter of the space, with respect to a suitable metric. These estimates are
discrete analogues of classical results of Riemannian geometry obtained by Li
and Yau, Buser and Wang.


title: Growth and fluctuation in perturbed nonlinear Volterra equations

abstract:
  We develop precise bounds on the growth rates and fluctuation sizes of
unbounded solutions of deterministic and stochastic nonlinear Volterra
equations perturbed by external forces. The equation is sublinear for large
values of the state, in the sense that the state--dependence is negligible
relative to linear functions. If an appropriate functional of the forcing term
has a limit $L$ at infinity, the solution of the differential equation behaves
asymptotically like the underlying unforced equation when $L=0$, like the
forcing term when $L=+\infty$, and inherits properties of both the forcing term
and underlying differential equation for values of $L\in (0,\infty)$. Our
approach carries over in a natural way to stochastic equations with additive
noise and we treat the illustrative cases of Brownian and L\'evy noise.


title:
Canonical Correlation Analysis for Analyzing Sequences of Medical
  Billing Codes

abstract:
  We propose using canonical correlation analysis (CCA) to generate features
from sequences of medical billing codes. Applying this novel use of CCA to a
database of medical billing codes for patients with diverticulitis, we first
demonstrate that the CCA embeddings capture meaningful relationships among the
codes. We then generate features from these embeddings and establish their
usefulness in predicting future elective surgery for diverticulitis, an
important marker in efforts for reducing costs in healthcare.


title:
On the Christoffel function for the generalized Jacobi measures on a
  quasidisk

abstract:
  We establish the exact (up to the constants) double inequality for the
Christoffel function for a measure supported on a Jordan domain bounded by a
quasiconformal curve. We show that this quasiconformality of the boundary
cannot be omitted.


title: Efficiency at the maximum power output for simple two-level heat engine

abstract:
  We introduce a simple two-level heat engine to study the efficiency in the
condition of the maximum power output, depending on the energy levels from
which the net work is extracted. In contrast to the quasi-statically operated
Carnot engine whose efficiency reaches the theoretical maximum, recent research
on more realistic engines operated in finite time has revealed other classes of
efficiency such as the Curzon-Ahlborn efficiency maximizing the power output.
We investigate yet another side with our heat engine model, which consists of
pure relaxation and net work extraction processes from the population
difference caused by different transition rates. Due to the nature of our
model, the time-dependent part is completely decoupled from the other terms in
the generated work. We derive analytically the optimal condition for transition
rates maximizing the generated power output and discuss its implication on
general premise of realistic heat engines. In particular, the optimal engine
efficiency of our model is different from the Curzon-Ahlborn efficiency,
although they share the universal linear and quadratic coefficients at the
near-equilibrium limit. We further confirm our results by taking an alternative
approach in terms of the entropy production at hot and cold reservoirs.


title: On Lebesgue Constants for Interpolation Points on a Quasiconformal Arc

abstract:
  Using the theory of quasiconformal mappings, we simplify the proof of the
recent result by Taylor and Totik (see IMA Journal of Numerical Analysis 30
(2010) 462--486) on the behavior of the Lebesgue constants for interpolation
points on a compact set in the complex plane.


title: A Bayesian Approach to Predicting Disengaged Youth

abstract:
  This article presents a Bayesian approach for predicting and identifying the
factors which most influence an individual's propensity to fall into the
category of Not in Employment Education or Training (NEET). The approach
partitions the covariates into two groups: those which have the potential to be
changed as a result of an intervention strategy and those which must be
controlled for. This partition allows us to develop models and identify
important factors conditional on the control covariates, which is useful for
clinicians and policy makers who wish to identify potential intervention
strategies. Using the data obtained by O'Dea (2014) we compare the results from
this approach with the results from O'Dea (2014) and with the results obtained
using the Bayesian variable selection procedure of Lamnisos (2009) when the
covariates are not partitioned. We find that the relative importance of
predictive factors varies greatly depending upon the control covariates. This
has enormous implications when deciding on what interventions are most useful
to prevent young people from being NEET.


title: Performance Modeling of Distributed Deep Neural Networks

abstract:
  During the past decade, machine learning has become extremely popular and can
be found in many aspects of our every day life. Nowayadays with explosion of
data while rapid growth of computation capacity, Distributed Deep Neural
Networks (DDNNs) which can improve their performance linearly with more
computation resources, have become hot and trending. However, there has not
been an in depth study of the performance of these systems, and how well they
scale.
  In this paper we analyze CNTK, one of the most commonly used DDNNs, by first
building a performance model and then evaluating the system two settings: a
small cluster with all nodes in a single rack connected to a top of rack
switch, and in large scale using Blue Waters with arbitary placement of nodes.
Our main focus was the scalability of the system with respect to adding more
nodes. Based on our results, this system has an excessive initialization
overhead because of poor I/O utilization which dominates the whole execution
time. Because of this, the system does not scale beyond a few nodes (4 in Blue
Waters). Additionally, due to a single server-multiple worker design the server
becomes a bottleneck after 16 nodes limiting the scalability of the CNTK.


title: A Visual Representation for Editing Face Images

abstract:
  We propose a new approach for editing face images, which enables numerous
exciting applications including face relighting, makeup transfer and face
detail editing. Our face edits are based on a visual representation, which
includes geometry, face segmentation, albedo, illumination and detail map. To
recover our visual representation, we start by estimating geometry using a
morphable face model, then decompose the face image to recover the albedo, and
then shade the geometry with the albedo and illumination. The residual between
our shaded geometry and the input image produces our detail map, which carries
high frequency information that is either insufficiently or incorrectly
captured by our shading process. By manipulating the detail map, we can edit
face images with reality and identity preserved. Our representation allows
various applications. First, it allows a user to directly manipulate various
illumination. Second, it allows non-parametric makeup transfer with input
face's distinctive identity features preserved. Third, it allows non-parametric
modifications to the face appearance by transferring details. For face
relighting and detail editing, we evaluate via a user study and our method
outperforms other methods. For makeup transfer, we evaluate via an online
attractiveness evaluation system, and can reliably make people look younger and
more attractive. We also show extensive qualitative comparisons to existing
methods, and have significant improvements over previous techniques.


title: Photorealistic Facial Texture Inference Using Deep Neural Networks

abstract:
  We present a data-driven inference method that can synthesize a
photorealistic texture map of a complete 3D face model given a partial 2D view
of a person in the wild. After an initial estimation of shape and low-frequency
albedo, we compute a high-frequency partial texture map, without the shading
component, of the visible face area. To extract the fine appearance details
from this incomplete input, we introduce a multi-scale detail analysis
technique based on mid-layer feature correlations extracted from a deep
convolutional neural network. We demonstrate that fitting a convex combination
of feature correlations from a high-resolution face database can yield a
semantically plausible facial detail description of the entire face. A complete
and photorealistic texture map can then be synthesized by iteratively
optimizing for the reconstructed feature correlations. Using these
high-resolution textures and a commercial rendering framework, we can produce
high-fidelity 3D renderings that are visually comparable to those obtained with
state-of-the-art multi-view face capture systems. We demonstrate successful
face reconstructions from a wide range of low resolution input images,
including those of historical figures. In addition to extensive evaluations, we
validate the realism of our results using a crowdsourced user study.


title:
Towards Understanding The B[e] Phenomenon: VI. Nature and Spectral
  Variations of HD 85567

abstract:
  We report the results of high-resolution ($R \sim 80,000$) spectroscopic
observations of the emission-line object HD 85567, which has been classified as
a FS CMa type object or a pre-main-sequence star. The main goal is to put more
constraints on the object's fundamental parameters as well as on its nature and
evolutionary state. Absorption lines in the spectrum of HD 85567 were found
similar to those of mid B--type dwarfs and correspond to the following
fundamental parameters: T$_{\rm eff} = 15000\pm500$ K, $v \sin i = 31\pm3$ km
s$^{-1}$, $\log g \sim 4.0$. The interstellar extinction, A$_V$ $= 0.50\pm0.02$
mag, was measured using the strengths of some diffuse interstellar bands. We
also obtained $UBV(RI)_{\rm c}$ images of a $10^{\prime} \times 10^{\prime}$
region around the object. Photometry of projectionally close stars was used to
derive an interstellar extinction law in this direction and resulted in a
distance of 1300$\pm$100 pc to the object and a luminosity of $\log$
(L/L$_\odot) = 3.3\pm0.2$. We found no significant radial velocity variations
of the absorption lines in the spectra of HD 85567 obtained during two
month-long periods of time in 2012 and 2015. Our analysis of the spectroscopic
and photometric data available for the star led us to a conclusion that it
cannot be a pre-main-sequence Herbig Ae/Be star. We argue that the
circumstellar gas and dust were produced during the object's evolution as most
likely a binary system, which contains an undetected secondary component and is
unlikely to be a merger product.


title: A Noise-Filtering Approach for Cancer Drug Sensitivity Prediction

abstract:
  Accurately predicting drug responses to cancer is an important problem
hindering oncologists' efforts to find the most effective drugs to treat
cancer, which is a core goal in precision medicine. The scientific community
has focused on improving this prediction based on genomic, epigenomic, and
proteomic datasets measured in human cancer cell lines. Real-world cancer cell
lines contain noise, which degrades the performance of machine learning
algorithms. This problem is rarely addressed in the existing approaches. In
this paper, we present a noise-filtering approach that integrates techniques
from numerical linear algebra and information retrieval targeted at filtering
out noisy cancer cell lines. By filtering out noisy cancer cell lines, we can
train machine learning algorithms on better quality cancer cell lines. We
evaluate the performance of our approach and compare it with an existing
approach using the Area Under the ROC Curve (AUC) on clinical trial data. The
experimental results show that our proposed approach is stable and also yields
the highest AUC at a statistically significant level.


title:
Finite time blowup for a supercritical defocusing nonlinear
  Schr\"odinger system

abstract:
  We consider the global regularity problem for defocusing nonlinear
Schr\"odinger systems $$ i \partial_t + \Delta u = (\nabla_{{\bf R}^m} F)(u) +
G $$ on Galilean spacetime ${\bf R} \times {\bf R}^d$, where the field $u\colon
{\bf R}^{1+d} \to {\bf C}^m$ is vector-valued, $F\colon {\bf C}^m \to {\bf R}$
is a smooth potential which is positive, phase-rotation-invariant, and
homogeneous of order $p+1$ outside of the unit ball for some exponent $p >1$,
and $G: {\bf R} \times {\bf R}^d \to {\bf C}^m$ is a smooth, compactly
supported forcing term. This generalises the scalar defocusing nonlinear
Schr\"odinger (NLS) equation, in which $m=1$ and $F(v) = \frac{1}{p+1}
|v|^{p+1}$. In this paper we study the supercritical case where $d \geq 3$ and
$p > 1 + \frac{4}{d-2}$. We show that in this case, there exists a smooth
potential $F$ for some sufficiently large $m$, positive and homogeneous of
order $p+1$ outside of the unit ball, and a smooth compactly choice of initial
data $u(0)$ and forcing term $G$ for which the solution develops a finite time
singularity. In fact the solution is locally discretely self-similar with
respect to parabolic rescaling of spacetime. This demonstrates that one cannot
hope to establish a global regularity result for the scalar defocusing NLS
unless one uses some special property of that equation that is not shared by
these defocusing nonlinear Schr\"odinger systems.
  As in a previous paper of the author considering the analogous problem for
the nonlinear wave equation, the basic strategy is to first select the mass,
momentum, and energy densities of $u$, then $u$ itself, and then finally design
the potential $F$ in order to solve the required equation.


title:
Probing the resonance in the Dirac equation with quadruple-deformed
  potentials by complex momentum representation method

abstract:
  Resonance plays critical roles in the formation of many physical phenomena,
and many techniques have been developed for the exploration of resonance. In a
recent letter [Phys. Rev. Lett. 117, 062502 (2016)], we proposed a new method
for probing single-particle resonances by solving the Dirac equation in complex
momentum representation for spherical nuclei. Here, we extend this method to
deformed nuclei with theoretical formalism presented. We elaborate numerical
details, and calculate the bound and resonant states in $^{37}$Mg. The results
are compared with those from the coordinate representation calculations with a
satisfactory agreement. In particular, the present method can expose clearly
the resonant states in complex momentum plane and determine precisely the
resonance parameters for not only narrow resonances but also broad resonances
that were difficult to obtain before.


title: Quasar Host Galaxies and the $M_{SMBH}$ - $\sigma_{*}$ Relation

abstract:
  We analyze the emission line profiles detected in deep optical spectra of
quasars to derive the mass of their super-massive black holes (SMBH) following
the single-epoch virial method. Our sample consists in 6 radio-loud quasars and
4 radio-quiet quasars. We carefully fit a broad and narrow Gaussian component
for each emission line in both the H$\beta$ (10 objects) and H$\alpha$ regions
(5 objects). A very good agreement of the derived SMBH masses, $M_{\rm SMBH}$,
is found using the fitted broad H$\beta$ and H$\alpha$ emission lines. We
compare our $M_{\rm SMBH}$ results with those found by previous studies. We
study the relationship between the $M_{\rm SMBH}$ of the quasar and the stellar
velocity dispersion, $\sigma_{*}$, of the host galaxy. We use the measured
$M_{\rm SMBH}$ and $\sigma_{*}$ to investigate the $M_{\rm SMBH}$ -
$\sigma_{*}$ relation for both the radio-loud and radio-quiet subsamples.
Besides the scatter, we find a good agreement between radio-quiet quasars and
AGN+quiescent galaxies and between radio-loud quasars and AGN. Our analysis
does not support the hypothesis of using $\sigma$([O III] $\lambda$5007) as a
surrogate for stellar velocity dispersions in high-mass, high-luminosity
quasars. We also investigate the relationship between the 5 GHz radio-continuum
luminosity, $L_{\rm~5\,GHz}$, of the quasar host galaxy with both $M_{\rm
SMBH}$ and $\sigma_{*}$. We do not find any correlation between $L_{\rm
5\,GHz}$ and $M_{\rm SMBH}$, although we observe a trend that galaxies with
larger stellar velocity dispersions have larger $L_{\rm 5\,GHz}$. Using the
results of our fitting for the narrow emission lines of [O III] $\lambda$5007
and [N II] $\lambda$6583 we estimate the gas-phase oxygen abundance of six
quasars, being sub-solar in all cases.


title:
Measurement of the $\tau$ lepton polarization and $R(D^*)$ in the decay
  $\bar{B} \to D^* \tau^- \bar{\nu}_\tau$

abstract:
  We report the first measurement of the $\tau$ lepton polarization
$P_\tau(D^*)$ in the decay $\bar{B} \rightarrow D^* \tau^- \bar{\nu}_\tau$ as
well as a new measurement of the ratio of the branching fractions $R(D^{*}) =
\mathcal{B}(\bar {B} \rightarrow D^* \tau^- \bar{\nu}_\tau) /
\mathcal{B}(\bar{B} \rightarrow D^* \ell^- \bar{\nu}_\ell)$, where $\ell^-$
denotes an electron or a muon, and the $\tau$ is reconstructed in the modes
$\tau^- \rightarrow \pi^- \nu_\tau$ and $\tau^- \rightarrow \rho^- \nu_\tau$.
We use the full data sample of $772 \times 10^6$ $B{\bar B}$ pairs recorded
with the Belle detector at the KEKB electron-positron collider. Our results,
$P_\tau(D^*) = -0.38 \pm 0.51 {\rm (stat.)} ^{+0.21}_{-0.16} {\rm (syst.)}$ and
$R(D^*) = 0.270 \pm 0.035{\rm (stat.)} ^{+0.028}_{-0.025}{\rm (syst.)}$, are
consistent with the theoretical predictions of the Standard Model.


title:
Implementation and evaluation of data-compression algorithms for
  irregular-grid iterative methods on the PEZY-SC processor

abstract:
  Iterative methods on irregular grids have been used widely in all areas of
comptational science and engineering for solving partial differential equations
with complex geometry. They provide the flexibility to express complex shapes
with relatively low computational cost. However, the direction of the evolution
of high-performance processors in the last two decades have caused serious
degradation of the computational efficiency of iterative methods on irregular
grids, because of relatively low memory bandwidth. Data compression can in
principle reduce the necessary memory memory bandwidth of iterative methods and
thus improve the efficiency. We have implemented several data compression
algorithms on the PEZY-SC processor, using the matrix generated for the HPCG
benchmark as an example. For the SpMV (Sparse Matrix-Vector multiplication)
part of the HPCG benchmark, the best implementation without data compression
achieved 11.6Gflops/chip, close to the theoretical limit due to the memory
bandwidth. Our implementation with data compression has achieved 32.4Gflops.
This is of course rather extreme case, since the grid used in HPCG is
geometrically regular and thus its compression efficiency is very high.
However, in real applications, it is in many cases possible to make a large
part of the grid to have regular geometry, in particular when the resolution is
high. Note that we do not need to change the structure of the program, except
for the addition of the data compression/decompression subroutines. Thus, we
believe the data compression will be very useful way to improve the performance
of many applications which rely on the use of irregular grids.


title: Revenue Maximization in Incentivized Social Advertising

abstract:
  Incentivized social advertising, an emerging marketing model, provides
monetization opportunities not only to the owners of the social networking
platforms but also to their influential users by offering a "cut" on the
advertising revenue. We consider a social network (the host) that sells
ad-engagements to advertisers by inserting their ads, in the form of promoted
posts, into the feeds of carefully selected "initial endorsers" or seed users:
these users receive monetary incentives in exchange for their endorsements. The
endorsements help propagate the ads to the feeds of their followers. In this
context, the problem for the host is is to allocate ads to influential users,
taking into account the propensity of ads for viral propagation, and carefully
apportioning the monetary budget of each of the advertisers between incentives
to influential users and ad-engagement costs, with the rational goal of
maximizing its own revenue. We consider a monetary incentive for the
influential users, which is proportional to their influence potential. We show
that revenue maximization in incentivized social advertising corresponds to the
problem of monotone submodular function maximization, subject to a partition
matroid constraint on the ads-to-seeds allocation, and submodular knapsack
constraints on the advertisers' budgets. This problem is NP-hard and we devise
2 greedy algorithms with provable approximation guarantees, which differ in
their sensitivity to seed user incentive costs. Our approximation algorithms
require repeatedly estimating the expected marginal gain in revenue as well as
in advertiser payment. By exploiting a connection to the recent advances made
in scalable estimation of expected influence spread, we devise efficient and
scalable versions of the greedy algorithms.


title: On the covering type of a space

abstract:
  We introduce the notion of the "covering type" of a space, which is more
subtle that the notion of Lusternik Schnirelman category. It measures the
complexity of a space which arises from coverings by contractible subspaces
whose non-empty intersections are also contractible.


title:
Unifying quantum heat transfer in a nonequilibrium spin-boson model with
  full counting statistics

abstract:
  To study the full counting statistics of quantum heat transfer in a driven
nonequilibrium spin-boson model, we develop a generalized nonequilibrium
polaron-transformed Redfield equation with an auxiliary counting field. This
enables us to study the impact of qubit-bath coupling ranging from weak to
strong regimes. Without external modulations, we observe maximal values of both
steady state heat flux and noise power at moderate coupling regimes, below
which we find those two transport quantities are enhanced by the finite qubit
energy bias. With external modulations, the geometric-phase-induced heat flux
shows monotonic decrease as increasing the qubit-bath coupling at zero qubit
energy bias (without bias). While under finite qubit energy bias (with bias),
the geometric-phase-induced heat flux exhibits an interesting reversal behavior
in strong coupling regime. Our results unify the seemingly contradictory
results in weak and strong qubit-bath coupling regimes, and provide detailed
dissections for the quantum fluctuation of nonequilibrium heat transfer.


title:
Object Detection via Aspect Ratio and Context Aware Region-based
  Convolutional Networks

abstract:
  Jointly integrating aspect ratio and context has been extensively studied and
shown performance improvement in traditional object detection systems such as
the DPMs. It, however, has been largely ignored in deep neural network based
detection systems. This paper presents a method of integrating a mixture of
object models and region-based convolutional networks for accurate object
detection. Each mixture component accounts for both object aspect ratio and
multi-scale contextual information explicitly: (i) it exploits a mixture of
tiling configurations in the RoI pooling to remedy the warping artifacts caused
by a single type RoI pooling (e.g., with equally-sized 7 x 7 cells), and to
respect the underlying object shapes more; (ii) it "looks from both the inside
and the outside of a RoI" by incorporating contextual information at two
scales: global context pooled from the whole image and local context pooled
from the surrounding of a RoI. To facilitate accurate detection, this paper
proposes a multi-stage detection scheme for integrating the mixture of object
models, which utilizes the detection results of the model at the previous stage
as the proposals for the current in both training and testing. The proposed
method is called the aspect ratio and context aware region-based convolutional
network (ARC-R-CNN). In experiments, ARC-R-CNN shows very competitive results
with Faster R-CNN [41] and R-FCN [10] on two datasets: the PASCAL VOC and the
Microsoft COCO. It obtains significantly better mAP performance using high IoU
thresholds on both datasets.


title:
Deep Chandra observations of NGC 1404: cluster plasma physics revealed
  by an infalling early-type galaxy

abstract:
  The intracluster medium (ICM), as a magnetized and highly ionized fluid,
provides an ideal laboratory to study plasma physics under extreme conditions
that cannot yet be achieved on Earth. NGC 1404 is a bright elliptical galaxy
that is being gas stripped as it falls through the ICM of the Fornax Cluster.
We use the new {\sl Chandra} X-ray observations of NGC 1404 to study ICM
microphysics. The interstellar medium (ISM) of NGC 1404 is characterized by a
sharp leading edge, 8 kpc from the galaxy center, and a short downstream
gaseous tail. Contact discontinuities are resolved on unprecedented spatial
scales ($0\farcs5=45$\,pc) due to the combination of the proximity of NGC 1404,
the superb spatial resolution of {\sl Chandra}, and the very deep (670 ksec)
exposure. At the leading edge, we observe sub-kpc scale eddies generated by
Kelvin-Helmholtz instability and put an upper limit of 5\% Spitzer on the
isotropic viscosity of the hot cluster plasma. We also observe mixing between
the hot cluster gas and the cooler galaxy gas in the downstream stripped tail,
which provides further evidence of a low viscosity plasma. The assumed ordered
magnetic fields in the ICM ought to be smaller than 5\,$\mu$G to allow KHI to
develop. The lack of evident magnetic draping layer just outside the contact
edge is consistent with such an upper limit.


title:
Ideals generated by traces or by supertraces in the symplectic
  reflection algebra $H_{1,\nu}(I_2(2m+1))$

abstract:
  For each complex number $\nu$, an associative symplectic reflection algebra
$\mathcal H:= H_{1,\nu}(I_2(2m+1))$, based on the group generated by root
system $I_2(2m+1)$, has an $m$-dimensional space of traces and an
$(m+1)$-dimensional space of supertraces. A (super)trace $sp$ is said to be
degenerate if the corresponding bilinear (super)symmetric form
$B_{sp}(x,y)=sp(xy)$ is degenerate. We find all values of the parameter $\nu$
for which either the space of traces contains a degenerate nonzero trace or the
space of supertraces contains a degenerate nonzero supertrace and, as a
consequence, the algebra $\mathcal H$ has a two-sided ideal of null-vectors.
The analogous results for the algebra $H_{1,\nu_1, \nu_2}(I_2(2m))$ are also
presented.


title:
Characteristic free measure rigidity for the action of solvable groups
  on homogeneous spaces

abstract:
  We classify measures on a homogeneous space which are invariant under a
certain solvable subgroup and ergodic under its unipotent radical. Our
treatment is independent of characteristic. As a result we get the first
measure classification for the action of semisimple subgroups without any
characteristic restriction.


title: Daytime Sky Polarization Calibration Limitations

abstract:
  The daytime sky has been recently demonstrated as a useful calibration tool
for deriving polarization cross-talk properties of large astronomical
telescopes. The Daniel K Inouye Solar Telescope (DKIST) and other large
telescopes under construction can benefit from precise polarimetric calibration
of large mirrors. Several atmospheric phenomena and instrumental errors
potentially limit the techniques accuracy. At the 3.67m AEOS telescope on
Haleakala, we have performed a large observing campaign with the HiVIS
spectropolarimeter to identify limitations and develop algorithms for
extracting consistent calibrations. Effective sampling of the telescope optical
configurations and filtering of data for several derived parameters provide
robustness to the derived Mueller matrix calibrations. Second-order scattering
models of the sky show that this method is relatively insensitive to
multiple-scattering in the sky provided calibration observations are done in
regions of high polarization degree. The technique is also insensitive to
assumptions about telescope induced polarization provided the mirror coatings
are highly reflective. Zemax-derived polarization models show agreement between
the functional dependence of polarization predictions and the corresponding
on-sky calibrations.


title:
Dimensional lower bounds for Falconer type incidence and point
  configuration theorems

abstract:
  Let $1 \leq k \leq d$ and consider a subset $E\subset \mathbb{R}^d$. In this
paper, we study the problem of how large the Hausdorff dimension of $E$ must be
in order for the set of distinct noncongruent $k$-simplices in $E$ (that is,
noncongruent point configurations of $k+1$ points from $E$) to have positive
Lebesgue measure. This generalizes the $k=1$ case, the well-known Falconer
distance problem and a major open problem in geometric measure theory. We
establish a dimensional lower threshold of $\frac{d(k+1)}{d+2}$ for Falconer
type theorems for $k$-simplices. This threshold is nontrivial in the range $d/2
\leq k \leq d$ and is obtained through counting simplices in a standard lattice
using results of the Gauss circle problem. Many results on Falconer type
theorems have been established through incidence theorems, which generally
establish sufficient but not necessary conditions for the point configuration
theorems. We also establish a dimensional lower threshold of $\frac{d+1}{2}$ on
incidence theorems for $k$-simplices where $k\leq d \leq 2k+1$ by generalizing
an example of Mattila. Finally, we prove a dimensional lower threshold of
$\frac{d+1}{2}$ on incidence theorems for triangles in a convex setting in
every dimension greater than $3$. This last result generalizes work by Iosevich
and Senger on distances that was built on a construction by Valtr. The final
result utilizes number-theoretic machinery to estimate the number of solutions
to a Diophantine equation.


title:
Reactors as a source of antineutrinos: the effect of fuel loading and
  burnup for mixed oxide fuels

abstract:
  In a conventional light water reactor loaded with a range of uranium and
plutonium-based fuel mixtures, the variation in antineutrino production over
the cycle reflects both the initial core fissile inventory and its evolution.
Under the assumption of constant thermal power, we calculate the rate at which
antineutrinos are emitted from variously fueled cores, and the evolution of
that rate as measured by a representative ton-scale antineutrino detector. We
find that antineutrino flux decreases with burnup for Low Enriched Uranium
cores, increases for full mixed-oxide (MOX) cores, and does not appreciably
change for cores with a MOX fraction of approximately 75%. Accounting for
uncertainties in the fission yields, in the emitted antineutrino spectra, and
the detector response function, we show that the difference in core-wide MOX
fractions at least as small as 8% can be distinguished using a hypothesis test.
The test compares the evolution of the antineutrino rate relative to an initial
value over part or all of the cycle. The use of relative rates reduces the
sensitivity of the test to an independent thermal power measurement, making the
result more robust against possible countermeasures. This rate-only approach
also offers the potential advantage of reducing the cost and complexity of the
antineutrino detectors used to verify the diversion, compared to methods that
depend on the use of the antineutrino spectrum. A possible application is the
verification of the disposition of surplus plutonium in nuclear reactors.


title: A May-type spectral sequence for higher topological Hochschild homology

abstract:
  Given a filtration of a commutative monoid $A$ in a symmetric monoidal stable
model category $\mathcal{C}$, we construct a spectral sequence analogous to the
May spectral sequence whose input is the higher order topological Hochschild
homology of the associated graded commutative monoid of $A$, and whose output
is the higher order topological Hochschild homology of $A$. We then construct
examples of such filtrations and derive some consequences: for example, given a
connective commutative graded ring $R$, we get an upper bound on the size of
the $THH$-groups of $E_{\infty}$-ring spectra $A$ such that $\pi_*(A) \cong R$.


title:
Breast Mass Classification from Mammograms using Deep Convolutional
  Neural Networks

abstract:
  Mammography is the most widely used method to screen breast cancer. Because
of its mostly manual nature, variability in mass appearance, and low
signal-to-noise ratio, a significant number of breast masses are missed or
misdiagnosed. In this work, we present how Convolutional Neural Networks can be
used to directly classify pre-segmented breast masses in mammograms as benign
or malignant, using a combination of transfer learning, careful pre-processing
and data augmentation to overcome limited training data. We achieve
state-of-the-art results on the DDSM dataset, surpassing human performance, and
show interpretability of our model.


title:
Vaidya solution and its generalization in de Rham-Gabadadze-Tolley
  massive gravity

abstract:
  We present a detailed study of the Vaidya solution and its generalization in
de Rham-Gabadadze-Tolley (dRGT) theory. Since the diffeomorphism invariance can
be restored with the St\"{u}ckelberg fields $\phi^a$ introduced, there is a new
invariant $I^{ab}=g^{\mu \nu}\partial_\mu \phi^a\partial_\nu \phi^b$ in the
massive gravity, which adds to the ones usually encountered in general
relativity. There is no conventional Vaidya solution if we choose unitary
gauge. In this paper, we obtain three types of self-consistent ansatz with some
nonunitary gauge, and find accordingly the Vaidya, generalized Vaidya and furry
Vaidya solution. As by-products, we obtain a series of furry black hole. The
Vaidya solution and its generalization in dRGT massive gravity describe the
black holes with a variable horizon.


title: A Natural Min-Max Construction for Ginzburg-Landau Functionals

abstract:
  We use min-max techniques to produce nontrivial solutions $u_{\epsilon}:M\to
\mathbb{R}^2$ of the Ginzburg-Landau equation $\Delta
u_{\epsilon}+\frac{1}{\epsilon^2}(1-|u_{\epsilon}|^2)u_{\epsilon}=0$ on a given
compact Riemannian manifold, whose energy grows like $|\log\epsilon|$ as
$\epsilon\to 0$. When the degree one cohomology $H^1_{dR}(M)=0$, we show that
the energy of these solutions concentrates on a nontrivial stationary,
rectifiable $(n-2)$-varifold $V$.


title: Dendritic cell-cluster metasurface manipulation of visible light

abstract:
  The manipulation of visible light is important in science and technology
research. Metasurfaces can enable flexible and effective regulation of the
phase, polarization, and propagation modes of an electromagnetic wave.
Metasurfaces have become a research hotspot in optics and electromagnetics, and
cross-polarization conversion is an important application for visible-light
manipulation using a metasurface. A metasurface composed of nano-antenna arrays
and bilayer plasma can reportedly convert the direction of linear polarized
light efficiently. However, the metasurface of cross-polarization conversion
operating in short-wavelength visible light is problematic. In addition,
previous metasurfaces prepared using the top-down etching method is unsuitable
for practical applications because of the necessary harsh experimental
conditions and the high construction cost of preparation. In the present work,
we suggest a dendritic cell-cluster metasurface achieve cross-polarization in
transmission mode within 550, 570, 590 and 610 nm wavelength. Preparation is
accomplished using a bottom-up electrochemical deposition method, which is easy
and low cost. The dendritic cell-cluster metasurface is an important step in
cross-polarization conversion research and has broad application prospects and
development potential.


title:
Exact $P_s T_d$ Invariant and $P_s T_d$ Symmetric Breaking solutions,
  Symmetry Reductions and B\"{a}cklund Transformations For An AB-KdV System

abstract:
  In natural and social science, many events happened at different space-times
may be closely correlated. Two events, A (Alice) and B (Bob) are defined as
correlated if one event is determined by another, say, $B=\hat{f} A$ for
suitable $\hat{f}$ operators. A nonlocal AB-KdV system with shifted-parity
($P_s$, parity with a shift), delayed time reversal ($T_d$, time reversal with
a delay) symmetry where $B=\hat{P_s}\hat{T_d} A$ is constructed directly from
the normal KdV equation to describe two-area physical event. The exact
solutions of the AB-KdV system, including $P_s T_d$ invariant and $P_s T_d$
symmetric breaking solutions are shown by different methods. The $P_s T_d$
invariant solution show that the event happened at $A$ will happen also at $B$.
These solutions, such as single soliton solutions, infinitely many singular
soliton solutions, soliton-cnoidal wave interaction solutions, and symmetry
reduction solutions etc., show the AB-KdV system possesses rich structures.
Also, a special B\"{a}cklund transformation related to residual symmetry is
presented via the localization of the residual symmetry to find interaction
solutions between the solitons and other types of the AB-KdV system.


title:
Gradient Descent Efficiently Finds the Cubic-Regularized Non-Convex
  Newton Step

abstract:
  We consider the minimization of non-convex quadratic forms regularized by a
cubic term, which exhibit multiple saddle points and poor local minima.
Nonetheless, we prove that, under mild assumptions, gradient descent
approximates the $\textit{global minimum}$ to within $\varepsilon$ accuracy in
$O(\varepsilon^{-1}\log(1/\varepsilon))$ steps for large $\varepsilon$ and
$O(\log(1/\varepsilon))$ steps for small $\varepsilon$ (compared to a condition
number we define), with at most logarithmic dependence on the problem
dimension. When we use gradient descent to approximate the Nesterov-Polyak
cubic-regularized Newton step, our result implies a rate of convergence to
second-order stationary points of general smooth non-convex functions.


title: On topological Hochschild homology of the $K(1)$-local sphere

abstract:
  We compute topological Hochschild homology mod $p$ and $v_1$ of the
connective cover of the $K(1)$-local sphere spectrum for all primes $p\ge 3$.
This is accomplished using a May-type spectral sequence in topological
Hochschild homology constructed from a filtration of a commutative ring
spectrum.


title: MF is always superior to CEM

abstract:
  The constrained energy minimization (CEM) and matched filter (MF) are two
most frequently used target detection algorithms in the remotely sensed
community. In this paper, we first introduce an augmented CEM (ACEM) by adding
an all-one band. According to a recently published conclusion that CEM can
always achieve a better performance by adding any linearly independent bands,
ACEM is better than CEM. Further, we prove that ACEM is mathematically
equivalent to MF. As a result, we can conclude that the classical matched
filter (MF) is always superior to the CEM operator.


title:
Haldane phase in the sawtooth lattice: Edge states, entanglement
  spectrum and the flat band

abstract:
  Using density matrix renormalization group numerical calculations, we study
the phase diagram of the half filled Bose-Hubbard system in the sawtooth
lattice with strong frustration in the kinetic energy term. We focus in
particular on values of the hopping terms which produce a flat band and show
that, in the presence of contact and near neighbor repulsion, three phases
exist: Mott insulator (MI), charge density wave (CDW), and the topological
Haldane insulating (HI) phase which displays edge states and particle imbalance
between the two ends of the system. We find that, even though the entanglement
spectrum in the Haldane phase is not doubly degenerate, it is in excellent
agreement with the entanglement spectrum of the Affleck-Kennedy-Lieb-Tasaki
(AKLT) state built in the Wannier basis associated with the flat band. This
emphasizes that the absence of degeneracy in the entanglement spectrum is not
necessarily a signature of a non-topological phase, but rather that the
(hidden) protecting symmetry involves non-local states. Finally, we also show
that the HI phase is stable against small departure from flatness of the band
but is destroyed for larger ones.


title:
A Classical and Spinorial Description of the Relativistic Spinning
  Particle

abstract:
  In a previous work we showed that spin can be envisioned as living in a phase
space that is dual to the standard phase space of position and momentum. In
this work we demonstrate that the second class constraints inherent in this
"Dual Phase Space" picture can be solved by introducing a spinorial
parameterization of the spinning degrees of freedom. This allows for a purely
first class formulation that generalizes the usual relativistic description of
spinless particles and provides several insights into the nature of spin and
its relationship with spacetime and locality. In particular, we find that the
spin motion acts as a Lorentz contraction on the four-velocity and that, in
addition to proper time, spinning particles posses a second gauge invariant
observable which we call proper angle. Heuristically, this proper angle
represents the amount of Zitterbewegung necessary for a spin transition to
occur. Additionally, we show that the spin velocity satisfies a causality
constraint, and even more stringently, that it is constant along classical
trajectories. This leads to the notion of "half-quantum" states which violate
the classical equations of motion, and yet do not experience an exponential
suppression in the path integral. Finally we give a full analysis of the
Poisson bracket structure of this new parametrization.


title:
Massive Non-Orthogonal Multiple Access for Cellular IoT: Potentials and
  Limitations

abstract:
  The Internet of Things (IoT) promises ubiquitous connectivity of everything
everywhere, which represents the biggest technology trend in the years to come.
It is expected that by 2020 over 25 billion devices will be connected to
cellular networks; far beyond the number of devices in current wireless
networks. Machine-to-Machine (M2M) communications aims at providing the
communication infrastructure for enabling IoT by facilitating the billions of
multi-role devices to communicate with each other and with the underlying data
transport infrastructure without, or with little, human intervention. Providing
this infrastructure will require a dramatic shift from the current protocols
mostly designed for human-to-human (H2H) applications. This article reviews
recent 3GPP solutions for enabling massive cellular IoT and investigates the
random access strategies for M2M communications, which shows that cellular
networks must evolve to handle the new ways in which devices will connect and
communicate with the system. A massive non-orthogonal multiple access (NOMA)
technique is then presented as a promising solution to support a massive number
of IoT devices in cellular networks, where we also identify its practical
challenges and future research directions.


title:
First-principles design of the spinel iridate Ir2O4 for high-temperature
  quantum spin ice

abstract:
  Insulating magnetic rare-earth pyrochlores related to spin ice host emergent
bosonic monopolar spinons, which obey a magnetic analogue of quantum
electrodynamics and may open a route to a magnetic analogue of electronics.
However, the energy scales of the interactions among rare-earth moments are so
low as 1 K that the possible quantum coherence can only be achieved at a
sub-Kelvin. Here, we desgin high-temperature quantum spin ice materials from
first principles. It is shown that the A-site deintercalated spinel iridate
Ir2O4, which has been experimentally grown as epitaxial thin films, is a
promising candidate for quantum spin ice with a spin-ice-rule interaction of a
few tens of meV. Controlling electronic structures of Ir2O4 through substrates,
it is possible to tune magnetic interactions so that a magnetic Coulomb liquid
persists at high temperatures.


title: Higher Order Mutual Information Approximation for Feature Selection

abstract:
  Feature selection is a process of choosing a subset of relevant features so
that the quality of prediction models can be improved. An extensive body of
work exists on information-theoretic feature selection, based on maximizing
Mutual Information (MI) between subsets of features and class labels. The prior
methods use a lower order approximation, by treating the joint entropy as a
summation of several single variable entropies. This leads to locally optimal
selections and misses multi-way feature combinations. We present a higher order
MI based approximation technique called Higher Order Feature Selection (HOFS).
Instead of producing a single list of features, our method produces a ranked
collection of feature subsets that maximizes MI, giving better comprehension
(feature ranking) as to which features work best together when selected, due to
their underlying interdependent structure. Our experiments demonstrate that the
proposed method performs better than existing feature selection approaches
while keeping similar running times and computational complexity.


title:
Transfer Learning via Latent Factor Modeling to Improve Prediction of
  Surgical Complications

abstract:
  We aim to create a framework for transfer learning using latent factor models
to learn the dependence structure between a larger source dataset and a target
dataset. The methodology is motivated by our goal of building a risk-assessment
model for surgery patients, using both institutional and national surgical
outcomes data. The national surgical outcomes data is collected through NSQIP
(National Surgery Quality Improvement Program), a database housing almost 4
million patients from over 700 different hospitals. We build a latent factor
model with a hierarchical prior on the loadings matrix to appropriately account
for the different covariance structure in our data. We extend this model to
handle more complex relationships between the populations by deriving a scale
mixture formulation using stick-breaking properties. Our model provides a
transfer learning framework that utilizes all information from both the source
and target data, while modeling the underlying inherent differences between
them.


title: The Eigenvalue Spectrum of the Inertia Operator

abstract:
  We view the inertia construction of algebraic stacks as an operator on the
Grothendieck groups of various categories of algebraic stacks. We show that the
inertia operator is locally finite and diagonalizable. This is proved for the
Grothendieck group of Deligne-Mumford stacks over a base scheme and the
category of quasi-split Artin stacks defined over a field of characteristic
zero. Motivated by the quasi-splitness condition, in [2] we consider the
inertia operator of the Hall algebra of algebroids, and applications of it in
generalized Donaldson-Thomas theory.


title: A precise measure of avian magnetoreception based on quantum metrology

abstract:
  The radical pair (RP) mechanism, which describes the quantum dynamics of a
spatially separated electron pair, is considered as one of the principal models
of avian magnetoreception. Different from the conventional phenomenological
approach where the sensitivity of avian magnetoreception is characterized by
the singlet yield $\Phi_{S}$, we introduce the quantum Fisher information
(QFI), which represents the maximum information about the magnetic field's
direction extracted from the RP state, to give a precise measure of sensitivity
of avian compass essentially. The consistency between our results and
experimental observations suggests that QFI plays a decisive role in avian
magnetoreception. Besides, within the framework of quantum metrology, we can
judge the feasibility of any possible measurement scheme for avian
magnetoreception, and shed light on an intrinsic relevance between the singlet
yield and a concrete measurement scheme of our approach. The present work
allows us to understand many things about avian magnetoreception from a fully
new perspective of quantum metrology, and provide a new route to establish a
direct connection between quantum information and many other biological
functions.


title: Unsupervised Human Action Detection by Action Matching

abstract:
  We propose a new task of unsupervised action detection by action matching.
Given two long videos, the objective is to temporally detect all pairs of
matching video segments. A pair of video segments are matched if they share the
same human action. The task is category independent---it does not matter what
action is being performed---and no supervision is used to discover such video
segments. Unsupervised action detection by action matching allows us to align
videos in a meaningful manner. As such, it can be used to discover new action
categories or as an action proposal technique within, say, an action detection
pipeline. Moreover, it is a useful pre-processing step for generating video
highlights, e.g., from sports videos.
  We present an effective and efficient method for unsupervised action
detection. We use an unsupervised temporal encoding method and exploit the
temporal consistency in human actions to obtain candidate action segments. We
evaluate our method on this challenging task using three activity recognition
benchmarks, namely, the MPII Cooking activities dataset, the THUMOS15 action
detection benchmark and a new dataset called the IKEA dataset. On the MPII
Cooking dataset we detect action segments with a precision of 21.6% and recall
of 11.7% over 946 long video pairs and over 5000 ground truth action segments.
Similarly, on THUMOS dataset we obtain 18.4% precision and 25.1% recall over
5094 ground truth action segment pairs.


title: Poisson Geometry from a Dirac perspective

abstract:
  We present proofs of classical results in Poisson geometry using techniques
from Dirac geometry. This article is based on mini-courses at the Poisson
summer school in Geneva, June 2016, and at the workshop "Quantum Groups and
Gravity" at the University of Waterloo, April 2016.


title: Zero-Shot Learning posed as a Missing Data Problem

abstract:
  This paper presents a method of zero-shot learning (ZSL) which poses ZSL as
the missing data problem, rather than the missing label problem. Specifically,
most existing ZSL methods focus on learning mapping functions from the image
feature space to the label embedding space. Whereas, the proposed method
explores a simple yet effective transductive framework in the reverse way \---
our method estimates data distribution of unseen classes in the image feature
space by transferring knowledge from the label embedding space. In experiments,
our method outperforms the state-of-the-art on two popular datasets.


title: Top and bottom tensor couplings from a color octet scalar

abstract:
  We compute the one-loop contributions from a color octet scalar to the tensor
anomalous couplings of top and bottom quarks to gluons, photons and W bosons.
We use known constraints on the parameters of the model to compare the
predicted size of these couplings with existing phenomenological constraints.


title:
Analysis of $L1$-Galerkin FEMs for time-fractional nonlinear parabolic
  problems

abstract:
  This paper is concerned with numerical solutions of time-fractional nonlinear
parabolic problems by a class of $L1$-Galerkin finite element methods. The
analysis of $L1$ methods for time-fractional nonlinear problems is limited
mainly due to the lack of a fundamental Gronwall type inequality. In this
paper, we establish such a fundamental inequality for the $L1$ approximation to
the Caputo fractional derivative. In terms of the Gronwall type inequality, we
provide optimal error estimates of several fully discrete linearized Galerkin
finite element methods for nonlinear problems. The theoretical results are
illustrated by applying our proposed methods to three examples: linear
Fokker-Planck equation, nonlinear Huxley equation and Fisher equation.


title: Self-critical Sequence Training for Image Captioning

abstract:
  Recently it has been shown that policy-gradient methods for reinforcement
learning can be utilized to train deep end-to-end systems directly on
non-differentiable metrics for the task at hand. In this paper we consider the
problem of optimizing image captioning systems using reinforcement learning,
and show that by carefully optimizing our systems using the test metrics of the
MSCOCO task, significant gains in performance can be realized. Our systems are
built using a new optimization approach that we call self-critical sequence
training (SCST). SCST is a form of the popular REINFORCE algorithm that, rather
than estimating a "baseline" to normalize the rewards and reduce variance,
utilizes the output of its own test-time inference algorithm to normalize the
rewards it experiences. Using this approach, estimating the reward signal (as
actor-critic methods must do) and estimating normalization (as REINFORCE
algorithms typically do) is avoided, while at the same time harmonizing the
model with respect to its test-time inference procedure. Empirically we find
that directly optimizing the CIDEr metric with SCST and greedy decoding at
test-time is highly effective. Our results on the MSCOCO evaluation sever
establish a new state-of-the-art on the task, improving the best result in
terms of CIDEr from 104.9 to 114.7.


title:
Metric and topological entropy bounds for optimal coding of stochastic
  dynamical systems

abstract:
  We consider the problem of optimal zero-delay coding and estimation of a
stochastic dynamical system over a noisy communication channel under three
estimation criteria concerned with the low-distortion regime. The criteria
considered are (i) a strong and (ii) a weak form of almost sure stability of
the estimation error as well as (ii) quadratic stability in expectation. For
all three objectives, we derive lower bounds on the smallest channel capacity
$C_0$ above which the objective can be achieved with an arbitrarily small
error. We first obtain bounds through a dynamical systems approach by
constructing an infinite-dimensional dynamical system and relating the capacity
with the topological and the metric entropy of this dynamical system. We also
consider information-theoretic and probability-theoretic approaches to address
the different criteria. Finally, we prove that a memoryless noisy channel in
general constitutes no obstruction to asymptotic almost sure state estimation
with arbitrarily small errors, when there is no noise in the system. The
results provide new solution methods for the criteria introduced (e.g.,
standard information-theoretic bounds cannot be applied for some of the
criteria) and establish further connections between dynamical systems,
networked control, and information theory, and especially in the context of
nonlinear stochastic systems.


title: Programming by Demonstration with User-Specified Perceptual Landmarks

abstract:
  Programming by demonstration (PbD) is an effective technique for developing
complex robot manipulation tasks, such as opening bottles or using human tools.
In order for such tasks to generalize to new scenes, the robot needs to be able
to perceive objects, object parts, or other task-relevant parts of the scene.
Previous work has relied on rigid, task-specific perception systems for this
purpose. This paper presents a flexible and open-ended perception system that
lets users specify perceptual "landmarks" during the demonstration, by
capturing parts of the point cloud from the demonstration scene. We present a
method for localizing landmarks in new scenes and experimentally evaluate this
method in a variety of settings. Then, we provide examples where user-specified
landmarks are used together with PbD on a PR2 robot to perform several complex
manipulation tasks. Finally, we present findings from a user evaluation of our
landmark specification interface demonstrating its feasibility as an end-user
tool.