title: CAD2RL: Real Single-Image Flight without a Single Real Image

abstract:
  Deep reinforcement learning has emerged as a promising and powerful technique
for automatically acquiring control policies that can process raw sensory
inputs, such as images, and perform complex behaviors. However, extending deep
RL to real-world robotic tasks has proven challenging, particularly in
safety-critical domains such as autonomous flight, where a trial-and-error
learning process is often impractical. In this paper, we explore the following
question: can we train vision-based navigation policies entirely in simulation,
and then transfer them into the real world to achieve real-world flight without
a single real training image? We propose a learning method that we call
CAD$^2$RL, which can be used to perform collision-free indoor flight in the
real world while being trained entirely on 3D CAD models. Our method uses
single RGB images from a monocular camera, without needing to explicitly
reconstruct the 3D geometry of the environment or perform explicit motion
planning. Our learned collision avoidance policy is represented by a deep
convolutional neural network that directly processes raw monocular images and
outputs velocity commands. This policy is trained entirely on simulated images,
with a Monte Carlo policy evaluation algorithm that directly optimizes the
network's ability to produce collision-free flight. By highly randomizing the
rendering settings for our simulated training set, we show that we can train a
policy that generalizes to the real world, without requiring the simulator to
be particularly realistic or high-fidelity. We evaluate our method by flying a
real quadrotor through indoor environments, and further evaluate the design
choices in our simulator through a series of ablation studies on depth
prediction. For supplementary video see: https://youtu.be/nXBWmzFrj5s


title:
Physical mechanisms of micro- and nanodomain formation in multicomponent
  lipid membranes

abstract:
  This article summarizes a variety of physical mechanisms proposed in the
literature, which can generate micro- and nanodomains in multicomponent lipid
bilayers and biomembranes. It mainly focusses on lipid-driven mechanisms that
do not involve direct protein-protein interactions. Specifically, it considers
(i) equilibrium mechanisms based on lipid-lipid phase separation such as
critical cluster formation close to critical points, and multiple domain
formation in curved geometries, (ii) equilibrium mechanisms that stabilize
two-dimensional microemulsions, such as the effect of linactants and the effect
of curvature-composition coupling in bilayers and monolayers, and (iii)
non-equilibrium mechanisms induced by the interaction of a biomembrane with the
cellular environment, such as membrane recycling and the pinning effects of the
cytoplasm. Theoretical predictions are discussed together with simulations and
experiments. The presentation is guided by the theory of phase transitions and
critical phenomena, and the appendix summarizes the mathematical background in
a concise way within the framework of the Ginzburg-Landau theory.


title: Polar Coding for Non-Stationary Channels

abstract:
  The problem of polar coding for an arbitrary sequence of independent
binary-input memoryless symmetric (BMS) channels $\left\{W_i\right\}_{i=1}^{N}$
is considered. The sequence of channels is assumed to be completely known to
both the transmitter and the receiver (a coherent scenario). Also, at each code
block transmission, each of the channels is used only once. In other words, a
codeword of length $N$ is constructed and then the $i$-th encoded bit is
transmitted over $W_i$. The goal is to operate at a rate $R$ close to the
average of the symmetric capacities of $W_i$'s, denoted by $\overline{I}_N$. To
this end, we construct a polar coding scheme using Arikan's channel
polarization transform in combination with certain permutations at each
polarization level and certain skipped operations. In particular, given a
non-stationary sequence of BMS channels $\left\{W_i\right\}_{i=1}^{N}$ and
$P_e$, where $0 < P_e <1$, we construct a polar code of length $N$ and rate $R$
guaranteeing a block error probability of at most $P_e$ for transmission over
$\left\{W_i\right\}_{i=1}^{N}$ such that $$ N \leq
\frac{\kappa}{(\overline{I}_N - R)^{\mu}}, $$ where $\mu$ is a constant and
$\kappa$ is a constant depending on $P_e$ and $\mu$. We further show a
numerical upper bound on $\mu$ that is: $\mu \leq 7.34$ for non-stationary
binary erasure channels and $\mu \leq 8.54$ for general non-stationary BMS
channels. The encoding and decoding complexities of the constructed polar code
preserve $O(N \log N)$ complexity of Arikan's polar codes. In an asymptotic
sense, when coded bits are transmitted over a non-stationary sequence of BMS
channels $\left\{W_i\right\}_{i=1}^{\infty}$, our proposed scheme achieves the
average symmetric capacity $$ \overline{I}(\left\{W_i\right\}_{i=1}^{\infty})
:= \lim_{N\rightarrow \infty} \frac{1}{N}\sum_{i=1}^N I(W_i), $$ assuming that
the limit exists.


title: Coupled, multi-strain epidemic models of mutating pathogens

abstract:
  We introduce and analyze coupled, multi-strain epidemic models designed to
simulate the emergence and dissemination of mutant (e.g. drug-resistant)
pathogen strains. In particular, we investigate the mathematical and biological
properties of a general class of multi-strain epidemic models in which the
infectious compartments of each strain are coupled together in a general
manner. We derive explicit expressions for the basic reproduction number of
each strain and highlight their importance in regulating the system dynamics
(e.g. the potential for an epidemic outbreak) and the existence of nonnegative
endemic solutions. Importantly, we find that the basic reproduction number of
each strain is independent of the mutation rates between the strains --- even
under quite general assumptions for the form of the infectious compartment
coupling. Moreover, we verify that the coupling term promotes strain
coexistence (as an extension of the competitive exclusion principle) and
demonstrate that the strain with the greatest reproductive capacity is not
necessarily the most prevalent. Finally, we briefly discuss the implications of
our results for public health policy and planning.


title: Neutron-antineutron oscillations beyond the quasi-free limit

abstract:
  Prompted by plans to conduct a new neutron oscillation experiment at the
European Spallation Source (ESS), we consider issues associated with the
magnetic field that must be present, some of which are potentially exacerbated
by the significantly larger length $l$ contemplated for the neutron propagation
region. To this end, we introduce a stochastic model of the residual magnetic
field within the propagation region which draws on features of magnetic
profiles measured during the last free neutron oscillation experiment
[conducted at the Institut Laue-Langevin (ILL) in the 1990's]. We average over
both fluctuations in the magnetic field sampled by neutrons, and representative
spectra of neutron speeds. We find that deviations from the quasi-free result
for the antineutron probability do not depend quadratically on $l$ (as a naive
perturbative estimate would suggest) but increase only linearly with $l$. As
regards the large spikes in the magnetic field which can be expected at, for
example, joints in the magnetic shielding of the propagation region (despite
compensating currents and magnetic idealization of the shield), we demonstrate
that their effect scales as $l/D^{3/2}$, where $D$ is the diameter of the
cylindrical magnetic shielding. Our arguments suggest that, provided the
dimensions of the propagation region are such that the ratio $l/D^{3/2}$ does
not exceed the value pertinent to the ILL experiment, and these spikes occur
close to either end of the propagation region, they can be neglected. We also
establish that any large magnetic field encountered after the propagation
region is exited will not diminish the probability for antineutron detection.
For the range of values of $l$ of most interest to the ESS experiment, it
should suffice to improve on the level of magnetic suppression achieved at the
ILL by a factor of two.


title: The Effective Temperature Concept Tested in an Active Colloid Mixture

abstract:
  Thermal energy agitates all matter and its competition with ordering
tendencies is one of the most fundamental organizing principles in the physical
world. Thus, it is natural to enquire if an effective temperature could result
when external energy input enhances agitation. Potentially this could extend
the insights of statistical thermodynamics to nonequilibrium systems, but
despite proposals that the effective temperature concept may apply to synthetic
active matter, biological motors, granular materials and turbulent fluids, its
predictive value remains unclear. Here, combining computer simulations and
imaging experiments, we design a two-component system of driven Janus colloids
such that collisions produced by external energy sources play the role of
temperature, and in this system we demonstrate quantitative agreement with
hallmarks of statistical thermodynamics for binary phase behavior: the
archetypal phase diagram with equilibrium critical exponents, Gaussian
displacement distributions, fluctuation-dissipation relations, and capillarity.
These quantitative analogies to equilibrium expectations, observed in this
decidedly nonequilibrium system, constitute an existence proof from which to
compare future theories of nonequilibrium, but limitations of this concept are
also highlighted.


title:
On the superlinear convergence of Newton's method on Riemannian
  manifolds

abstract:
  In this paper we study the Newton's method for finding a singularity of a
differentiable vector field defined on a Riemannian manifold. Under the
assumption of invertibility of covariant derivative of the vector field at its
singularity, we establish the well definition of the method in a suitable
neighborhood of this singularity. Moreover, we also show that the generated
sequence by Newton method converges for the solution with superlinear rate.


title:
Joint mean and covariance estimation with unreplicated matrix-variate
  data

abstract:
  It has been proposed that complex populations, such as those that arise in
genomics studies, may exhibit dependencies among observations as well as among
variables. This gives rise to the challenging problem of analyzing unreplicated
high-dimensional data with unknown mean and dependence structures.
Matrix-variate approaches that impose various forms of (inverse) covariance
sparsity allow flexible dependence structures to be estimated, but cannot
directly be applied when the mean and covariance matrices are estimated
jointly. We present a practical method utilizing generalized least squares and
penalized (inverse) covariance estimation to address this challenge. We
establish consistency and obtain rates of convergence for estimating the mean
parameters and covariance matrices. The advantages of our approaches are: (i)
dependence graphs and covariance structures can be estimated in the presence of
unknown mean structure, (ii) the mean structure becomes more efficiently
estimated when accounting for the dependence structure among observations; and
(iii) inferences about the mean parameters become correctly calibrated. We use
simulation studies and analysis of genomic data from a twin study of ulcerative
colitis to illustrate the statistical convergence and the performance of our
methods in practical settings. Several lines of evidence show that the test
statistics for differential gene expression produced by our methods are
correctly calibrated and improve power over conventional methods.


title: Asymptotically Optimal Amplifiers for the Moran Process

abstract:
  We study the Moran process as adapted by Lieberman, Hauert and Nowak. This is
a model of an evolving population on a graph or digraph where certain
individuals, called "mutants" have fitness r and other individuals, called
non-mutants have fitness 1. We focus on the situation where the mutation is
advantageous, in the sense that r>1. A family of digraphs is said to be
strongly amplifying if the extinction probability tends to 0 when the Moran
process is run on digraphs in this family. The most-amplifying known family of
digraphs is the family of megastars of Galanis et al. We show that this family
is optimal, up to logarithmic factors, since every strongly-connected n-vertex
digraph has extinction probability Omega(n^(-1/2)). Next, we show that there is
an infinite family of undirected graphs, called dense incubators, whose
extinction probability is O(n^(-1/3)). We show that this is optimal, up to
constant factors. Finally, we introduce sparse incubators, for varying edge
density, and show that the extinction probability of these graphs is O(n/m),
where m is the number of edges. Again, we show that this is optimal, up to
constant factors.


title: Critical behavior in porous media flow

abstract:
  The intermittent burst dynamics during the slow drainage of a porous medium
is studied experimentally. We have shown that this system satisfies a set of
conditions known to be true for critical systems, such as intermittent activity
with bursts extending over several time and length scales, self-similar
macroscopic fractal structure and $1/f^\alpha$ power spectrum. Additionally, we
have verified a theoretically predicted scaling for the burst size
distribution, previously assessed via numerical simulations. The observation of
$1/f^\alpha$ power spectra is new for porous media flows and, for specific
boundary conditions, we notice the occurrence of a transition from $1/f$ to
$1/f^2$ scaling. An analytically integrable mathematical framework was employed
to explain this behavior.


title: On Location Hiding in Distributed Systems

abstract:
  We consider the following problem - a group of mobile agents perform some
task on a terrain modeled as a graph. In a given moment of time an adversary
gets an access to the graph and positions of the agents. Shortly before
adversary's observation the mobile agents have a chance to relocate themselves
in order to hide their initial configuration. We assume that the initial
configuration may possibly reveal to the adversary some information about the
task they performed. Clearly agents have to change their location in possibly
short time using minimal energy. In our paper we introduce a definition of a
\emph{well hiding} algorithm in which the starting and final configurations of
the agents have small mutual information. Then we discuss the influence of
various features of the model on the running time of the optimal well-hiding
algorithm. We show that if the topology of the graph is known to the agents,
then the number of steps proportional to the diameter of the graph is
sufficient and necessary. In the unknown topology scenario we only consider a
single agent case. We first show that the task is impossible in the
deterministic case if the agent has no memory. Then we present a polynomial
randomized algorithm. Finally in the model with memory we show that the number
of steps proportional to the number of edges of the graph is sufficient and
necessary. In some sense we investigate how complex is the problem of "losing"
information about location (both physical and logical) for different settings.


title:
Millimeter Wave Beam Alignment: Large Deviations Analysis and Design
  Insights

abstract:
  In millimeter wave cellular communication, fast and reliable beam alignment
via beam training is crucial to harvest sufficient beamforming gain for the
subsequent data transmission. In this paper, we establish fundamental limits in
beam-alignment performance under both the exhaustive search and the
hierarchical search that adopts multi-resolution beamforming codebooks,
accounting for time-domain training overhead. Specifically, we derive lower and
upper bounds on the probability of misalignment for an arbitrary level in the
hierarchical search, based on a single-path channel model. Using the method of
large deviations, we characterize the decay rate functions of both bounds and
show that the bounds coincide as the training sequence length goes large. We go
on to characterize the asymptotic misalignment probability of both the
hierarchical and exhaustive search, and show that the latter asymptotically
outperforms the former, subject to the same training overhead and codebook
resolution. We show via numerical results that this relative performance
behavior holds in the non-asymptotic regime. Moreover, the exhaustive search is
shown to achieve significantly higher worst-case spectrum efficiency than the
hierarchical search, when the pre-beamforming signal-to-noise ratio (SNR) is
relatively low. This study hence implies that the exhaustive search is more
effective for users situated further from base stations, as they tend to have
low SNR.


title: The Optimal Placement Delivery Arrays

abstract:
  In wireless networks, coded caching is an effective technique to reduce
network congestion during peak traffic times. Recently, a new concept called
placement delivery array (PDA) was proposed to characterize the coded caching
scheme. So far, only one class of PDAs by Maddah-Ali and Niesen is known to be
optimal. In this paper, we mainly focus on constructing optimal PDAs. Firstly,
we derive some lower bounds. Next, we present several infinite classes of PDAs,
which are shown to be optimal with respect to the new bounds.


title:
Method of lines transpose: Energy gradient flows using direct operator
  inversion for phase field models

abstract:
  In this work, we develop an $\mathcal{O}(N)$ implicit real space method in 1D
and 2D for the Cahn Hilliard (CH) and vector Cahn Hilliard (VCH) equations,
based on the Method Of Lines Transpose (MOL$^\text{T}$) formulation. This
formulation results in a semi-discrete time stepping algorithm, which we prove
is gradient stable in the $H^{-1}$ norm.
  The spatial discretization follows from dimensional splitting, and an
$\mathcal{O}(N)$ matrix-free solver, which applies fast convolution to the
modified Helmholtz equation. We propose a novel factorization technique, in
which fourth order spatial derivatives are incorporated into the solver. The
splitting error is included in the nonlinear fixed point iteration, resulting
in a high order, logically Cartesian (line-by-line) update. Our method is fast,
but not restricted to periodic boundaries like the fast Fourier transform
(FFT).
  The basic solver is implemented using the Backward Euler formulation, and we
extend this to both backward difference (BDF) stencils, implicit Runge Kutta
(SDIRK) and spectral deferred correction (SDC) frameworks to achieve high
orders of temporal accuracy. We demonstrate with numerical results that the CH,
and VCH equations maintain gradient stability in one and two spatial
dimensions. We also explore time-adaptivity, so that meta-stable states and
ripening events can be simulated both quickly and efficiently.


title: Convolutional Regression for Visual Tracking

abstract:
  Recently, discriminatively learned correlation filters (DCF) has drawn much
attention in visual object tracking community. The success of DCF is
potentially attributed to the fact that a large amount of samples are utilized
to train the ridge regression model and predict the location of object. To
solve the regression problem in an efficient way, these samples are all
generated by circularly shifting from a search patch. However, these synthetic
samples also induce some negative effects which weaken the robustness of DCF
based trackers.
  In this paper, we propose a Convolutional Regression framework for visual
tracking (CRT). Instead of learning the linear regression model in a closed
form, we try to solve the regression problem by optimizing a one-channel-output
convolution layer with Gradient Descent (GD). In particular, the receptive
field size of the convolution layer is set to the size of object. Contrary to
DCF, it is possible to incorporate all "real" samples clipped from the whole
image. A critical issue of the GD approach is that most of the convolutional
samples are negative and the contribution of positive samples will be
suppressed. To address this problem, we propose a novel Automatic Hard Negative
Mining method to eliminate easy negatives and enhance positives. Extensive
experiments are conducted on a widely-used benchmark with 100 sequences. The
results show that the proposed algorithm achieves outstanding performance and
outperforms almost all the existing DCF based algorithms.


title: Ghosts of Deletions Past: New Secure Deletion Challenges and Solutions

abstract: Is secure deletion of data still a problem?


title: Signatures of exciton condensation in a transition metal dichalcogenide

abstract:
  Bose condensation has shaped our understanding of macroscopic quantum
phenomena, having been realized in superconductors, atomic gases, and liquid
helium. Excitons are bosons that have been predicted to condense into either a
superfluid or an insulating electronic crystal. Using the recently developed
momentum-resolved electron energy-loss spectroscopy (M-EELS), we study
electronic collective modes in the transition metal dichalcogenide semimetal,
1T-TiSe$_2$. Near the phase transition temperature, T$_c$ = 190 K, the energy
of the electronic mode falls to zero at nonzero momentum, indicating dynamical
slowing down of plasma fluctuations and crystallization of the valence
electrons into an exciton condensate. Our study provides compelling evidence
for exciton condensation in a three-dimensional solid and establishes M-EELS as
a versatile technique sensitive to valence band excitations in quantum
materials.


title: Preference Completion from Partial Rankings

abstract:
  We propose a novel and efficient algorithm for the collaborative preference
completion problem, which involves jointly estimating individualized rankings
for a set of entities over a shared set of items, based on a limited number of
observed affinity values. Our approach exploits the observation that while
preferences are often recorded as numerical scores, the predictive quantity of
interest is the underlying rankings. Thus, attempts to closely match the
recorded scores may lead to overfitting and impair generalization performance.
Instead, we propose an estimator that directly fits the underlying preference
order, combined with nuclear norm constraints to encourage low--rank
parameters. Besides (approximate) correctness of the ranking order, the
proposed estimator makes no generative assumption on the numerical scores of
the observations. One consequence is that the proposed estimator can fit any
consistent partial ranking over a subset of the items represented as a directed
acyclic graph (DAG), generalizing standard techniques that can only fit
preference scores. Despite this generality, for supervision representing total
or blockwise total orders, the computational complexity of our algorithm is
within a $\log$ factor of the standard algorithms for nuclear norm
regularization based estimates for matrix completion. We further show promising
empirical results for a novel and challenging application of collaboratively
ranking of the associations between brain--regions and cognitive neuroscience
terms.


title:
Resistance distance and Kirchhoff index in the corona-vertex and the
  corona $-$ edge of subdivision graph

abstract:
  The subdivision graph $S(G)$ of a graph $G$ is the graph obtained by
inserting a new vertex into every edge of $G$. In $\cite{PL}$, two classes of
new corona graphs, the corona-vertex of the subdivision graph
$G_{1}\diamondsuit G_{2}$ and corona-edge of the subdivision graph $G_{1}\star
G_{2}$ were defined. The adjacency spectrum and the signless Laplacian spectrum
of the two new graphs were computed when $G_{1}$ is an arbitrary graph and
$G_{2}$ is an $r$-regular graph. In this paper, we give the formulate of the
resistance distance and the Kirchhoff index in $G_{1}\diamondsuit G_{2}$ and
$G_{1}\star G_{2}$ when $G_{1}$ and $G_{2}$ are arbitrary graphs. These results
generalize them in $\cite{PL}$.


title:
Possible Nodeless Superconducting Gaps in
  Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$ and YBa$_2$Cu$_3$O$_{7-x}$ Revealed by
  Cross-Sectional Scanning Tunneling Spectroscopy

abstract:
  Pairing in the cuprate high-temperature superconductors and its origin remain
among the most enduring mysteries in condensed matter physics. With
cross-sectional scanning tunneling microscopy/ spectroscopy, we clearly reveal
the spatial-dependence or inhomogeneity of the superconducting gap structure of
Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$ (Bi2212) and YBa$_2$Cu$_3$O$_{7-x}$ (YBCO)
along their $c$-axes on a scale shorter than the interlayer spacing. By
tunneling into the (100) plane of a Bi2212 single crystal and a YBCO film, we
observe both U-shaped tunneling spectra with extended flat zero-conductance
bottoms, and V-shaped gap structures, in different regions of each sample. On
the YBCO film, tunneling into a (110) surface only reveals a U-shaped gap
without any zero-bias peak. Our analysis suggests that the U-shaped gap is
likely a nodeless superconducting gap. The V-shaped gap has a very small
amplitude, and is likely proximity-induced by regions having the larger
U-shaped gap.


title: Nonlinear Transport of Graphene in the Quantum Hall Regime

abstract:
  We have studied the breakdown of the integer quantum Hall (QH) effect with
fully broken symmetry, in an ultra-high mobility graphene device sandwiched
between two single crystal hexagonal boron nitride substrates. The evolution
and stabilities of the QH states are studied quantitatively through the
nonlinear transport with dc Hall voltage bias. The mechanism of the QH
breakdown in graphene and the movement of the Fermi energy with the electrical
Hall field are discussed. This is the first study in which the stabilities of
fully symmetry broken QH states are probed all together. Our results raise the
possibility that the v=6 states might be a better target for the quantum
resistance standard.


title: Adaptive Depth Imaging with Single-Photon Detectors

abstract:
  For active optical imaging, the use of single-photon detectors can greatly
improve the detection sensitivity of the system. However, the traditional
maximum-likelihood based imaging method needs a long acquisition time to
capture clear three-dimensional (3D) image in low light-level. To tackle this
problem, we present a novel imaging method for depth estimate, which can obtain
the accurate 3D image in a short acquisition time. Our method combines the
photon-count statistics with the temporal correlations of the reflected signal.
According to the characteristics of the target surface, including the surface
reflectivity, our method is capable of adaptively changing the dwell time in
each pixel. The experimental results demonstrate that the proposed method can
fast obtain the accurate depth image despite the existence of strong background
noise.


title: Emergent pattern formation in an interstitial biofilm

abstract:
  Collective behavior of bacterial colonies plays critical roles in
adaptability, survivability, biofilm expansion and infection. We employ an
individual-based model of an interstitial biofilm to study emergent pattern
formation based on the assumptions that rod-shaped bacteria furrow through a
viscous environment, and excrete extracellular polymeric substances which bias
their rate of motion. Because the bacteria furrow through their environment,
the substratum stiffness is a key control parameter behind the formation of
distinct morphological patterns. By systematically varying this property (which
we quantify with a stiffness coefficient {\gamma}), we show that subtle changes
in the substratum stiffness can give rise to a stable state characterized by a
high degree of local order and long-range pattern formation. The ordered state
exhibits characteristics typically associated with bacterial fitness
advantages, even though it is induced by changes in environmental conditions
rather than changes in biological parameters. Our findings are applicable to
broad range of biofilms and provide insights into the relationship between
bacterial movement and their environment, and basic mechanisms behind
self-organization of biophysical systems.


title:
BDMA for Millimeter-Wave/Terahertz Massive MIMO Transmission with
  Per-Beam Synchronization

abstract:
  We propose beam division multiple access (BDMA) with per-beam synchronization
(PBS) in time and frequency for wideband massive multiple-input multiple-output
(MIMO) transmission over millimeter-wave (mmW)/Terahertz (THz) bands. We first
introduce a physically motivated beam domain channel model for massive MIMO and
demonstrate that the envelopes of the beam domain channel elements tend to be
independent of time and frequency when both the numbers of antennas at base
station and user terminals (UTs) tend to infinity. Motivated by the derived
beam domain channel properties, we then propose PBS for mmW/THz massive MIMO.
We show that both the effective delay and Doppler frequency spreads of wideband
massive MIMO channels with PBS are reduced by a factor of the number of UT
antennas compared with the conventional synchronization approaches.
Subsequently, we apply PBS to BDMA, investigate beam scheduling to maximize the
achievable ergodic rates for both uplink and downlink BDMA, and develop a
greedy beam scheduling algorithm. Simulation results verify the effectiveness
of BDMA with PBS for mmW/THz wideband massive MIMO systems in typical mobility
scenarios.


title: New Characterisations of Tree-Based Networks and Proximity Measures

abstract:
  Phylogenetic networks are a type of directed acyclic graph that represent how
a set $X$ of present-day species are descended from a common ancestor by
processes of speciation and reticulate evolution. In the absence of reticulate
evolution, such networks are simply phylogenetic (evolutionary) trees.
Moreover, phylogenetic networks that are not trees can sometimes be represented
as phylogenetic trees with additional directed edges placed between their
edges. Such networks are called {\em tree based}, and the class of phylogenetic
networks that are tree based has recently been characterised. In this paper, we
establish a number of new characterisations of tree-based networks in terms of
path partitions and antichains (in the spirit of Dilworth's theorem), as well
as via matchings in a bipartite graph. We also show that a temporal network is
tree based if and only if it satisfies an antichain-to-leaf condition. In the
second part of the paper, we define three indices that measure the extent to
which an arbitrary phylogenetic network deviates from being tree based. We
describe how these three indices can be described exactly and computed
efficiently using classical results concerning maximum-sized matchings in
bipartite graphs.


title: An algebraic framework for end-to-end physical-layer network coding

abstract:
  We propose an algebraic setup for end-to-end physical-layer network coding
based on submodule transmission. We introduce a distance function between
modules, describe how it relates to information loss and errors, and show how
to compute it. Then we propose a definition of submodule error-correcting code,
and investigate bounds and constructions for such codes.


title:
Robust Consensus-Based Network Intrusion Detection in Presence of
  Byzantine Attacks

abstract:
  Consensus algorithms provide strategies to solve problems in a distributed
system with the added constraint that data can only be shared between adjacent
computing nodes. We find these algorithms in applications for wireless and
sensor networks, spectrum sensing for cognitive radio, even for some IoT
services. However, consensus-based applications are not resilient to
compromised nodes sending falsified data to their neighbors, i.e. they can be
the target of Byzantine attacks. Several solutions have been proposed in the
literature inspired from reputation based systems, outlier detection or
model-based fault detection techniques in process control. We have reviewed
some of these solutions, and propose two mitigation techniques to protect the
consensus-based Network Intrusion Detection System in
\cite{toulouse2015consensus}. We analyze several implementation issues such as
computational overhead, fine tuning of the solution parameters, impacts on the
convergence of the consensus phase, accuracy of the intrusion detection system.


title: Learning Sparse, Distributed Representations using the Hebbian Principle

abstract:
  The "fire together, wire together" Hebbian model is a central principle for
learning in neuroscience, but surprisingly, it has found limited applicability
in modern machine learning. In this paper, we take a first step towards
bridging this gap, by developing flavors of competitive Hebbian learning which
produce sparse, distributed neural codes using online adaptation with minimal
tuning. We propose an unsupervised algorithm, termed Adaptive Hebbian Learning
(AHL). We illustrate the distributed nature of the learned representations via
output entropy computations for synthetic data, and demonstrate superior
performance, compared to standard alternatives such as autoencoders, in
training a deep convolutional net on standard image datasets.


title:
New approach to canonical partition functions computation in $N_f=2$
  lattice QCD at finite baryon density

abstract:
  We propose and test a new approach to computation of canonical partition
functions in lattice QCD at finite density. We suggest a few steps procedure.
We first compute numerically the quark number density for imaginary chemical
potential $i\mu_{qI}$. Then we restore the grand canonical partition function
for imaginary chemical potential using fitting procedure for the quark number
density. Finally we compute the canonical partition functions using high
precision numerical Fourier transformation. Additionally we compute the
canonical partition functions using known method of the hopping parameter
expansion and compare results obtained by two methods in the deconfining as
well as in the confining phases. The agreement between two methods indicates
the validity of the new method. Our numerical results are obtained in two
flavor lattice QCD with clover improved Wilson fermions.


title:
SummaRuNNer: A Recurrent Neural Network based Sequence Model for
  Extractive Summarization of Documents

abstract:
  We present SummaRuNNer, a Recurrent Neural Network (RNN) based sequence model
for extractive summarization of documents and show that it achieves performance
better than or comparable to state-of-the-art. Our model has the additional
advantage of being very interpretable, since it allows visualization of its
predictions broken up by abstract features such as information content,
salience and novelty. Another novel contribution of our work is abstractive
training of our extractive model that can train on human generated reference
summaries alone, eliminating the need for sentence-level extractive labels.


title: Identity Matters in Deep Learning

abstract:
  An emerging design principle in deep learning is that each layer of a deep
artificial neural network should be able to easily express the identity
transformation. This idea not only motivated various normalization techniques,
such as \emph{batch normalization}, but was also key to the immense success of
\emph{residual networks}.
  In this work, we put the principle of \emph{identity parameterization} on a
more solid theoretical footing alongside further empirical progress. We first
give a strikingly simple proof that arbitrarily deep linear residual networks
have no spurious local optima. The same result for linear feed-forward networks
in their standard parameterization is substantially more delicate. Second, we
show that residual networks with ReLu activations have universal finite-sample
expressivity in the sense that the network can represent any function of its
sample provided that the model has more parameters than the sample size.
  Directly inspired by our theory, we experiment with a radically simple
residual architecture consisting of only residual convolutional layers and ReLu
activations, but no batch normalization, dropout, or max pool. Our model
improves significantly on previous all-convolutional networks on the CIFAR10,
CIFAR100, and ImageNet classification benchmarks.


title:
Chimera states in nonlocally coupled phase oscillators with biharmonic
  interaction

abstract:
  Chimera states, which consist of coexisting domains of coherent and
incoherent parts, have been observed in a variety of systems. Most of previous
works on chimera states have taken into account specific form of interaction
between oscillators, for example sinusoidal coupling or diffusive coupling.
Here, we investigate chimera dynamics in nonlocally coupled phase oscillators
with biharmonic interaction. We find novel chimera states with features such as
that oscillators in the same coherent cluster may split into two groups with a
phase difference between them at around pi/2 and that oscillators in adjacent
coherent clusters may have a phase difference close to pi/2. The different
impacts of the coupling ranges in the first and the second harmonic
interactions on chimera dynamics are investigated based on the synchronous
dynamics in globally coupled phase oscillators. Our study suggests a new
direction in the field of chimera dynamics.


title: A New Recurrent Neural CRF for Learning Non-linear Edge Features

abstract:
  Conditional Random Field (CRF) and recurrent neural models have achieved
success in structured prediction. More recently, there is a marriage of CRF and
recurrent neural models, so that we can gain from both non-linear dense
features and globally normalized CRF objective. These recurrent neural CRF
models mainly focus on encode node features in CRF undirected graphs. However,
edge features prove important to CRF in structured prediction. In this work, we
introduce a new recurrent neural CRF model, which learns non-linear edge
features, and thus makes non-linear features encoded completely. We compare our
model with different neural models in well-known structured prediction tasks.
Experiments show that our model outperforms state-of-the-art methods in NP
chunking, shallow parsing, Chinese word segmentation and POS tagging.


title:
F-Score Driven Max Margin Neural Network for Named Entity Recognition in
  Chinese Social Media

abstract:
  We focus on named entity recognition (NER) for Chinese social media. With
massive unlabeled text and quite limited labelled corpus, we propose a
semi-supervised learning model based on B-LSTM neural network. To take
advantage of traditional methods in NER such as CRF, we combine transition
probability with deep learning in our model. To bridge the gap between label
accuracy and F-score of NER, we construct a model which can be directly trained
on F-score. When considering the instability of F-score driven method and
meaningful information provided by label accuracy, we propose an integrated
method to train on both F-score and label accuracy. Our integrated model yields
7.44\% improvement over previous state-of-the-art result.


title:
Sub-channel and Power Allocation for Non-orthogonal Multiple Access
  Relay Networks with Amplify-and-Forward Protocol

abstract:
  In this paper, we study the resource allocation problem for a single-cell
non-orthogonal multiple access (NOMA) relay network where an OFDM
amplify-and-forward (AF) relay allocates the spectrum and power resources to
the source-destination (SD) pairs. We aim to optimize the resource allocation
to maximize the average sum-rate. The optimal approach requires an exhaustive
search, leading to an NP-hard problem. To solve this problem, we propose two
efficient many-to-many two-sided SD pair-subchannel matching algorithms in
which the SD pairs and sub-channels are considered as two sets of players
chasing their own interests. The proposed algorithms can provide a sub-optimal
solution to this resource allocation problem in affordable time. Both the
static matching algorithm and dynamic matching algorithm converge to a
pair-wise stable matching after a limited number of iterations. Simulation
results show that the capacity of both proposed algorithms in the NOMA scheme
significantly outperforms the conventional orthogonal multiple access scheme.
The proposed matching algorithms in NOMA scheme also achieve a better
user-fairness performance than the conventional orthogonal multiple access.


title:
On the initial- and boundary-value problem for 2D micropolar equations
  with only angular velocity dissipation

abstract:
  This paper focuses on the initial- and boundary-value problem for the
two-dimensional micropolar equations with only angular velocity dissipation in
a smooth bounded domain. The aim here is to establish the global existence and
uniqueness of solutions by imposing natural boundary conditions and minimal
regularity assumptions on the initial data. Besides, the global solution is
shown to possess higher regularity when the initial datum is more regular. To
obtain these results, we overcome two main difficulties, one due to the lack of
full dissipation and one due to the boundary conditions. In addition to the
global regularity problem, we also examine the large-time behavior of solutions
and obtain explicit decay rates.


title: Probing the Deep End of the Milky Way with New Oscillating Kepler Giants

abstract:
  The Kepler mission has been a success in both exoplanet search and stellar
physics studies. Red giants have actually been quite a highlight in the Kepler
scene. The Kepler long and almost continuous four-year observations allowed us
to detect oscillations in more than 15,000 red giants targeted by the mission.
However by looking at the power spectra of 45,000 stars classified as dwarfs
according to the Q1-16 Kepler star properties catalog, we detected red-giant
like oscillations in 850 stars. Even though this is a small addition to the
known red-giant sample, these misclassified stars represent a goldmine for
galactic archeology studies. Indeed they happen to be fainter (down to Kp~16)
and more distant (d>10kpc) than the known red giants, opening the possibility
to probe unknown regions of our Galaxy. The faintness of these red giants with
detected oscillations is very promising for detecting acoustic modes in red
giants observed with K2 and TESS. In this talk, I will present this new sample
of red giants with their revised stellar parameters derived from
asteroseismology. Then I will discuss about the distribution of their masses,
distances, and evolutionary states compared to the previously known sample of
red giants.


title: On the Bott-Chern characteristic classes for coherent sheaves

abstract:
  Using the concept of a cohesive module defined by Block, we use the theory of
superconnections in the sense of Quillen to construct natural superconnections
on Hermitian cohesive modules. By the Chern-Weil construction, we obtain
characteristic classes with values in Bott-Chern cohomology which refines the
usual deRham cohomology. The main result of this paper shows that such
characteristic classes are independent of the Hermitian metric and only
dependent on the homotopy class of the cohesive module in the homotopy
category. This extends the Bott-Chern cohomology to the bounded derived
category of complexes of analytic sheaves with coherent cohomology. We also
constructed secondary Bott-Chern characteristic forms and the main technical
theorem proves that they are well defined.


title:
Structure, Propagation and Expansion of a CME-Driven Shock in the
  Heliosphere: A Revisit of the 2012 July 23 Extreme Storm

abstract:
  We examine the structure, propagation and expansion of the shock associated
with the 2012 July 23 extreme coronal mass ejection (CME). Characteristics of
the shock determined from multi-point imaging observations are compared to in
situ measurements at different locations and a complex radio type II burst,
which according to our definition has multiple branches that may not all be
fundamental-harmonic related. The white-light shock signature can be modeled
reasonably well by a spherical structure and was expanding backward even on the
opposite side of the Sun. The expansion of the shock, which was roughly
self-similar after the first $\sim$1.5 hours from launch, largely dominated
over the translation of the shock center for the time period of interest. Our
study also suggests a bow-shock morphology around the nose at later times due
to the outward motion in combination with the expansion of the ejecta. The
shock decayed and failed to reach Mercury in the backward direction and STEREO
B and Venus in the lateral directions, as indicated by the imaging and in situ
observations. The shock in the nose direction, however, may persist to the far
outer heliosphere, with predicted impact on Dawn around 06 UT on July 25 and on
Jupiter around 23:30 UT on July 27 by an MHD model. The type II burst shows
properties generally consistent with the spatial/temporal variations of the
shock deduced from imaging and in situ observations. In particular, the
low-frequency bands agree well with the in situ measurements of a very low
density ahead of the shock at STEREO A.


title:
Revisiting 154-day periodicity in the occurrence of hard flares. A
  planetary influence?

abstract:
  Rieger et al (1984) reported observations of a 154 day periodicity in flares
during solar cycle 21. This paper discusses the observations in the light of a
simple empirical planetary model of sunspot emergence. The planetary model
predicts sunspot emergence when Mercury and Earth approach conjunction and
Mercury approaches the Sun. We show that the reported times of flare activity
are coherent with the planetary model. While the base period of the model is
170 days, the average model period, over the interval of flare recordings, is
157 days due to a 180 degree phase change in the planetary forcing near the
middle of the record interval. We conclude that the periodicity at 154 days
arises when the phase change in planetary forcing and the resulting progressive
phase change in total sunspot area emergence and flare occurrence shifts the
major peak in the flare spectrum from the planetary forcing period, 170 days,
to 154 days.


title: Stellar, gas and dark matter content of barred galaxies

abstract:
  We select a sample of galaxies from the Sloan Digital Sky Survey Data Release
7 (SDSS-DR7) where galaxies are classified, through visual inspection, as
hosting strong bars, weak bars or as unbarred galaxies, and make use of HI mass
and kinematic information from the Arecibo Legacy Fast ALFA (ALFALFA) survey
catalog, to study the stellar, atomic gas and dark matter content of barred
disk galaxies. We find, in agreement with previous studies, that the bar
fraction increases with increasing stellar mass. A similar trend is found with
total baryonic mass, although the dependence is not as strong as with stellar
mass, this due to the contribution of gas. The bar fraction shows a decrease
with increasing gas mass fraction. This anticorrelation between the likelihood
of a galaxy hosting a bar with the gas richness of the galaxy results from the
inhibiting effect the gas has in the formation of bars. We also find that for
massive galaxies with stellar masses larger than 10$^{10} M_{\odot}$, at fixed
stellar mass, the bar fraction decreases with increasing global halo mass (i.e.
halo mass measured up to a radius of the order of the HI disk extent).


title:
Master equation approach to transient quantum transport in
  nanostructures

abstract:
  In this review article, we present a non-equilibrium quantum transport theory
for transient electron dynamics in nanodevices based on exact master equation
derived with the path integral method in the fermion coherent-state
representation. Applying the exact master equation to nanodevices, we also
establish the connection of the reduced density matrix and the transient
quantum transport current with the Keldysh nonequilibrium Green functions. The
theory enables us to study transient quantum transport in nanostructures with
back-reaction effects from the contacts, with non-Markovian dissipation and
decoherence being fully taken into account. In applications, we utilize the
theory to specific quantum transport systems, a variety of quantum decoherence
and quantum transport phenomena involving the non-Markovian memory effect are
investigated in both transient and stationary scenarios at arbitrary initial
temperatures of the contacts.


title: Contracting the Weierstrass locus to a point

abstract:
  We construct an open substack $U\subset\mathcal{M}_{g,1}$ with the complement
of codimension $\ge 2$ and a morphism from $U$ to a weighted projective stack,
which sends the Weierstrass locus $\mathcal{W}\cap U$ to a point, and maps
$\mathcal{M}_{g,1}\setminus\mathcal{W}$ isomorphically to its image. The proof
uses alternative birational models of $\mathcal{M}_{g,1}$ and
$\mathcal{M}_{g,2}$ from arXiv:1509.07241.


title:
Classify or Select: Neural Architectures for Extractive Document
  Summarization

abstract:
  We present two novel and contrasting Recurrent Neural Network (RNN) based
architectures for extractive summarization of documents. The Classifier based
architecture sequentially accepts or rejects each sentence in the original
document order for its membership in the final summary. The Selector
architecture, on the other hand, is free to pick one sentence at a time in any
arbitrary order to piece together the summary. Our models under both
architectures jointly capture the notions of salience and redundancy of
sentences. In addition, these models have the advantage of being very
interpretable, since they allow visualization of their predictions broken up by
abstract features such as information content, salience and redundancy. We show
that our models reach or outperform state-of-the-art supervised models on two
different corpora. We also recommend the conditions under which one
architecture is superior to the other based on experimental evidence.


title:
Properties of chromatic polynomials of hypergraphs not held for
  chromatic polynomials of graphs

abstract:
  In this paper, we present some properties on chromatic polynomials of
hypergraphs which do not hold for chromatic polynomials of graphs. We first
show that chromatic polynomials of hypergraphs have all integers as their zeros
and contain dense real zeros in the set of real numbers. We then prove that for
any multigraph $G=(V,E)$, the number of totally cyclic orientations of $G$ is
equal to the value of $|P(H,-1)|$, where $P(H,\lambda)$ is the chromatic
polynomial of a hypergraph $H$ which is constructed from $G$. Finally we show
that the multiplicity of root "$0$" of $P(H,\lambda)$ may be at least $2$ for
some connected hypergraphs $H$, and the multiplicity of root "$1$" of
$P(H,\lambda)$ may be $1$ for some connected and separable hypergraphs $H$ and
may be $2$ for some connected and non-separable hypergraphs $H$.


title: Growing Interpretable Part Graphs on ConvNets via Multi-Shot Learning

abstract:
  This paper proposes a learning strategy that extracts object-part concepts
from a pre-trained convolutional neural network (CNN), in an attempt to 1)
explore explicit semantics hidden in CNN units and 2) gradually grow a
semantically interpretable graphical model on the pre-trained CNN for
hierarchical object understanding. Given part annotations on very few (e.g.,
3-12) objects, our method mines certain latent patterns from the pre-trained
CNN and associates them with different semantic parts. We use a four-layer
And-Or graph to organize the mined latent patterns, so as to clarify their
internal semantic hierarchy. Our method is guided by a small number of part
annotations, and it achieves superior performance (about 13%-107% improvement)
in part center prediction on the PASCAL VOC and ImageNet datasets.


title:
Ultrafast Energy- and Momentum-resolved Surface Dirac Photocurrents in
  the Topological Insulator Sb$_2$Te$_3$

abstract:
  We present energy-momentum mapping of surface Dirac photocurrent in the
topological insulator Sb$_2$Te$_3$ by means of time- and angle-resolved
two-photon photoemission spectroscopy combined with polarization-variable
mid-infrared pulse laser. It is demonstrated that the direct optical transition
from the occupied to the unoccupied part of the surface Dirac-cone permits the
linear and circular photogalvanic effect which thereby enables us to coherently
control the surface electric-current by laser polarization. Moreover, the
surface current mapping directly visualizes ultrafast current dynamics in the
Dirac cone in the time domain. We unravel the ultrafast intraband relaxation
dynamics of the inelastic scattering and momentum scattering separately. Our
observations pave the pathway for coherent optical control over surface Dirac
electrons in topological insulators.


title: Asymptotic Inference for AR(1) Penal Data

abstract:
  A general asymptotic theory is given for the panel data AR(1) model with time
series independent in different cross sections. The theory covers the cases of
stationary process, nearly non-stationary process, unit root process, mildly
integrated, mildly explosive and explosive processes. It is assumed that the
cross-sectional dimension and time-series dimension are respectively $N$ and
$T$. The results in this paper illustrate that whichever the process is, with
an appropriate regularization, the least squares estimator of the
autoregressive coefficient converges to a normal distribution with rate at
least $O(N^{-1/3})$. Since the variance is the key to characterize the normal
distribution, it is important to discuss the variance of the least squares
estimator. We will show that when the autoregressive coefficient $\rho$
satisfies $|\rho|<1$, the variance declines at the rate $O((NT)^{-1/2})$, while
the rate changes to $O(N^{-1/2}T^{-1})$ when $\rho=1$ and
$O(N^{-1/2}\rho^{-T+2})$ when $|\rho|>1$. $\rho=1$ is the critical point where
the convergence rate changes radically. The transition process is studied by
assuming $\rho$ depending on $T$ and going to $1$. An interesting phenomenon
discovered in this paper is that, in the explosive case, the least squares
estimator of the autoregressive coefficient has a standard normal limiting
distribution in panel data case while it may not has a limiting distribution in
univariate time series case.


title: On Orthogonal Decomposition of a Sobolev Space

abstract:
  The theme of this short article is to investigate an orthogonal decomposition
of a Sobolev space and look at some properties of the inner product therein and
the distance defined from the inner product. We also determine the dimension of
the orthogonal difference space and show the expansion of spaces as their
regularity increases.


title: On electromagnetic scattering from a penetrable corner

abstract:
  This article is concerned with the time-harmonic electromagnetic (EM)
scattering from a generic inhomogeneous medium. It is shown that if there is a
right corner on the support of the medium, then it scatters every pair of
incident EM fields, excluding a possible class of EM fields which are of very
particular forms. That is, for every pair of admissible incident EM fields, the
corresponding scattered wave fields associated to the medium scatterer cannot
be identically vanishing outside the support of the medium. Indeed, we achieve
the corner scattering result by establishing a stronger result, that shows the
failure of the analytic extension across the corner of certain EM fields
satisfying the so-called interior transmission eigenvalue problem. This extends
the relevant study in [3] for the acoustic scattering governed by the Helmholtz
equation to the electromagnetic case governed by the Maxwell system.
Substantial new challenges arise from the corresponding extension from the
scalar PDE to the system of PDEs. Our mathematical arguments combine the
analysis for interior transmission eigenvalue problems associated to the
Maxwell system; the derivation of novel orthogonality relation for the
solutions of Maxwell systems; the construction of complex-geometrical-optics
(CGO) solutions for the Maxwell system with new Lp-estimates (p > 6) on the
remainder terms; and the proof of the non-vanishing property for the Laplace
transform of vectorial homogeneous harmonic polynomials.


title: Baseline CNN structure analysis for facial expression recognition

abstract:
  We present a baseline convolutional neural network (CNN) structure and image
preprocessing methodology to improve facial expression recognition algorithm
using CNN. To analyze the most efficient network structure, we investigated
four network structures that are known to show good performance in facial
expression recognition. Moreover, we also investigated the effect of input
image preprocessing methods. Five types of data input (raw, histogram
equalization, isotropic smoothing, diffusion-based normalization, difference of
Gaussian) were tested, and the accuracy was compared. We trained 20 different
CNN models (4 networks x 5 data input types) and verified the performance of
each network with test images from five different databases. The experiment
result showed that a three-layer structure consisting of a simple convolutional
and a max pooling layer with histogram equalization image input was the most
efficient. We describe the detailed training procedure and analyze the result
of the test accuracy based on considerable observation.


title: Emerging trends in Topological Insulator and Topological Superconductor

abstract:
  Topological insulators are new class of materials which are characterized by
a bulk band gap like ordinary band insulator but have protected conducting
states on their edge or surface. These states emerge out due to the combination
of spin-orbit coupling and time reversal symmetry. Also these states are
insensitive to scattering by non-magnetic impurities. A two-dimensional (2D)
topological insulator has one dimensional (1D) edge states in which the
spin-momentum locking of the electrons gives rise to quantum spin Hall effect.
A three-dimensional (3D) topological insulator supports novel spin-polarized 2D
Dirac fermions on its surface. These topological insulator materials have been
theoretically predicted and experimentally observed in a variety of 2D and 3D
systems, including $\rm HgTe$ quantum wells, $\rm BiSb$ alloys, and $\rm
Bi_{2}Te_{3}$, $\rm Bi_{2}Se_{3}$ crystals. Moreover, proximity induced
superconductivity in these systems can lead to a state that supports zero
energy Majorana fermion and the phase is known as topological superconductors.
In this article, the basic idea of topological insulators and topological
superconductors are presented along with their experimental development.


title: Open Charm decays and spectroscopy at Belle

abstract:
  In this review we report the recent results of open charm decays and
spectroscopy using the data collected with the Belle detector at the KEKB
asymmetric-energy e+e- collider.


title: Towards Information Privacy for the Internet of Things

abstract:
  In an Internet of Things network, multiple sensors send information to a
fusion center for it to infer a public hypothesis of interest. However, the
same sensor information may be used by the fusion center to make inferences of
a private nature that the sensors wish to protect. To model this, we adopt a
decentralized hypothesis testing framework with binary public and private
hypotheses. Each sensor makes a private observation and utilizes a local sensor
decision rule or privacy mapping to summarize that observation independently of
the other sensors. The local decision made by a sensor is then sent to the
fusion center. Without assuming knowledge of the joint distribution of the
sensor observations and hypotheses, we adopt a nonparametric learning approach
to design local privacy mappings. We introduce the concept of an empirical
normalized risk, which provides a theoretical guarantee for the network to
achieve information privacy for the private hypothesis with high probability
when the number of training samples is large. We develop iterative optimization
algorithms to determine an appropriate privacy threshold and the best sensor
privacy mappings, and show that they converge. Finally, we extend our approach
to the case of a private multiple hypothesis. Numerical results on both
synthetic and real data sets suggest that our proposed approach yields low
error rates for inferring the public hypothesis, but high error rates for
detecting the private hypothesis.


title: Efficient Communications in Training Large Scale Neural Networks

abstract:
  We consider the problem of how to reduce the cost of communication that is
required for the parallel training of a neural network. The state-of-the-art
method, Bulk Synchronous Parallel Stochastic Gradient Descent (BSP-SGD),
requires many collective communication operations, like broadcasts of
parameters or reductions for sub-gradient aggregations, which for large
messages quickly dominates overall execution time and limits parallel
scalability. To address this problem, we develop a new technique for collective
operations, referred to as Linear Pipelining (LP). It is tuned to the message
sizes that arise in BSP-SGD, and works effectively on multi-GPU systems.
Theoretically, the cost of LP is invariant to $P$, where $P$ is the number of
GPUs, while the cost of more conventional Minimum Spanning Tree (MST) scales
like $O(\log P)$. LP also demonstrate up to 2x faster bandwidth than
Bidirectional Exchange (BE) techniques that are widely adopted by current MPI
implementations. We apply these collectives to BSP-SGD, showing that the
proposed implementations reduce communication bottlenecks in practice while
preserving the attractive convergence properties of BSP-SGD.


title: A linear-time benchmarking tool for generalized surface codes

abstract:
  Quantum information processors need to be protected against errors and
faults. One of the most widely considered fault-tolerant architecture is based
on surface codes. While the general principles of these codes are well
understood and basic code properties such as minimum distance and rate are easy
to characterize, a code's average performance depends on the detailed geometric
layout of the qubits. To date, optimizing a surface code architecture and
comparing different geometric layouts relies on costly numerical simulations.
Here, we propose a benchmarking algorithm for simulating the performance of
surface codes, and generalizations thereof, that runs in linear time. We
implemented this algorithm in a software that generates performance reports and
allows to quickly compare different architectures.


title: Nuclear Energy Density Functional for KIDS

abstract:
  The density functional theory (DFT) is based on the existence and uniqueness
of a universal functional $E[\rho]$, which determines the dependence of the
total energy on single-particle density distributions. However, DFT says
nothing about the form of the functional. Our strategy is to first look at what
we know, from independent considerations, about the analytical density
dependence of the energy of nuclear matter and then, for practical
applications, to obtain an appropriate density-dependent effective interaction
by reverse engineering. In a previous work on homogeneous matter, we identified
the most essential terms to include in our "KIDS" functional, named after the
early-stage participating institutes. We now present first results for finite
nuclei, namely the energies and radii of $^{16,28}$O, $^{40,60}$Ca.


title: Hadronic Vacuum Polarization in True Muonium

abstract:
  The leading-order hadronic vacuum polarization contribution to the hyperfine
splitting of true muonium is reevaluated in two ways. The first considers a
more complex pionic form factor and better estimates of the perturbative QCD
contributions. The second, more accurate method directly integrates the Drell
ratio $R(s)$ to obtain $C_{1,\rm hvp}=-0.0489(3)$. This corresponds to an
energy shift in the hyperfine splitting of $\Delta E^\mu_{hfs,\rm
hvp}=276196(51)$ MHz.


title: Horizon Fluffs: In the Context of Generalized Minimal Massive Gravity

abstract:
  We consider a metric which describes Ba$\tilde{\text{n}}$ados geometries and
show that the considered metric is a solution of generalized minimal massive
gravity (GMMG) model. We consider the Killing vector field which preserves the
form of considered metric. Using the off-shell quasi-local approach we obtain
the asymptotic conserved charges of given solution. Similar to the Einstein
gravity in the presence of negative cosmological constant, for the GMMG model
also, we show that the algebra among the asymptotic conserved charges is
isomorphic to two copies of the Virasoro algebra. Eventually, we find relation
between the algebra of the near horizon and the asymptotic conserved charges.
This relation show that the main part of the horizon fluffs proposal of
Refs.\cite{140,14} appear for generic black holes in the class of
Ba$\tilde{\text{n}}$ados geometries in the context of GMMG model.


title:
Measurements of the branching fractions for $D^+\to K^0_SK^0_SK^+$,
  $K^0_SK^0_S\pi^+$ and $D^0\to K^0_SK^0_S$, $K^0_SK^0_SK^0_S$

abstract:
  By analyzing $2.93\ \rm fb^{-1}$ of data taken at the $\psi(3770)$ resonance
peak with the BESIII detector, we measure the branching fractions for the
hadronic decays $D^+\to K^0_SK^0_S K^+$, $D^+\to K^0_SK^0_S \pi^+$, $D^0\to
K^0_S K^0_S$ and $D^0\to K^0_SK^0_SK^0_S$. They are determined to be ${\mathcal
B}(D^+\to K^0_SK^0_SK^+)=(2.54 \pm 0.05_{\rm stat.} \pm 0.12_{\rm sys.})\times
10^{-3}$, ${\mathcal B}(D^+\to K^0_SK^0_S\pi^+)=(2.70 \pm 0.05_{\rm stat.} \pm
0.12_{\rm sys.})\times 10^{-3}$, ${\mathcal B}(D^0\to K^0_SK^0_S)=(1.67 \pm
0.11_{\rm stat.} \pm 0.11_{\rm sys.})\times 10^{-4}$ and ${\mathcal B}(D^0\to
K^0_SK^0_SK^0_S)=(7.21 \pm 0.33_{\rm stat.} \pm 0.44_{\rm sys.})\times
10^{-4}$, where the second one is measured for the first time and the others
are measured with significantly improved precision over the previous
measurements.


title: Current status of $\varepsilon_K$ in lattice QCD

abstract:
  We present the current status of $\varepsilon_K$ evaluated directly from the
standard model using lattice QCD inputs. The lattice QCD inputs include
$\hat{B}_K$, $\xi_0$, $\xi_2$, $|V_{us}|$, $m_c(m_c)$, and $|V_{cb}|$.
Recently, FLAG has updated $\hat{B}_K$, exclusive $|V_{cb}|$ has been updated
with new lattice data in the $\bar{B}\to D\ell\bar{\nu}$ decay mode, and
RBC-UKQCD has updated $\xi_0$ and $\xi_2$. We find that the standard model
evaluation of $\varepsilon_K$ with exclusive $|V_{cb}|$ (lattice QCD inputs) is
$3.2\sigma$ lower than the experimental value, while that with inclusive
$|V_{cb}|$ (heavy quark expansion) shows no tension.


title:
Fate of Majorana modes in $\mathrm{CeCoIn}_5$/$\mathrm{YbCoIn}_5$
  superlattices -a test bed for reduction of topological classification-

abstract:
  In this paper, we propose $\mathrm{CeCoIn_5}/\mathrm{YbCoIn_5}$ superlattice
systems as a test bed for the reduction of topological classification in free
fermions. We find that the system with quad-layer of $\mathrm{CeCoIn_5}$ shows
a topological crystalline superconducting phase with the mirror Chern number
eight at the non-interacting level. Furthermore, we demonstrate that in the
presence of two-body interactions, gapless edge modes are no longer protected
by the symmetry in the system with quad-layer, but are protected in the systems
with bi- or tri-layer. This clearly exemplifies the reduction of topological
classification from $\mathbb{Z}\oplus\mathbb{Z}$ to
$\mathbb{Z}\oplus\mathbb{Z}_8$.


title:
Transition between strong and weak topological insulator in ZrTe$_5$ and
  HfTe$_5$

abstract:
  ZrTe$_5$ and HfTe$_5$ have attracted increasingly attention recently since
the theoretical prediction of being topological insulators (TIs). However,
subsequent works show many contradictions about their topological nature.Three
possible phases, i.e. strong TI, weak TI, and Dirac semi-metal, have been
observed in different experiments until now. Essentially whether ZrTe$_5$ or
HfTe$_5$ has a band gap or not is still a question. Here, we present detailed
first-principles calculations on the electronic and topological properties of
ZrTe$_5$ and HfTe$_5$ on variant volumes and clearly demonstrate the
topological phase transition from a strong TI, going through an intermediate
Dirac semi-metal phase, then to a weak TI when the crystal expands.Our work
might give a unified explain about the divergent experimental results and
propose the crucial clue to further experiments to elucidate the topological
nature of these materials.


title: Bond Graph Modelling of Chemiosmotic Biomolecular Energy Transduction

abstract:
  Engineering systems modelling and analysis based on the bond graph approach
has been applied to biomolecular systems. In this context, the notion of a
Faraday-equivalent chemical potential is introduced which allows chemical
potential to be expressed in an analogous manner to electrical volts thus
allowing engineering intuition to be applied to biomolecular systems. Redox
reactions, and their representation by half-reactions, are key components of
biological systems which involve both electrical and chemical domains. A bond
graph interpretation of redox reactions is given which combines bond graphs
with the Faraday- equivalent chemical potential. This approach is particularly
relevant when the biomolecular system implements chemoelectrical transduction -
for example chemiosmosis within the key metabolic pathway of mitochondria:
oxidative phosphorylation. An alternative way of implementing computational
modularity using bond graphs is introduced and used to give a physically based
model of the mitochondrial electron transport chain. To illustrate the overall
approach, this model is analysed using the Faraday-equivalent chemical
potential approach and engineering intuition is used to guide affinity
equalisation: a energy based analysis of the mitochondrial electron transport
chain.


title: Oriented area is a perfect Morse function

abstract:
  We show that an appropriate generalization of the oriented area function is a
perfect Morse function on the space of three-dimensional configurations of an
equilateral polygonal linkage with odd number of edges. Therefore cyclic
equilateral polygons (which appear as Morse points) are interpreted as
independent generators of the homology groups of the (decorated) configuration
space.


title:
Unusual nodal behaviors of the superconducting gap in the iron-based
  superconductor Ba(Fe$_{0.65}$Ru$_{0.35}$)$_2$As$_2$: Effects of spin-orbit
  coupling

abstract:
  We have investigated the superconducting gap of optimally doped
Ba(Fe$_{0.65}$Ru$_{0.35}$)$_2$As$_2$ by angle-resolved photoemission
spectroscopy (APRES) using bulk-sensitive 7 eV laser and synchrotron radiation.
It was found that the gap is isotropic in the $k_x$-$k_y$ plane both on the
electron and hole Fermi surfaces (FSs). The gap magnitudes of two resolved hole
FSs show similar $k_z$ dependences and decrease as $k_z$ approaches $\sim$
2$\pi$/$c$ (i.e., around the Z point) unlike the other Fe-based superconductors
reported so far, where the superconducting gap of only one hole FS shows a
strong $k_z$ dependence. This unique gap structure can be understood in the
scenario that the $d_{z^2}$ orbital character is mixed into both hole FSs due
to the finite spin-orbit coupling between almost degenerate FSs and is
reproduced by calculations within the random phase approximation including the
spin-orbit coupling.


title:
Countermeasure against blinding attacks on low-noise detectors with
  background noise cancellation scheme

abstract:
  We developed a countermeasure against blinding attacks on low-noise detectors
with a background noise cancellation scheme in quantum key distribution (QKD)
systems. Background noise cancellation includes self-differencing and balanced
avalanche photon diode (APD) schemes and is considered a promising solution for
low-noise APDs, which are critical components in high-performance QKD systems.
However, its vulnerability to blinding attacks has been recently reported. In
this work, we propose a new countermeasure that prevents this potential
security loophole from being used in detector blinding attacks. An experimental
QKD setup is implemented and various tests are conducted to verify the
feasibility and performance of the proposed method. The obtained measurement
results show that the proposed scheme successfully detects occurring
blinding-attack-based hacking attempts.


title:
AntMonitor: A System for On-Device Mobile Network Monitoring and its
  Applications

abstract:
  In this paper, we present a complete system for on-device passive monitoring,
collection, and analysis of fine grained, large-scale packet measurements from
mobile devices. First, we describe the design and implementation of AntMonitor
as a userspace mobile app based on a VPN-service but only on the device
(without the need to route through a remote VPN server) and using only the
minimum resources required. We evaluate our prototype and show that it
significantly outperforms prior state-of-the-art approaches: it achieves
throughput of over 90 Mbps downlink and 65 Mbps uplink, which is 2x and 8x
faster than mobile-only baselines and is 94% of the throughput without VPN,
while using 2-12x less energy. Second, we show that AntMonitor is uniquely
positioned to serve as a platform for passive on-device mobile network
monitoring and to enable a number of applications, including: (i) real-time
detection and prevention of private information leakage from the device to the
network; (ii) passive network performance monitoring; and (iii) application
classification and user profiling. We showcase preliminary results from a pilot
user study at a university campus.


title:
Exactly solvable model for a velocity jump observed in crack propagation
  in viscoelastic solids

abstract:
  Needs to impart appropriate elasticity and high toughness to viscoelastic
polymer materials are ubiquitous in industries such as concerning automobiles
and medical devices. One of the major problems to overcome for toughening is
catastrophic failure linked to a velocity jump, i.e., a sharp transition in the
velocity of crack propagation occurred in a narrow range of the applied load.
However, its physical origin has remained an enigma despite previous studies
over 35 years. Here, we propose an exactly solvable model that exhibits the
velocity jump incorporating linear viscoelasticity with a cutoff length for a
continuum description. With the exact solution, we elucidate the physical
origin of the velocity jump: it emerges from a dynamic glass transition in the
vicinity of the propagating crack tip. We further quantify the velocity jump
together with slow- and fast-velocity regimes of crack propagation, which would
stimulate the development of tough polymer materials.


title: Accurate OH maser positions from the SPLASH pilot region

abstract:
  We report on high spatial resolution observations, using the Australia
Telescope Compact Array (ATCA), of ground-state OH masers. These observations
were carried out toward 196 pointing centres previously identified in the
Southern Parkes Large-Area Survey in Hydroxyl (SPLASH) pilot region, between
Galactic longitudes of $334^{\circ}$ and $344^{\circ}$ and Galactic latitudes
of $-2^{\circ}$ and $+2^{\circ}$. Supplementing our data with data from the
MAGMO (Mapping the Galactic Magnetic field through OH masers) survey, we find
maser emission towards 175 of the 196 target fields. We conclude that about
half of the 21 non-detections were due to intrinsic variability. Due to the
superior sensitivity of the follow-up ATCA observations, and the ability to
resolve nearby sources into separate sites, we have identified 215 OH maser
sites towards the 175 fields with detections. Among these 215 OH maser sites,
111 are new detections. After comparing the positions of these 215 maser sites
to the literature, we identify 122 (57 per cent) sites associated with evolved
stars (one of which is a planetary nebula), 64 (30 per cent) with star
formation, two sites with supernova remnants and 27 (13 per cent) of unknown
origin. The infrared colors of evolved star sites with symmetric maser profiles
tend to be redder than those of evolved star sites with asymmetric maser
profiles, which may indicate that symmetric sources are generally at an earlier
evolutionary stage.


title:
Large deviation theorem for zeros of polynomials and Hermitian random
  matrices

abstract:
  We give abstract versions of the large deviation theorem for the distribution
of zeros of polynomials and apply them to the characteristic polynomials of
Hermitian random matrices. We obtain new estimates related to the local
semi-circular law for the empirical spectral distribution of these matrices
when the 4th moments of their entries are controlled.


title: A note on curvature estimate of the Hermitian-Yang-Mills flow

abstract:
  In this paper, we study the curvature estimate of the Hermitian-Yang-Mills
flow on holomorphic vector bundles. In one simple case, we show that the
curvature of the evolved Hermitian metric is uniformly bounded away from the
analytic subvariety determined by the Harder-Narasimhan-Seshadri filtration of
the holomorphic vector bundle.


title: On the Quantitative Analysis of Decoder-Based Generative Models

abstract:
  The past several years have seen remarkable progress in generative models
which produce convincing samples of images and other modalities. A shared
component of many powerful generative models is a decoder network, a parametric
deep neural net that defines a generative distribution. Examples include
variational autoencoders, generative adversarial networks, and generative
moment matching networks. Unfortunately, it can be difficult to quantify the
performance of these models because of the intractability of log-likelihood
estimation, and inspecting samples can be misleading. We propose to use
Annealed Importance Sampling for evaluating log-likelihoods for decoder-based
models and validate its accuracy using bidirectional Monte Carlo. The
evaluation code is provided at https://github.com/tonywu95/eval_gen. Using this
technique, we analyze the performance of decoder-based models, the
effectiveness of existing log-likelihood estimators, the degree of overfitting,
and the degree to which these models miss important modes of the data
distribution.


title:
Characterizations of Jordan mappings on some rings and algebras through
  zero products

abstract:
  Let $\mathcal{U}=\left[
  \begin{array}{cc}
  \mathcal{A} & \mathcal{M}
  \mathcal{N}& \mathcal{B}
  \end{array}
  \right]$ be a generalized matrix ring, where $\mathcal{A}$ and $\mathcal{B}$
are 2-torsion free. We prove that if $\phi :\mathcal{U}\rightarrow \mathcal{U}$
is an additive mapping such that $\phi(U)\circ V+U\circ \phi(V)=0$ whenever
$UV=VU=0,$ then $\phi=\delta+\eta$, where $\delta$ is a Jordan derivation and
$\eta$ is a multiplier. As its applications, we prove that the similar
conclusion remains valid on full matrix algebras, unital prime rings with a
nontrivial idempotent, unital standard operator algebras, CDCSL algebras and
von Neumann algebras.


title: Effective pion mass term and the trace anomaly

abstract:
  Recently, we developed an effective theory of pions and a light dilatonic
meson for gauge theories with spontaneously broken chiral symmetry that are
close to the conformal window. The pion mass term in this effective theory
depends on an exponent $y$. We derive the transformation properties under
dilatations of the renormalized fermion mass, and use this to rederive
$y=3-\gamma_m^*$, where $\gamma_m^*$ is fixed-point value of the mass anomalous
dimension at the sill of the conformal window. This value for $y$ is consistent
with the trace anomaly of the underlying near-conformal gauge theory.


title:
Byzantine Processors and Cuckoo Birds: Confining Maliciousness to the
  Outset

abstract:
  Are there Byzantine Animals? A Fooling Behavior is exhibited by the Cuckoo
bird. It sneakily replaces some of the eggs of other species with its own. Lest
the Cuckoo extinct itself by destroying its host, it self-limits its power: It
does not replace too large a fraction of the eggs. Here, we show that any
Byzantine Behavior that does not destroy the system it attacks, i.e. allows the
system to solve an easy task like epsilon-agreement, then its maliciousness can
be confined to be the exact replica of the Cuckoo bird behavior: Undetectably
replace an input of a processor and let the processor behave correctly
thereafter with respect to the new input. In doing so we reduce the study of
Byzantine behavior to fail-stop (benign) behavior with the Cuckoo caveat of a
fraction of the inputs replaced. We establish a complete correspondence between
the Byzantine and the Benign, modulo different thresholds, and replaced inputs.
This work is yet another step in a line of work unifying seemingly distinct
distributed system models, dispelling the Myth that Distributed Computing is a
plethora of distinct isolated models, each requiring its specialized tools and
ideas in order to determine solvability of tasks. Thus, hereafter, Byzantine
Computability questions can be reduced to questions in the benign failure
setting. We also show that the known results about correlated faults in the
asynchronous benign setting can be imported verbatim to the asynchronous
Byzantine setting. Finally, as in the benign case in which we have the property
that a processor can output once its faulty behavior stops for long enough, we
show this can be done in a similar manner in the Byzantine case. This
necessitated the generalization of Reliable Broadcast to what we term
Recoverable Reliable Broadcast.


title:
Two-carrier analyses of the transport properties of black phosphorus
  under pressure

abstract:
  We report on the electronic transport properties of black phosphorus and
analyze them using a two-carrier model in a wide range of pressure up to 2.5
GPa. In semiconducting state at 0.29 GPa, the remarkable non-linear behavior in
the Hall resistance is reasonably reproduced by assuming the coexistence of two
kinds of hole with different densities and mobilities. On the other hand,
two-carrier analyses of the magnetotransport properties above 1.01 GPa suggest
the coexistence of high mobility electron and hole carriers that have almost
the same densities, i.e., nearly compensated semimetallic nature of black
phosphorus. In the semimetallic state, analyses of both the two-carrier model
and quantum oscillations indicate a systematic increase in the carrier
densities as pressure increases. An observed sign inversion of Hall resistivity
at low magnetic fields suggests the existence of high mobility electrons
(\sim105 cm2 V-1 s-1) that is roughly ten times larger than that of holes, in
the semimetallic black phosphorus. We conclude that the extremely large
positive magnetoresistance that has been observed in semimetallic state cannot
be reproduced by a conventional two-carrier model.


title:
Revisiting 802.11 for User Fairness and Efficient Channel Utilization in
  Presence of LTE-U

abstract:
  A promising solution satisfying the industry's demand to have minimum
alterations in LTE for its operation in unlicensed spectrum is duty cycled
LTE-U scheme, which adopts discontinuous transmission to ensure fair
coexistence with 802.11 (Wi-Fi) WLANs. Even though the scheme guarantees to
maintain Wi-Fi network performance, the fairness among Wi-Fi users still
remains arcane. In this work, we present a practical scenario where LTE-U,
despite being discontinuous (by following an ON-OFF cycle), results in not only
unfair throughput distribution among Wi-Fi users but also causes degradation in
Wi-Fi APs downlink performance. This is due to the domination of few Wi-Fi
users who harness channel in both ON and OFF durations of LTE-U, namely
non-victim users over those who get access only in OFF duration, called victim
users. In this paper, we studied the performance of victim and non-victim Wi-Fi
users, and Wi-Fi AP while varying LTE-U ON duration (i.e., duty cycle). A
propitious scheme is proposed for WLANs, with regard to ease of implementation,
employing Point Coordination Function (PCF) mode of 802.11, promising fairness
among Wi-Fi users with improvement in the channel utilization of Wi-Fi network.
An analytical model is developed to demonstrate guaranteed improvement and
validate the simulation results.


title: Chromatic number of ISK4-free graphs

abstract:
  A graph $G$ is said to be ISK4-free if it does not contain any subdivision of
$K_4$ as an induced subgraph. In this paper, we propose new upper bounds for
chromatic number of ISK4-free graphs and $\{$ISK4, triangle$\}$-free graphs.


title: Order divisor graphs of finite groups

abstract:
  The interplay between groups and graphs have been the most famous and
productive area of algebraic graph theory. In this paper, we introduce and
study the graphs whose vertex set is group G such that two distinct vertices a
and b having different orders are adjacent provided that o(a) divides o(b) or
o(b) divides o(a).


title:
Statistical mechanics of the inverse Ising problem and the optimal
  objective function

abstract:
  The inverse Ising problem seeks to reconstruct the parameters of an Ising
Hamiltonian on the basis of spin configurations sampled from the Boltzmann
measure. Over the last decade, many applications of the inverse Ising problem
have arisen, driven by the advent of large-scale data across different
scientific disciplines. Recently, strategies to solve the inverse Ising problem
based on convex optimisation have proven to be very successful. These
approaches maximise particular objective functions with respect to the model
parameters. Examples are the pseudolikelihood method and interaction screening.
In this paper, we establish a link between approaches to the inverse Ising
problem based on convex optimisation and the statistical physics of disordered
systems. We characterise the performance of an arbitrary objective function and
calculate the objective function which optimally reconstructs the model
parameters. We evaluate the optimal objective function within a
replica-symmetric ansatz and compare the results of the optimal objective
function with other reconstruction methods. Apart from giving a theoretical
underpinning to solving the inverse Ising problem by convex optimisation, the
optimal objective function outperforms state-of-the-art methods, albeit by a
small margin.


title: Amplitude of solar wind density turbulence from 10--45 $R_{\odot}$

abstract:
  We report on the amplitude of the density turbulence spectrum ($C_{N}^{2}$)
and the density modulation index ($\delta N/N$) in the solar wind between $10$
and $45 R_{\odot}$. We derive these quantities using a structure function that
is observationally constrained by occultation observations of the Crab nebula
made in 2011 and 2013 and similar observations published earlier. We use the
most general form of the structure function, together with currently used
prescriptions for the inner/dissipation scale of the turbulence spectrum. Our
work yields a comprehensive picture of a) the manner in which $C_{N}^{2}$ and
$\delta N/N$ vary with heliocentric distance in the solar wind and b) of the
solar cycle dependence of these quantities.


title:
Powerful Radio Emission From Low-mass Supermassive Black Holes Favors
  Disk-like Bulges

abstract:
  The origin of spin of low-mass supermassive black hole (SMBH) is still a
puzzle at present. We here report a study on the host galaxies of a sample of
radio-selected nearby ($z<0.05$) Seyfert 2 galaxies with a BH mass of $10^{6-7}
M_\odot$. By modeling the SDSS $r$-band images of these galaxies through a
2-dimensional bulge+disk decomposition, we identify a new dependence of SMBH's
radio power on host bulge surface brightness profile, in which more powerful
radio emission comes from a SMBH associated with a more disk-like bulge. This
result means low-mass and high-mass SMBHs are spun up by two entirely different
modes that correspond to two different evolutionary paths. A low-mass SMBH is
spun up by a gas accretion with significant disk-like rotational dynamics of
the host galaxy in the secular evolution, while a high-mass one by a BH-BH
merger in the merger evolution.


title:
Thermodynamic Volume Product in Spherically Symmetric and Axisymmetric
  Spacetime

abstract:
  In this Letter, we have examined the thermodynamic volume products for
spherically symmetric and axisymmetric spacetimes in the framework of
\emph{extended phase space}. Such volume products usually formulated in terms
of the outer horizon~(${\cal H}^{+}$) and the inner horizon~(${\cal H}^{-}$) of
black hole ~ (BH) spacetime. Besides volume product, the other thermodynamic
formulations like \emph{volume sum, volume minus and volume division} are
considered for a wide variety of spherically symmetric spacetime and
axisymmetric spacetimes. Like area~(or entropy) product of multihorizons, the
mass-independent~(universal) feature of volume products are sometimes also
\emph{fail}. In particular for a spherically symmetric AdS spacetimes the
simple thermodynamic volume product of ${\cal H}^{\pm}$ is not
mass-independent. In this case, more complicated combinations of outer and
inner horizon volume products are indeed mass-independent. For a particular
class of spherically symmetric cases i.e. Reissner Nordstr\"om BH of Einstein
gravity and Kehagias-Sfetsos BH of Ho\v{r}ava Lifshitz gravity, the
thermodynamic volume products of ${\cal H}^{\pm}$ is indeed \emph{universal}.
For axisymmetric class of BH spacetime in Einstein gravity all the combinations
are \emph{mass-dependent}. There has been no chance to formulate any
combinations of volume product relation is to be mass-independent.
Interestingly, \emph{only the rotating BTZ black hole} in 3D provides the
volume product formula is mass-independent i.e. \emph{universal} and hence it
is quantized.


title:
Deconfinement and chiral transition in AdS/QCD wall models supplemented
  with a magnetic field

abstract:
  We discuss the phenomenon of (inverse) magnetic catalysis for both the
deconfinement and chiral transition. We discriminate between the hard and soft
wall model, which we suitably generalize to include a magnetic field. Our
findings show a critical deconfinement temperature going down, in contrast with
the chiral restoration temperature growing with increasing magnetic field. This
is at odds with contemporary lattice data, so the quest for a holographic QCD
model capable of capturing inverse magnetic catalysis in the chiral sector
remains open.


title:
A FE-ADMM algorithm for Lavrentiev-regularized state-constrained
  elliptic control problem

abstract:
  In this paper, elliptic control problems with pointwise box constraints on
the state is considered, where the corresponding Lagrange multipliers in
general only represent regular Borel measure functions. To tackle this
difficulty, the Lavrentiev regularization is employed to deal with the state
constraints. To numerically discretize the resulted problem, since the weakness
of variational discretization in numerical implementation, full piecewise
linear finite element discretization is employed. Estimation of the error
produced by regularization and discretization is done. The error order of full
discretization is not inferior to that of variational discretization because of
the Lavrentiev-regularization. Taking the discretization error into account,
algorithms of high precision do not make much sense. Utilizing efficient
first-order algorithms to solve discretized problems to moderate accuracy is
sufficient. Then a heterogeneous alternating direction method of multipliers
(hADMM) is proposed. Different from the classical ADMM, our hADMM adopts two
different weighted norms in two subproblems respectively. Additionally, to get
more accurate solution, a two-phase strategy is presented, in which the
primal-dual active set (PDAS) method is used as a postprocessor of the hADMM.
Numerical results not only verify error estimates but also show the efficiency
of the hADMM and the two-phase strategy.


title:
Energetic disorder induced leakage current in organic bulk
  heterojunction solar cells: comprehending the ultra-high open circuit voltage
  loss at low temperatures

abstract:
  In organic bulk heterojunction solar cells, the open circuit voltage
($V_\mathrm{oc}$) suffers from an ultra-high loss at low temperatures. In this
work we investigate the origin of the loss through calculating the
$V_\mathrm{oc}-T$ plots with the device model method systematically and
comparing it with experimentally observed ones. When the energetic disorder is
incorporated into the model by considering the disorder-suppressed and
temperature-dependent charge carrier mobilities, it is found that for
nonselective contacts the $V_\mathrm{oc}$ reduces drastically under the low
temperature regime, while for selective contacts the $V_\mathrm{oc}$ keeps
increasing with the decreasing temperature. The main reason is revealed that as
the temperature decreases, the reduced mobilities give rise to low charge
extraction efficiency and small bimolecular recombination rate for the
photogenerated charge carriers, so that in the former case they can be
extracted from the wrong electrode to form a leakage current which counteracts
the photocurrent and increases quickly with voltage, leading to the anomalous
reduction of $V_\mathrm{oc}$. In addition, it is revealed that the charge
generation rate is slow-varying with temperature and does not induce
significant $V_\mathrm{oc}$ loss. This work also provides a comprehensive
picture for the $V_\mathrm{oc}$ behavior under varying device working
conditions.


title: Efficient Web-based Data Imputation with Graph Model

abstract:
  A challenge for data imputation is the lack of knowledge. In this paper, we
attempt to address this challenge by involving extra knowledge from web. To
achieve high-performance web-based imputation, we use the dependency, i.e.FDs
and CFDs, to impute as many as possible values automatically and fill in the
other missing values with the minimal access of web, whose cost is relatively
large. To make sufficient use of dependencies, We model the dependency set on
the data as a graph and perform automatical imputation and keywords generation
for web-based imputation based on such graph model. With the generated
keywords, we design two algorithms to extract values for imputation from the
search results. Extensive experimental results based on real-world data
collections show that the proposed approach could impute missing values
efficiently and effectively compared to existing approach.


title:
Generalized Analytical Solutions and Synchronization Dynamics of Coupled
  Simple Nonlinear Electronic Circuits

abstract:
  In this paper we present a generalized analytical solution to the generalized
state equations of coupled second-order non-autonomous circuit systems. The
analytical solutions thus obtained are used to study the synchronization
dynamics of two different types of circuit systems, differing only by their
constituting nonlinear element. The synchronization dynamics of the coupled
systems are studied through two-parameter bifurcation diagrams, phase portraits
and time-series plots obtained from the explicit analytical solutions. The
mechanism of synchronization is realized through the bifurcation of the
eigenvalues as functions of the control parameter in each of the coupled
piecewise linear regions of the drive and response systems. The stability of
the synchronized state for coupled identical chaotic states are studeid through
the {\emph{master stability function}}. Further, {\emph{conditional Lyapunov
exponents}} and {\emph{Kaplan-Yorke dimension}} are obtained to confirm the
synchronized states of both coupled identical and non-identical chaotic states.
The synchronization dynamics of coupled chaotic systems studied through
two-parameter bifurcation diagrams obtained from explicit analytical solutions
is reported in the literature for the first time.


title:
Pion Fluctuation in High Energy Collisions - A Chaos-based Quantitative
  Estimation with Visibility Graph Technique

abstract:
  We propose a new approach for studying pion fluctuation for deeper
understanding of the dynamical process involved, from a perspective of
fBm-based complex network analysis method called Visibility graph Analysis.
This chaos-based, rigorous, non-linear technique is applied to study the
erratic behavior of multipion production in \pi^{-}-Ag/Br interactions at 350
GeV. This method can offer reliable results with finite data points. The Power
of Scale-freeness of Visibility Graph denoted by-PSVG is a measure of
fractality, which can be used as a quantitative parameter for the assessment of
the state of a chaotic system. The event-wise fluctuation of the multipion
production process can be described by this parameter-PSVG. From the analysis
of the PSVG parameter, we can quantitatively confirm that fractal behavior of
the particle production process depends on the target excitation and also the
fractality decreases with the increase of target excitation.


title:
Maximum Principle for Partial Observed Zero-Sum Stochastic Differential
  Game of Mean-Field SDEs

abstract:
  In this paper, we consider a partial observed two-person zero-sum stochastic
differential game problem where the system is governed by a stochastic
differential equation of mean-field type. Under standard assumptions on the
coefficients, the maximum principles for optimal open-loop control in a strong
sense as well as a weak one are established by the associated optimal control
theory in Tang and Meng (2016). To illustrate the general results, a class of
linear quadratic stochastic differential game problem is discussed and the
existence and dual characterization for the partially observed open-loop saddle
are obtained.