title: A Generalized Information Theoretical Model for Quantum Secret Sharing

abstract:
  An information theoretical model for quantum secret sharing was introduced by
A. C. A. Nascimento et al.[Quantum Inf. Comput. Vol.5,1,205,68-79(2003)], which
was analyzed by quantum information theory. In this paper, we analyze this
information theoretical model using the properties of the quantum access
structure. By the analysis we propose a generalized model definition for the
quantum secret sharing schemes. In our model, there are more quantum access
structures which can be realized by our generalized quantum secret sharing
schemes than those of the previous one. In addition, we also analyse two kinds
of important quantum access structures to illustrate the existence and
rationality of the generalized quantum secret sharing schemes and consider the
security of the scheme by simple examples.


title: Breathers in a locally resonant granular chain with precompression

abstract:
  We study a locally resonant granular material in the form of a precompressed
Hertzian chain with linear internal resonators. Using an asymptotic reduction,
we derive an effective nonlinear Schr\"odinger (NLS) modulation equation. This,
in turn, leads us to provide analytical evidence, subsequently corroborated
numerically, for the existence of two distinct types of discrete breathers
related to acoustic or optical modes: (a) traveling bright breathers with a
strain profile exponentially vanishing at infinity and (b) stationary and
traveling dark breathers, exponentially localized, time-periodic states mounted
on top of a non-vanishing background. The stability and bifurcation structure
of numerically computed exact stationary dark breathers is also examined.
Stationary bright breathers cannot be identified using the NLS equation, which
is defocusing at the upper edges of the phonon bands and becomes linear at the
lower edge of the optical band.


title: Solving Society's Big Ills, A Small Step

abstract:
  We look at a collection of conjectures with the unifying message that smaller
social systems, tend to be less complex and can be aligned better, towards
fulfilling their intended objectives. We touch upon a framework, referred to as
the four pronged approach that can aid the analysis of social systems. The four
prongs are:
  1. The Uncertainty Principle of the Social Sciences
  2. The Objectives of a Social System or the Responsibilities of the Players
  3. The Need for Smaller Organizations
  4. Redirecting Unintended Outcomes
  Smaller organizations mitigating the disruptive effects of corruption is
discussed and also the need for organizations, whose objective is to foster the
development of other smaller organizations. We consider a way of life, which is
about respect for knowledge and a desire to seek it. Knowledge can help
eradicate ignorance, but the accumulation of knowledge can lead to
overconfidence. Hence it becomes important to instill an attitude that does not
knowledge too seriously, along with the thirst for knowledge. All of this is
important to create an environment that is conducive for smaller organizations
and can be viewed as a natural extension of studies that fall under the wider
category of understanding factors and policies aimed at increasing the welfare
or well-being to society.


title: L0-norm Sparse Graph-regularized SVD for Biclustering

abstract:
  Learning the "blocking" structure is a central challenge for high dimensional
data (e.g., gene expression data). Recently, a sparse singular value
decomposition (SVD) has been used as a biclustering tool to achieve this goal.
However, this model ignores the structural information between variables (e.g.,
gene interaction graph). Although typical graph-regularized norm can
incorporate such prior graph information to get accurate discovery and better
interpretability, it fails to consider the opposite effect of variables with
different signs. Motivated by the development of sparse coding and
graph-regularized norm, we propose a novel sparse graph-regularized SVD as a
powerful biclustering tool for analyzing high-dimensional data. The key of this
method is to impose two penalties including a novel graph-regularized norm
($|\pmb{u}|\pmb{L}|\pmb{u}|$) and $L_0$-norm ($\|\pmb{u}\|_0$) on singular
vectors to induce structural sparsity and enhance interpretability. We design
an efficient Alternating Iterative Sparse Projection (AISP) algorithm to solve
it. Finally, we apply our method and related ones to simulated and real data to
show its efficiency in capturing natural blocking structures.


title: Fractal Dimension Invariant Filtering and Its CNN-based Implementation

abstract:
  Fractal analysis has been widely used in computer vision, especially in
texture image processing and texture analysis. The key concept of fractal-based
image model is the fractal dimension, which is invariant to bi-Lipschitz
transformation of image, and thus capable of representing intrinsic structural
information of image robustly. However, the invariance of fractal dimension
generally does not hold after filtering, which limits the application of
fractal-based image model. In this paper, we propose a novel fractal dimension
invariant filtering (FDIF) method, extending the invariance of fractal
dimension to filtering operations. Utilizing the notion of local
self-similarity, we first develop a local fractal model for images. By adding a
nonlinear post-processing step behind anisotropic filter banks, we demonstrate
that the proposed filtering method is capable of preserving the local
invariance of the fractal dimension of image. Meanwhile, we show that the FDIF
method can be re-instantiated approximately via a CNN-based architecture, where
the convolution layer extracts anisotropic structure of image and the nonlinear
layer enhances the structure via preserving local fractal dimension of image.
The proposed filtering method provides us with a novel geometric interpretation
of CNN-based image model. Focusing on a challenging image processing task ---
detecting complicated curves from the texture-like images, the proposed method
obtains superior results to the state-of-art approaches.


title:
Global well-posedness of the Boltzmann equation with large amplitude
  initial data

abstract:
  The global well-posedness of the Boltzmann equation with initial data of
large amplitude has remained a long-standing open problem. In this paper, by
developing a new $L^\infty_xL^1_{v}\cap L^\infty_{x,v}$ approach, we prove the
global existence and uniqueness of mild solutions to the Boltzmann equation in
the whole space or torus for a class of initial data with bounded
velocity-weighted $L^\infty$ norm under some smallness condition on
$L^1_xL^\infty_v$ norm as well as defect mass, energy and entropy so that the
initial data allow large amplitude oscillations. Both the hard and soft
potentials with angular cut-off are considered, and the large time behavior of
solutions in $L^\infty_{x,v}$ norm with explicit rates of convergence is also
studied.


title: Tensor Methods and Recommender Systems

abstract:
  A substantial progress in development of new and efficient tensor
factorization techniques has led to an extensive research of their
applicability in recommender systems field. Tensor-based recommender models
push the boundaries of traditional collaborative filtering techniques by taking
into account a multifaceted nature of real environments, which allows to
produce more accurate, situational (e.g. context-aware, criteria-driven)
recommendations. Despite the promising results, tensor-based methods are poorly
covered in existing recommender systems surveys. This survey aims to complement
previous works and provide a comprehensive overview on the subject. To the best
of our knowledge, this is the first attempt to consolidate studies from various
application domains in an easily readable, digestible format, which helps to
get a notion of the current state of the field. We also provide a high level
discussion of the future perspectives and directions for further improvement of
tensor-based recommendation systems.


title: Black hole solutions in de Rham-Gabadadze-Tolley massive gravity

abstract:
  We present a detailed study of the static spherically symmetric solutions in
de Rham-Gabadadze-Tolley (dRGT) theory. Since the diffeomorphism invariance can
be restored by introducing the St\"{u}ckelberg fields $\phi^a$, there is new
invariant $I^{ab}=g^{\mu\nu}\partial_{\mu}\phi^a\partial_\nu\phi^b$ in the
massive gravity, which adds to the ones usually encountered in general
relativity (GR). In the unitary gauge $\phi^a=x^\mu\delta_\mu^a$, any inverse
metric $g^{\mu\nu}$ that has divergence including the coordinate singularity in
GR would exhibit a singularity in the invariant $I^{ab}$. Therefore, there is
no conventional Schwarzschild metric if we choose unitary gauge. In this paper,
we obtain a self-consistent static spherically symmetric ansatz in the
nonunitary gauge. Under this ansatz, we find that there are seven solutions
including the Schwarzschild solution, Reissner-Nordstr\"{o}m solution and five
other solutions. These solutions may possess an event horizon depending upon
the physical parameters (Schwarzschild radius $r_s$, scalar charge $S$ and/or
electric charge $Q$). If these solutions possess an event horizon, we show that
the singularity of $I^{ab}$ is absent at the horizon. Therefore, these
solutions may become candidates for black holes in dRGT.


title: Sparse Hamburger Moment Sequences and Completions in Several Variables

abstract:
  Putinar and Vasilescu have given an algebraic characterization of Hamburger
moment sequences in several variables. In this paper we give a characterization
of sparse moment subsequences of Hamburger moment sequences and consider the
problem of completion of these moment subsequences.


title: Learning Image Matching by Simply Watching Video

abstract:
  This work presents an unsupervised learning based approach to the ubiquitous
computer vision problem of image matching. We start from the insight that the
problem of frame-interpolation implicitly solves for inter-frame
correspondences. This permits the application of analysis-by-synthesis: we
firstly train and apply a Convolutional Neural Network for frame-interpolation,
then obtain correspondences by inverting the learned CNN. The key benefit
behind this strategy is that the CNN for frame-interpolation can be trained in
an unsupervised manner by exploiting the temporal coherency that is naturally
contained in real-world video sequences. The present model therefore learns
image matching by simply watching videos. Besides a promise to be more
generally applicable, the presented approach achieves surprising performance
comparable to traditional empirically designed methods.


title: Globally Normalized Transition-Based Neural Networks

abstract:
  We introduce a globally normalized transition-based neural network model that
achieves state-of-the-art part-of-speech tagging, dependency parsing and
sentence compression results. Our model is a simple feed-forward neural network
that operates on a task-specific transition system, yet achieves comparable or
better accuracies than recurrent models. We discuss the importance of global as
opposed to local normalization: a key insight is that the label bias problem
implies that globally normalized models can be strictly more expressive than
locally normalized models.


abstract:
  In this paper a connection between Hamburger moment sequences and their
moment subsequences is given and the determinacy of these problems are related.


title: A Light-Weight Forwarding Plane for Content-Centric Networks

abstract:
  We present CCN-DART, a more efficient forwarding approach for content-centric
networking (CCN) than named data networking (NDN) that substitutes Pending
Interest Tables (PIT) with Data Answer Routing Tables (DART) and uses a novel
approach to eliminate forwarding loops. The forwarding state required at each
router using CCN-DART consists of segments of the routes between consumers and
content providers that traverse a content router, rather than the Interests
that the router forwards towards content providers. Accordingly, the size of a
DART is proportional to the number of routes used by Interests traversing a
router, rather than the number of Interests traversing a router. We show that
CCN-DART avoids forwarding loops by comparing distances to name prefixes
reported by neighbors, even when routing loops exist. Results of simulation
experiments comparing CCN-DART with NDN using the ndnSIM simulation tool show
that CCN-DART incurs 10 to 20 times less storage overhead.


title:
Non-standard conditionally specified models for non-ignorable missing
  data

abstract:
  Data analyses typically rely upon assumptions about missingness mechanisms
that lead to observed versus missing data. When the data are missing not at
random, direct assumptions about the missingness mechanism, and indirect
assumptions about the distributions of observed and missing data, are typically
untestable. We explore an approach, where the joint distribution of observed
data and missing data is specified through non-standard conditional
distributions. In this formulation, which traces back to a factorization of the
joint distribution, apparently proposed by J.W. Tukey, the modeling assumptions
about the conditional factors are either testable or are designed to allow the
incorporation of substantive knowledge about the problem at hand, thereby
offering a possibly realistic portrayal of the data, both missing and observed.
We apply Tukey's conditional representation to exponential family models, and
we propose a computationally tractable inferential strategy for this class of
models. We illustrate the utility of this approach using high-throughput
biological data with missing data that are not missing at random.


title: Post hoc verification with a single prover

abstract:
  We propose a simple protocol for the verification of quantum computation
after the computation has been performed. Our construction can be seen as an
improvement on previous results in that it requires only a single prover, who
is restricted to measuring qubits in the $X$ or $Z$ basis, while requiring only
one way communication, from the prover to the verifier. We also show similar
constant round protocols with purely classical verifiers are not possible,
unless BQP is contained in the third level of the polynomial hierarchy.


title:
The Circle of Investment: Connecting the Dots of the Portfolio
  Management Cycle...

abstract:
  We will look at the entire cycle of the investment process relating to all
aspects of, formulating an investment hypothesis, constructing a portfolio
based on that, executing the trades to implement it, on-going risk management,
periodically measuring the performance of the portfolio, and rebalancing the
portfolio either due to an increase in the risk parameters or due to a
deviation from the intended asset allocation. We provide several illustrative
analogies that are meant to intuitively explain the pleasures and the pitfalls
that can arise while managing a portfolio. If we consider the entire investment
management procedure as being akin to connecting the dots of a circle, then the
Circle of Investment can be represented as a dotted circle with many dots
falling approximately on the circumference and with no clue about the exact
location of the centre or the length of the radius. We represent the investment
process as a dotted circle since there is a lot of ambiguity in the various
steps involved. The circle also indicates the repetitive nature of many steps
that are continuously carried out while investing. This work introduces two new
points pertaining to this dotted circle and improves the ability, to understand
how far-off this dotted circle is, from a more well-defined circle and, to
create a well-formed circle. The two innovations we introduce are:
  1. The first, relating to the limitations that apply to any finding in the
social sciences, would be the additional point we introduce that lies near the
centre of the circle. We title this as, 'The Uncertainty Principle of the
Social Sciences'.
  2. The second, relating to establishing confidence levels in a systematic
manner for each view we associate with a security or group of securities as
required by the Black-Litterman framework, would be the new point we present
near the circumference of the circle.


title:
Self-Diagnosis, Scaffolding and Transfer in a More Conventional
  Introductory Physics Problem

abstract:
  Previously we discussed how well students in an introductory physics course
diagnosed their mistakes on a quiz problem with different levels of scaffolding
support. In that case, the problem they self-diagnosed was unusually difficult.
We also discussed issues related to transfer, particularly the fact that the
transfer problem in the midterm that corresponded to the self-diagnosed problem
was a far transfer problem. Here, we discuss a related intervention in which we
repeated the study methodology with the same students in the same intervention
groups, using a new quiz problem which was more typical for these students and
a near transfer problem. We discuss how these changes affected students'
ability to self-diagnose and transfer from the self-diagnosed quiz problem to a
transfer problem on the midterm exam.


title: How local is the information in MPS/PEPS tensor networks?

abstract:
  Two dimensional tensor networks such as projected entangled pairs states
(PEPS) are generally hard to contract. This is arguably the main reason why
variational tensor network methods in 2D are still not as successful as in 1D.
However, this is not necessarily the case if the tensor network represents a
gapped ground state of a local Hamiltonian; such states are subject to many
constraints and contain much more structure. In this paper we introduce a new
approach for approximating the expectation value of a local observable in
ground states of local Hamiltonians that are represented as PEPS
tensor-networks. Instead of contracting the full tensor-network, we try to
estimate the expectation value using only a local patch of the tensor-network
around the observable. Surprisingly, we demonstrate that this is often easier
to do when the system is frustrated. In such case, the spanning vectors of the
local patch are subject to non-trivial constraints that can be utilized via a
semi-definite program to calculate rigorous lower- and upper-bounds on the
expectation value. We test our approach in 1D systems, where we show how the
expectation value can be calculated up to at least 3 or 4 digits of precision,
even when the patch radius is smaller than the correlation length.


title: Tukey's transformational ladder for portfolio management

abstract:
  Over the past half-century, the empirical finance community has produced vast
literature on the advantages of the equally weighted S\&P 500 portfolio as well
as the often overlooked disadvantages of the market capitalization weighted
Standard and Poor's (S\&P 500) portfolio (see \cite{Bloom}, \cite{Uppal},
\cite{Jacobs}, \cite{Treynor}). However, portfolio allocation based on Tukey's
transformational ladde have, rather surprisingly, remained absent from the
literature. In this work, we consider the S\&P 500 portfolio over the 1958-2015
time horizon weighted by Tukey's transformational ladder (\cite{Tukey2}):
$1/x^2,\,\, 1/x,\,\, 1/\sqrt{x},\,\, \text{log}(x),\,\, \sqrt{x},\,\, x,\,\,
\text{and} \,\, x^2$, where $x$ is defined as the market capitalization
weighted S\&P 500 portfolio. Accounting for dividends and transaction fees, we
find that the 1/$x^2$ weighting strategy produces cumulative returns that
significantly dominates all other portfolios, achieving a compound annual
growth rate of 18\% over the 1958-2015 horizon. Our story is furthered by a
startling phenomenon: both the cumulative and annual returns of the $1/x^2$
weighting strategy are superior to those of the $1/x$ weighting strategy, which
are in turn superior to those of the 1/$\sqrt{x}$ weighted portfolio, and so
forth, ending with the $x^2$ transformation, whose cumulative returns are the
lowest of the seven transformations of Tukey's transformational ladder. The
order of cumulative returns precisely follows that of Tukey's transformational
ladder. To the best of our knowledge, we are the first to discover this
phenomenon.


title: Ballistic Deposition of Nanoclusters

abstract:
  Nanoporous thin-films are an important class of materials, offering a way to
observe fundamental surface and bulk processes with particles larger than
individual atoms, but small enough to interact significantly with each other
through mechanisms such as stress and surface mobility. In-Situ X-ray
Reflectivity and Grazing Incidence Small Angle X-Ray Scattering (GISAXS) were
used to monitor thin-films grown from Tungsten Disilicide (WSi$_2$) and Copper
(Cu) nanoclusters. The nanoclusters ranged in size from 2 nm to 6 nm diameter
and were made by high-pressure magnetron sputtering via plasma-gas
condensation. X-Ray Reflectivity (XRR) measurements of the film at various
stages of growth reveal that the resulting films exhibit very low density,
approaching 15% of bulk density. This is consistent with a simple off-lattice
ballistic deposition model where particles stick at the point of first contact
without further restructuring. Furthermore, there is little merging or
sintering of the clusters in these films.


title: Fast DPP Sampling for Nystr\"om with Application to Kernel Methods

abstract:
  The Nystr\"om method has long been popular for scaling up kernel methods. Its
theoretical guarantees and empirical performance rely critically on the quality
of the landmarks selected. We study landmark selection for Nystr\"om using
Determinantal Point Processes (DPPs), discrete probability models that allow
tractable generation of diverse samples. We prove that landmarks selected via
DPPs guarantee bounds on approximation errors; subsequently, we analyze
implications for kernel ridge regression. Contrary to prior reservations due to
cubic complexity of DPPsampling, we show that (under certain conditions) Markov
chain DPP sampling requires only linear time in the size of the data. We
present several empirical results that support our theoretical analysis, and
demonstrate the superior performance of DPP-based landmark selection compared
with existing approaches.


title: Negation in SPARQL

abstract:
  This paper presents a thorough study of negation in SPARQL. The types of
negation supported in SPARQL are identified and their main features discussed.
Then, we study the expressive power of the corresponding negation operators. At
this point, we identify a core SPARQL algebra which could be used instead of
the W3C SPARQL algebra. Finally, we analyze the negation operators in terms of
their compliance with elementary axioms of set theory.


title:
Magnetic behaviour of dirty multiband superconductors near the upper
  critical field

abstract:
  Magnetic properties of dirty multiband superconductors near the upper
critical field are studied. The parameter $\kappa_2$ characterizing
magnetization slope is shown to have a significant temperature variation which
is quite sensitive to the pairing interactions and relative strengths of
intraband impurity scattering. In contrast to single-band superconductors the
increase of $\kappa_2$ at low temperatures can be arbitrary large determined by
the ratio of minimal and maximal diffusion coefficients in different bands.
Temperature dependencies of $\kappa_2(T)$ in two-band MgB$_2$ and iron-based
superconductors are shown to be much more sensitive to the multiband effects
than the upper critical field $H_{c2}(T)$.


title:
Diffractive dijet photoproduction in ultraperipheral collisions at the
  LHC in next-to-leading order QCD

abstract:
  We make predictions for the cross sections of diffractive dijet
photoproduction in $pp$, $pA$ and $AA$ ultraperipheral collisions (UPCs) at the
LHC during Runs 1 and 2 using next-to-leading perturbative QCD. We find that
the resulting cross sections are sufficiently large and, compared to
lepton-proton scattering at HERA, have an enhanced sensitivity to small
observed momentum fractions in the diffractive exchange, commonly denoted
$z_{P}^{\rm jets}$, and an unprecedented reach in the invariant mass of the
photon-nucleon system $W$. We examine two competing schemes of diffractive QCD
factorization breaking, which assume either a global suppression factor or a
suppression for resolved photons only and demonstrate that the two scenarios
can be distinguished by the nuclear dependence of the distributions in the
observed parton momentum fraction in the photon $x_{\gamma}^{\rm jets}$.


title: Polygon of recollements and $N$-complexes

abstract:
  We study a structure of subcategories which are called a polygon of
recollements in a triangulated category. First, we study a $2n$-gon of
recollements in an $(m/n)$-Calabi-Yau triangulated category. Second, we show
the homotopy category $\mathsf{K}(\mathsf{Mor}_{N-1}(\mathcal{B}))$ of
complexes of an additive category $\mathsf{Mor}_{N-1}(\mathcal{B})$ of $N-1$
sequences of split monomorphisms of an additive category $\mathcal{B}$ has a
$2N$-gon of recollments. Third, we show the homotopy category
$\mathsf{K}_{N}(\mathcal{B})$ of $N$-complexes of $\mathcal{B}$ has also a
$2N$-gon of recollments. Finally, we show there is a triangle equivalence
between $\mathsf{K}(\mathsf{Mor}_{N-1}(\mathcal{B}))$ and
$\mathsf{K}_{N}(\mathcal{B})$.


title: Band Gap Opening in Stanene Induced by Patterned B-N doping

abstract:
  Stanene is a quantum spin hall insulator and a promising material for
electronic and optoelectronic devices. Density functional theory (DFT)
calculations are performed to study the band gap opening in stanene by
elemental mono- (B, N) and co-doping (B-N). Different patterned B-N co-doping
is studied to change the electronic properties in stanene. A patterned B-N
co-doping opens the band gap in stanene and the semiconducting nature persists
with strain. Molecular dynamics (MD) simulations are performed to confirm the
thermal stability of such doped system. The stress-strain study indicates that
such doped system is as stable as pure stanene. Our work function calculations
show that stanene and doped stanene has lower work function than graphene and
thus promising material for photocatalysis and electronic devices.


title: Entanglement asymmetry for boosted black branes

abstract:
  We study the effects of asymmetry in entanglement thermodynamics of the CFT
subsystems. It is found that `boosted' $p$-branes backgrounds give rise to the
first law of the entanglement thermodynamics where the CFT pressure plays
decisive role in the entanglement. Two different strip like subsystems, one
parallel to the boost and the other perpendicular, are studied in the
perturbative regime, where $T_{thermal}\ll T_E$. We also discuss the AdS-wave
backgrounds where some universal bounds can be obtained.


title: Generating Natural Questions About an Image

abstract:
  There has been an explosion of work in the vision & language community during
the past few years from image captioning to video transcription, and answering
questions about images. These tasks have focused on literal descriptions of the
image. To move beyond the literal, we choose to explore how questions about an
image are often directed at commonsense inference and the abstract events
evoked by objects in the image. In this paper, we introduce the novel task of
Visual Question Generation (VQG), where the system is tasked with asking a
natural and engaging question when shown an image. We provide three datasets
which cover a variety of images from object-centric to event-centric, with
considerably more abstract training data than provided to state-of-the-art
captioning systems thus far. We train and test several generative and retrieval
models to tackle the task of VQG. Evaluation results show that while such
models ask reasonable questions for a variety of images, there is still a wide
gap with human performance which motivates further work on connecting images
with commonsense knowledge and pragmatics. Our proposed task offers a new
challenge to the community which we hope furthers interest in exploring deeper
connections between vision & language.


title: DASA: Domain Adaptation in Stacked Autoencoders using Systematic Dropout

abstract:
  Domain adaptation deals with adapting behaviour of machine learning based
systems trained using samples in source domain to their deployment in target
domain where the statistics of samples in both domains are dissimilar. The task
of directly training or adapting a learner in the target domain is challenged
by lack of abundant labeled samples. In this paper we propose a technique for
domain adaptation in stacked autoencoder (SAE) based deep neural networks (DNN)
performed in two stages: (i) unsupervised weight adaptation using systematic
dropouts in mini-batch training, (ii) supervised fine-tuning with limited
number of labeled samples in target domain. We experimentally evaluate
performance in the problem of retinal vessel segmentation where the SAE-DNN is
trained using large number of labeled samples in the source domain (DRIVE
dataset) and adapted using less number of labeled samples in target domain
(STARE dataset). The performance of SAE-DNN measured using $logloss$ in source
domain is $0.19$, without and with adaptation are $0.40$ and $0.18$, and $0.39$
when trained exclusively with limited samples in target domain. The area under
ROC curve is observed respectively as $0.90$, $0.86$, $0.92$ and $0.87$. The
high efficiency of vessel segmentation with DASA strongly substantiates our
claim.


title: Positron production in collision of heavy nuclei

abstract:
  We consider the electromagnetic production of positron in collision of heavy
nuclei, with the simultaneously produced electron captured by one of the
nuclei. This cross-section exceeds by about four orders of magnitude the
cross-section of $e^+ e^-$ production.


title:
Development of a strontium optical lattice clock for the SOC mission on
  the ISS

abstract:
  The ESA mission "Space Optical Clock" project aims at operating an optical
lattice clock on the ISS in approximately 2023. The scientific goals of the
mission are to perform tests of fundamental physics, to enable space-assisted
relativistic geodesy and to intercompare optical clocks on the ground using
microwave and optical links. The performance goal of the space clock is less
than $1 \times 10^{-17}$ uncertainty and $1 \times 10^{-15} {\tau}^{-1/2}$
instability. Within an EU-FP7-funded project, a strontium optical lattice clock
demonstrator has been developed. Goal performances are instability below $1
\times 10^{-15} {\tau}^{-1/2}$ and fractional inaccuracy $5 \times 10^{-17}$.
For the design of the clock, techniques and approaches suitable for later space
application are used, such as modular design, diode lasers, low power
consumption subunits, and compact dimensions. The Sr clock apparatus is fully
operational, and the clock transition in $^{88}$Sr was observed with linewidth
as small as 9 Hz.


title:
Excluded volume effect in flexible dendrimer systems: A self-consistent
  field theory

abstract:
  We have studied the conformational and scaling behaviors of a flexible
dendrimer immersed in athermal or good solvents. A self-consistent field theory
combined with a pre-averaged excluded volume potential representing the
two-body short-ranged interaction between the segments, was adopted to
calculate the density profile of various generations and branch points
thoroughly. Our calculation results support the "dense-core" model. We find the
conformation of the dendrimer is strongly stretched in the dense central
region, but much weakly stretched in the outer region where the segment density
profile is shoulder shaped. Both our self-consistent field theory calculation
and the Flory mean-field theory calculation give the same scaling law R
proportional to (GP)^0.2N^0.4, where G is the generation number of the
dendrimer, P is the spacer segment number, and N is the total segment number.
If we fix G, the scaling law is simplified to R proportional to P^0.6 in good
solvent.


title: Adaptive heat engine

abstract:
  A major limitations for many heat engines is that their functioning demands
on-line control, and/or an external fitting between environmental parameters
(e.g. temperatures of thermal baths) and internal parameters of the engine. We
study a model for an adaptive heat engine, where---due to feedback from the
functional part---the engine's structure adapts to given thermal baths. Hence
no on-line control and no external fitting are needed. The engine can employ
unknown resources, it can also adapt to results of its own functioning that
makes the bath temperatures closer. We determine thermodynamic costs of
adaptation and relate them to the prior information available about the
environment. We also discuss informational constraints on the
structure-function interaction that are necessary for adaptation.


title:
A pairwise approach to simultaneous onset/offset detection for singing
  voice using correntropy

abstract:
  In this paper, we propose a novelmethod to search for precise locations of
paired note onset and offset in a singing voice signal. In comparison with the
existing onset detection algorithms,our approach differs in two key respects.
First, we employ Correntropy, a generalized correlation function inspired from
Reyni's entropy, as a detection function to capture the instantaneous flux
while preserving insensitiveness to outliers. Next, a novel peak picking
algorithm is specially designed for this detection function. By calculating the
fitness of a pre-defined inverse hyperbolic kernel to a detection function, it
is possible to find an onset and its corresponding offset simultaneously.
Experimental results show that the proposed method achieves performance
significantly better than or comparable to other state-of-the-art techniques
for onset detection in singing voice.


title:
The stretched exponential behavior and its underlying dynamics. The
  phenomenological approach

abstract:
  We show that the anomalous diffusion equations with a fractional derivative
in the Caputo or Riesz sense are strictly related to the special convolution
properties of the L\'evy stable distributions which stem from the evolution
properties of stretched or compressed exponential function. The formal
solutions of these fractional differential equations are found by using the
evolution operator method where the evolution operator is presented as integral
transforms whose kernel is the Green function. Exact and explicit examples of
the solutions are reported and studied for various fractional order of
derivatives and different initial conditions.


title:
Adaptive Joint Learning of Compositional and Non-Compositional Phrase
  Embeddings

abstract:
  We present a novel method for jointly learning compositional and
non-compositional phrase embeddings by adaptively weighting both types of
embeddings using a compositionality scoring function. The scoring function is
used to quantify the level of compositionality of each phrase, and the
parameters of the function are jointly optimized with the objective for
learning phrase embeddings. In experiments, we apply the adaptive joint
learning method to the task of learning embeddings of transitive verb phrases,
and show that the compositionality scores have strong correlation with human
ratings for verb-object compositionality, substantially outperforming the
previous state of the art. Moreover, our embeddings improve upon the previous
best model on a transitive verb disambiguation task. We also show that a simple
ensemble technique further improves the results for both tasks.


title: Measuring the Accuracy of Linked Data Indices

abstract:
  Being based on Web technologies, Linked Data is distributed and decentralised
in its nature. Hence, for the purpose of finding relevant Linked Data on the
Web, search indices play an important role. Also for avoiding network
communication overhead and latency, applications rely on indices or caches over
Linked Data. These indices and caches are based on local copies of the original
data and, thereby, introduce redundancy. Furthermore, as changes at the
original Linked Data sources are not automatically propagated to the local
copies, there is a risk of having inaccurate indices and caches due to outdated
information. In this paper I discuss and compare methods for measuring the
accuracy of indices. I will present different measures which have been used in
related work and evaluate their advantages and disadvantages from a theoretic
point of view as well as from a practical point of view by analysing their
behaviour on real world data in an empirical experiment.


title: Simultaneous Gaussian quadrature for Angelesco systems

abstract:
  We investigate simultaneous Gaussian quadrature for two integrals of the same
function $f$ but on two disjoint intervals. The quadrature nodes are zeros of a
type II multiple orthogonal polynomial for an Angelesco system. We recall some
known results for the quadrature nodes and the quadrature weights and prove
some new results about the convergence of the quadrature formulas. Furthermore
we give some estimates of the quadrature weights. Our results are based on a
vector equilibrium problem in potential theory and weighted polynomial
approximation.


title:
Quantitative use of electron energy-loss spectroscopy Mo-M$_{2,3}$ edges
  for the study of molybdenum oxides

abstract:
  Because of the large energy separation between O-K and Mo-L$_{2,3}$ edges,
extracting precise and reliable chemical information from core-loss EELS
analyze of molybdenum oxides has always been a challenge. In this regard
Mo-M$_{2,3}$ edges represents an interesting alternative as they are situated
close to the O-K edges. They should allow thus the extraction of a wealth of
chemical information from the same spectra. However the main difficulty to
overcome in order to work properly with these edges is the delayed maxima of
the Mo-M$_{4,5}$ edges which hinders the automated background subtraction with
the usual inverse power low function. In this study we propose another
background subtraction method specifically designed to overcome this obstacle
and we apply it to the study of MoO3 and MoO2. We are able to show that
quantitative chemical information can be precisely and accurately determined
from the joined analyze of O-K and Mo-M$_{2,3}$ edges. In particular k-factors
are derived as a function of the integration window width and standard errors
close to 2% are reported. The possibility to discriminate the two oxides thanks
to chemical shifts and energy-loss near-edge structures is also investigated
and discussed. Furthermore the M$_3$/M$_2$ ratios are derived and are found to
be strongly dependent on the local chemical environment. This result is
confirmed by multiplet calculations for which the crystal field parameters have
been determined by ab initio calculations. The whole methodology as well as the
conclusions presented in this paper should be easily transposable to any
transitions metal oxides of the 4d family. This work should open a new and
easier way regarding the quantitative EELS analyses of these compounds.


title:
Optimal control and zero-sum stochastic differential game problems of
  mean-field type

abstract:
  We establish existence of nearly-optimal controls, conditions for existence
of an optimal control and a saddle-point for respectively a control problem and
zero-sum differential game associated with payoff functionals of mean-field
type, under dynamics driven by weak solutions of stochastic differential
equations of mean-field type.


title:
Dual differential polarimetry. A technique to recover polarimetric
  information from dual polarization observations

abstract:
  Current mm/submm interferometers, like the Atacama Large mm/submm Array
(ALMA), use receivers that register the sky signal in a linear polarization
basis. In the case of observations performed in full-polarization mode (where
the cross-correlations are computed among all the polarization channels) it is
possible to reconstruct the full-polarization brightness distribution of the
observed sources, as long as a proper calibration of delay offsets and leakage
among polarization channels can be performed. Observations of calibrators,
preferably with some linear polarization, with a good parallactic angle
coverage are usually needed for such a calibration. In principle,
dual-polarization observations only allow us to recover the Stokes $I$
intensity distribution of the sources, regardless of the parallactic angle
coverage of the observations. In this paper, we present a novel technique of
dual differential polarimetry that makes it possible to obtain information
related to the full-polarization brightness distribution of the observed
sources from dual-polarization observations. This technique is inspired in the
Earth-rotation polarization synthesis and can be applied even to sources with
complex structures.


title: Some remarks on stable almost complex structures on manifolds

abstract:
  Let $X$ be an $(8k+i)$-dimensional pathwise connected $CW$-complex with $i=1$
or $2$ and $k\ge0$, $\xi$ be a real vector bundle over $X$. Suppose that $\xi$
admits a stable complex structure over the $8k$-skeleton of $X$. Then we get
that $\xi$ admits a stable complex structure over $X$ if the Steenrod square
$$\mathrm{Sq}^{2}\colon H^{8k-1}(X;\mathbb{Z}/2)\rightarrow
H^{8k+1}(X;\mathbb{Z}/2)$$ is surjective. As an application, let $M$ be a
$10$-dimensional manifold with no $2$-torsion in $H_{i}(M;\mathbb{Z})$ for
$i=1,2,3$, and no $3$-torsion in $H_{1}(M;\mathbb{Z})$. Suppose that the
Steenrod square $$\mathrm{Sq}^{2}\colon H^{7}(M;\mathbb{Z}/2)\rightarrow
H^{9}(M;\mathbb{Z}/2)$$ is surjective. Then the necessary and sufficient
conditions for the existence of a stable almost complex structure on $M$ are
given in terms of the cohomology ring and characteristic classes of $M$.


title:
Electric control of inverted gap and hybridization gap in type II
  InAs/GaSb quantum wells

abstract:
  The quantum spin Hall effect has been predicted theoretically and observed
experimentally in InAs/GaSb quantum wells as a result of inverted band
structures, for which electron bands in InAs layers are below heavy hole bands
in GaSb layers in energy. The hybridization between electron bands and heavy
hole bands leads to a hybridization gap away from k=0. A recent puzzling
observation in experiments is that when the system is tuned to more inverted
regime by a gate voltage (a larger inverted gap at k=0), the hybridization gap
decreases. Motivated by this experiment, we explore the dependence of
hybridization gap as a function of external electric fields based on the
eight-band Kane model. We identify two regimes when varying electric fields:
(1) both inverted and hybridization gaps increase and (2) inverted gap
increases while hybridization gap decreases. Based on the effective model, we
find that light-hole bands in GaSb layers play an important role in determining
hybridization gap. In addition, a large external electric field can induce a
strong Rashba splitting and also influence hybridization gap.


title: Tree-to-Sequence Attentional Neural Machine Translation

abstract:
  Most of the existing Neural Machine Translation (NMT) models focus on the
conversion of sequential data and do not directly use syntactic information. We
propose a novel end-to-end syntactic NMT model, extending a
sequence-to-sequence model with the source-side phrase structure. Our model has
an attention mechanism that enables the decoder to generate a translated word
while softly aligning it with phrases as well as words of the source sentence.
Experimental results on the WAT'15 English-to-Japanese dataset demonstrate that
our proposed model considerably outperforms sequence-to-sequence attentional
NMT models and compares favorably with the state-of-the-art tree-to-string SMT
system.


title:
Improving Hypernymy Detection with an Integrated Path-based and
  Distributional Method

abstract:
  Detecting hypernymy relations is a key task in NLP, which is addressed in the
literature using two complementary approaches. Distributional methods, whose
supervised variants are the current best performers, and path-based methods,
which received less research attention. We suggest an improved path-based
algorithm, in which the dependency paths are encoded using a recurrent neural
network, that achieves results comparable to distributional methods. We then
extend the approach to integrate both path-based and distributional signals,
significantly improving upon the state-of-the-art on this task.


title: Geometric Hitting Set for Segments of Few Orientations

abstract:
  We study several natural instances of the geometric hitting set problem for
input consisting of sets of line segments (and rays, lines) having a small
number of distinct slopes. These problems model path monitoring (e.g., on road
networks) using the fewest sensors (the "hitting points"). We give
approximation algorithms for cases including (i) lines of 3 slopes in the
plane, (ii) vertical lines and horizontal segments, (iii) pairs of
horizontal/vertical segments. We give hardness and hardness of approximation
results for these problems. We prove that the hitting set problem for vertical
lines and horizontal rays is polynomially solvable.


title: Deep Shading: Convolutional Neural Networks for Screen-Space Shading

abstract:
  In computer vision, convolutional neural networks (CNNs) have recently
achieved new levels of performance for several inverse problems where RGB pixel
appearance is mapped to attributes such as positions, normals or reflectance.
In computer graphics, screen-space shading has recently increased the visual
quality in interactive image synthesis, where per-pixel attributes such as
positions, normals or reflectance of a virtual 3D scene are converted into RGB
pixel appearance, enabling effects like ambient occlusion, indirect light,
scattering, depth-of-field, motion blur, or anti-aliasing. In this paper we
consider the diagonal problem: synthesizing appearance from given per-pixel
attributes using a CNN. The resulting Deep Shading simulates various
screen-space effects at competitive quality and speed while not being
programmed by human experts but learned from example images.


title:
Smoothed Temporal Variance Spectrum: weak line profile variations and
  NRP diagnostics

abstract:
  We describe the version of the Temporal Variance Spectrum (TVS, Fullerton,
Gies & Bolton 1996) method with pre-smoothed line profile (smoothed Temporal
Variance Spectrum, smTVS). This method introduced by Kholtygin et al. (2003)
can be used to detect the ultra weak variations of the line profile even for
very noisy stellar spectra. We also describe how to estimate the mode of the
non-radial pulsations (NRP) using the TVS and smTVS with different time spans.
The influence of the rotational modulation of the line profile on the TVS is
considered. The analysis of the contribution of NRP and rotational modulation
in the global TVS is studied.


title:
Kra\'skiewicz-Pragacz modules and Pieri and dual Pieri rules for
  Schubert polynomials

abstract:
  In their 1987 paper Kra\'skiewicz and Pragacz defined certain modules, which
we call KP modules, over the upper triangular Lie algebra whose characters are
Schubert polynomials. In a previous work the author showed that the tensor
product of KP modules always has a KP filtration, i.e. a filtration whose each
successive quotients are isomorphic to KP modules. In this paper we explicitly
construct such filtrations for certain special cases of these tensor product
modules, namely $\mathcal{S}_w \otimes S^d(K^i)$ and $\mathcal{S}_w \otimes
\bigwedge^d(K^i)$, corresponding to Pieri and dual Pieri rules for Schubert
polynomials.


title:
Characteristics study of projectiles lightest fragment for 84Kr36 -
  emulsion interaction at around 1 A GeV

abstract:
  The present article significantly investigated projectiles lightest fragments
(proton) multiplicity distribution and probability distribution with 84Kr36
emulsion collision at around 1 A GeV. The multiplicity and normalized
multiplicity of projectiles lightest fragments (proton) is correlated with the
compound particles, shower particles, black particles, grey particles, helium
fragments particles and heavily ionizing charged particles. It is found that
projectiles lightest fragments (proton) are strongly correlated with compound
particles and shower particles rather than other particles and the average
multiplicity of projectiles lightest fragments (proton) increases with
increasing compound, shower and heavy ionizing particles. Normalized
projectiles lightest fragments (proton) are strongly correlated with compound
particles, shower particles and heavy ionizing charge particles. The
multiplicity distribution of the projectiles lightest fragments (proton)
emitted in the 84Kr36 + emulsion interaction at around 1 A GeV with different
target has well explained by KNO scaling. The mean multiplicity of projectiles
lightest fragments (proton) depends on the mass number of the projectile and
does not significantly dependent of the projectile energy. The mean
multiplicity projectiles lightest fragment (proton) increases with increasing
the target mass number.


title:
On the Existence of Absolutely Maximally Entangled States of Minimal
  Support

abstract:
  In this paper we prove that no absolutely maximally entangled, AME, state
with minimal support exists with 7 sites and 5 levels.
  General AME states are pure multipartite states that, when reduced to half or
less of the sites, the maximum entropy mixed state is obtained. They have found
applications in teleportation and quantum secret sharing, and finding
conditions for their existence is a well known open problem. We consider the
version of this problem for minimally supported AME states. We single out known
both sufficient and necessary conditions in that case. From our negative
result, we show that the necessary condition is not sufficient. The proof uses
a recent result on the theory of general, nonlinear, classical codes.


title:
Towards Coordinated Bandwidth Adaptations for Hundred-Scale 3D
  Tele-Immersive Systems

abstract:
  3D tele-immersion improves the state of collaboration among geographically
distributed participants. Unlike the traditional 2D videos, a 3D tele-immersive
system employs multiple 3D cameras based in each physical site to cover a much
larger field of view, generating a very large amount of stream data. One of the
major challenges is how to efficiently transmit these bulky 3D streaming data
to bandwidth-constrained sites. In this paper, we study an adaptive Human
Visual System (HVS) -compliant bandwidth management framework for efficient
delivery of hundred-scale streams produced from distributed 3D tele-immersive
sites to a receiver site with limited bandwidth budget. Our adaptation
framework exploits the semantics link of HVS with multiple 3D streams in the 3D
tele-immersive environment. We developed TELEVIS, a visual simulation tool to
showcase a HVS-aware tele-immersive system for realistic cases. Our evaluation
results show that the proposed adaptation can improve the total quality per
unit of bandwidth used to deliver streams in 3D tele-immersive systems.


title: Integrable actions and quantum subgroups

abstract:
  We study homomorphisms of locally compact quantum groups from the point of
view of integrability of the associated action. For a given homomorphism of
quantum groups $\Pi\colon\mathbb{H}\to\mathbb{G}$ we introduce quantum groups
$\mathbb{H}/\!\ker{\Pi}$ and $\overline{\mathrm{im}\,\Pi}$ corresponding to the
classical quotient by kernel and closure of image. We show that if the action
of $\mathbb{H}$ on $\mathbb{G}$ associated to $\Pi$ is integrable then
$\mathbb{H}/\!\ker\Pi\cong\overline{\mathrm{im}\,\Pi}$ and characterize such
$\Pi$. As a particular case we consider an injective continuous homomorphism
$\Pi\colon{H}\to{G}$ between locally compact groups $H$ and $G$. Then $\Pi$
yields an integrable action of $H$ on $L^\infty\;\!\!(G)$ if and only if its
image is closed and $\Pi$ is a homeomorphism of $H$ onto $\mathrm{im}\,\Pi$.
  We also give characterizations of open quantum subgroups and of compact
quantum subgroups in terms of integrability and show that a closed quantum
subgroup always gives rise to an integrable action. Moreover we prove that
quantum subgroups closed in the sense of Woronowicz whose associated
homomorphism of quantum groups yields an integrable action are closed in the
sense of Vaes.


abstract:
  In this paper, we study Toeplitz operators on the weighted harmonic Bergman
spaces with nonnegative symbols, the weights we choose here are Muckenhoupt A_2
weights. Results obtained include characterizations of bounded Toeplitz
operators, compact Toeplitz operators, invertible Toeplitz operators and
Toeplitz operators in the Schatten classes.


title:
Limit on the production of a new vector boson in $\mathrm{e^+
  e^-}\rightarrow {\rm U}\gamma$, U$\rightarrow \pi^+\pi^-$ with the KLOE
  experiment

abstract:
  The recent interest in a light gauge boson in the framework of an extra U(1)
symmetry motivates searches in the mass range below 1 GeV.
  We present a search for such a particle, the dark photon, in ${\rm e^+
e^-}\rightarrow {\rm U}\gamma$, U$\rightarrow \pi^+\pi^-$ based on 28 million
$\mathrm{e^+ e^-} \rightarrow \pi^+ \pi^-\gamma$ events collected at DA$\Phi$NE
by the KLOE experiment. The $\pi^+ \pi^-$ production by initial-state radiation
compensates for a loss of sensitivity of previous KLOE ${\rm U} \rightarrow
\mathrm{e^+ e^-}$, $\mu^+\mu^-$ searches due to the small branching ratios in
the $\rho-\omega$ resonance region. We found no evidence for a signal and set a
limit at 90\% CL on the mixing strength between the photon and the dark photon,
$\varepsilon^2$, in the U mass range between $527$ and $987$~MeV. Above 700 MeV
this new limit is more stringent than previous ones.


title: Connectedness of self-affine sets with product digit sets

abstract:
  Let $T(A,\mathcal{D})$ be a self-affine set generated by an expanding matrix
$A=\left[\begin{array}{rr} p & 0\cr -a & q \end{array}\right]$ and a product
digit set $\mathcal{D}=\{0,1,\dots,m-1\}\times \{0,1,\dots,n-1\}$. We provide a
necessary and sufficient condition for the $T(A,\mathcal{D})$ to be connected,
which generalizes the known results.


title: Fractional perimeter from a fractal perspective

abstract:
  Following \cite{Visintin}, we exploit the fractional perimeter of a set to
give a definition of fractal dimension for its measure theoretic boundary. We
calculate the fractal dimension of sets which can be defined in a recursive way
and we give some examples of this kind of sets, explaining how to construct
them starting from well known self-similar fractals. In particular, we show
that in the case of the von Koch snowflake $S\subset\mathbb R^2$ this fractal
dimension coincides with the Minkowski dimension, namely \begin{equation*}
P_s(S)<\infty\qquad\Longleftrightarrow\qquad
s\in\Big(0,2-\frac{\log4}{\log3}\Big). \end{equation*} We also study the
asymptotics as $s\to1^-$ of the fractional perimeter of a set having finite
(classical) perimeter.


title: Local Constants for Galois Representations - Some Explicit Results

abstract:
  We can associate local constant to every continuous finite dimensional
complex representation of the absolute Galois group $G_F$ of a non-archimedean
local field $F/\mathbb{Q}_p$ by Deligne and Langlands. To give explicit formula
of local constant of a representation, we need to compute $\lambda$-functions
explicitly. In this thesis we compute $\lambda_{K/F}$ explicitly, where $K/F$
is a finite degree Galois extension of a non-archimedean local field $F$,
except when $K/F$ is a wildly ramified quadratic extension with
$F\ne\mathbb{Q}_2$.
  Then by using this $\lambda$-function computation, in general, we give an
invariant formula of local constant of finite dimensional Heisenberg
representations of the absolute Galois group $G_F$ of a non-archimedean local
field $F$. But for explicit invariant formula of local constant for a
Heisenberg representation, we should have information about the dimension of a
Heisenberg representation and the arithmetic description of the determinant of
a Heisenberg representation. In this thesis, we give explicit arithmetic
description of the determinant of Heisenberg representation.
  We also construct all Heisenberg representations of dimensions prime to $p$,
and study their various properties. By using $\lambda$-function computation and
arithmetic description of the determinant of Heisenberg representations, we
give an invariant formula of local constant for a Heisenberg representation of
dimension prime to $p$.


title: IMPi: An interactive homology modeling pipeline

abstract:
  Summary: The development of automated servers to predict the
three-dimensional structure of proteins has seen much progress over the years.
These servers make modeling simpler, but largely exclude users from the
process. We present an Interactive Modeling Pipeline (IMPi) for homology
modeling. The pipeline simplifies the modeling process and reduces the workload
required by the user, while still allowing engagement from the user during
every step. Default parameters are given for each step, which can either be
modified or supplemented with additional external input. As such, it has been
designed for users of varying levels of experience with homology modeling.
  Availability and implementation: The IMPi site is free for non-commercial use
and can be accessed at https://impi.rubi.ru.ac.za.
  Supplementary information: Documentation available at
https://impi.rubi.ru.ac.za/#documentation.


title:
Deflation of the cosmological constant associated with inflation and
  dark energy

abstract:
  In order to solve the fine-tuning problem of the cosmological constant, we
propose a simple model with the vacuum energy non-minimally coupled to the
inflaton field. In this model, the vacuum energy decays to the inflaton during
pre-inflation and inflation eras, so that the cosmological constant effectively
deflates from the Planck mass scale to a much smaller one after inflation and
plays the role of dark energy in the late-time of the universe. We show that
our deflationary scenario is applicable to arbitrary slow-roll inflation
models. We also take two specific inflation potentials to illustrate our
results.


title:
Slipping Magnetic Reconnection, Chromospheric Evaporation, Implosion,
  and Precursors in the 2014 September 10 X1.6-Class Solar Flare

abstract:
  We investigate the occurrence of slipping magnetic reconnection,
chromospheric evaporation, and coronal loop dynamics in the 2014 September 10
X-class flare. The slipping reconnection is found to be present throughout the
flare from its early phase. Flare loops are seen to slip in opposite directions
towards both ends of the ribbons. Velocities of 20--40 km\,s$^{-1}$ are found
within time windows where the slipping is well resolved. The warm coronal loops
exhibit expanding and contracting motions that are interpreted as displacements
due to the growing flux rope that subsequently erupts. This flux rope existed
and erupted before the onset of apparent coronal implosion. This indicates that
the energy release proceeds by slipping reconnection and not via coronal
implosion. The slipping reconnection leads to changes in the geometry of the
observed structures at the \textit{IRIS} slit position, from flare loop top to
the footpoints in the ribbons. This results in variations of the observed
velocities of chromospheric evaporation in the early flare phase. Finally, it
is found that the precursor signatures including localized EUV brightenings as
well as non-thermal X-ray emission are signatures of the flare itself,
progressing from the early phase towards the impulsive phase, with the
tether-cutting being provided by the slipping reconnection. The dynamics of
both the flare and outlying coronal loops is found to be consistent with the
predictions of the standard solar flare model in 3D.


title:
Large scale near-duplicate image retrieval using Triples of Adjacent
  Ranked Features (TARF) with embedded geometric information

abstract:
  Most approaches to large-scale image retrieval are based on the construction
of the inverted index of local image descriptors or visual words. A search in
such an index usually results in a large number of candidates. This list of
candidates is then re-ranked with the help of a geometric verification, using a
RANSAC algorithm, for example. In this paper we propose a feature
representation, which is built as a combination of three local descriptors. It
allows one to significantly decrease the number of false matches and to shorten
the list of candidates after the initial search in the inverted index. This
combination of local descriptors is both reproducible and highly
discriminative, and thus can be efficiently used for large-scale near-duplicate
image retrieval.


title: Entire unbounded constant mean curvature Killing graphs

abstract:
  In this paper, we provided conditions for an entire constant mean curvature
Killing graph lying inside a possible unbounded region to be necessarily a
slice.


title:
Slater to Mott crossover in the metal to insulator transition of
  Nd2Ir2O7

abstract:
  We present an angle-resolved photoemission study of the electronic structure
of the three-dimensional pyrochlore iridate Nd2Ir2O7 through its magnetic
metal-insulator transition. Our data reveal that metallic Nd2Ir2O7 has a
quadratic band, touching the Fermi level at the Gamma point, similarly to that
of Pr2Ir2O7. The Fermi node state is, therefore, a common feature of the
metallic phase of the pyrochlore iridates. Upon cooling below the transition
temperature, this compound exhibits a gap opening with an energy shift of
quasiparticle peaks like a band gap insulator. The quasiparticle peaks are
strongly suppressed, however, with further decrease of temperature, and
eventually vanish at the lowest temperature, leaving a non-dispersive flat band
lacking long-lived electrons. We thereby identify a remarkable crossover from
Slater to Mott insulators with decreasing temperature. These observations
explain the puzzling absence of Weyl points in this material, despite its
proximity to the zero temperature metal-insulator transition.


title: Population III stars around the Milky Way

abstract:
  We explore the possibility of observing Population III (Pop~III) stars, born
of the primordial gas.
  Pop~III stars with masses below $0.8 M_\odot$ should survive to date though
are not observed yet, but the existence of stars with low metallicity as
[Fe/H]$ < -5$ in the Milky Way halo suggests the surface pollution of Pop~III
stars with accreted metals from the interstellar gas after birth. In this
paper, we investigate the runaway of Pop~III stars from their host mini-halos,
considering the ejection of secondary members from binary systems when their
massive primaries explode as supernovae.
  These stars save them from the surface pollution.
  By computing the star formation and chemical evolution along with the
hierarchical structure formation based on the extended Press--Schechter merger
trees, we demonstrate that several hundreds to tens of thousands of low-mass
Pop~III stars escape from the building blocks of the Milky Way.
  The second and later generations of extremely metal-poor (EMP) stars are also
escaped from the mini-halos.
  We discuss the spatial distributions of these escaped stars by evaluating the
distances between the mini-halos in the branches of merger trees under the
spherical collapse model of dark matter halos.
  It is demonstrated that the escaped stars distribute beyond the stellar halo
with a density profile close to the dark matter halo, while the Pop~III stars
are slightly more centrally concentrated .
  Some escaped stars leave the Milky Way and spread into the intergalactic
space.
  Based on the results, we discuss the feasibility of observing the Pop~III
stars with the pristine surface abundance.


title: Laser-Induced Spallation of Microsphere Monolayers

abstract:
  The detachment of a semi-ordered monolayer of polystyrene microspheres
adhered to an aluminum-coated glass substrate is studied using a laser-induced
spallation technique. The microsphere-substrate adhesion force is estimated
from substrate surface displacement measurements obtained using optical
interferometry, and a rigid-body model that accounts for the inertia of the
microspheres. The estimated adhesion force is compared with estimates obtained
from interferometric measurement of the out-of-plane microsphere contact
resonance. Reasonable agreement is found between the two experiments. Scanning
electron microscope images of detached monolayer regions reveal a unique
morphology, namely, partially detached monolayer flakes composed of single
hexagonal close packed crystalline domains. This work contributes to an
improved understanding of microsphere adhesion and demonstrates a unique
monolayer delamination morphology.


title:
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image
  Segmentation

abstract:
  We introduce a new loss function for the weakly-supervised training of
semantic image segmentation models based on three guiding principles: to seed
with weak localization cues, to expand objects based on the information about
which classes can occur in an image, and to constrain the segmentations to
coincide with object boundaries. We show experimentally that training a deep
convolutional neural network using the proposed loss function leads to
substantially better segmentations than previous state-of-the-art methods on
the challenging PASCAL VOC 2012 dataset. We furthermore give insight into the
working mechanism of our method by a detailed experimental study that
illustrates how the segmentation quality is affected by each term of the
proposed loss function as well as their combinations.


title: Some Aspects of the Wiener Index for Sun Graphs

abstract:
  The Wiener index $W(G)$ is the sum of distances of all pairs of vertices of
the graph $G$. The Wiener polarity index $W_{p}(G)$ of a graph $G$ is the
number of unordered pairs of vertices $u$ and $v$ of $G$ such that the distance
$d_{G}(u,v)$ between $u$ and $v$ is $3$. In this paper the Wiener and the
Wiener polarity indices of sun graphs are computed. A relationship between
those indices with some other topological indices are presented. Finally, we
find the Hosoya (Wiener) polynomial for sun graphs.


title:
The Kato--Temple inequality and eigenvalue concentration with
  applications to graph inference

abstract:
  We present an adaptation of the Kato--Temple inequality for bounding
perturbations of eigenvalues with applications to statistical inference for
random graphs, specifically hypothesis testing and change-point detection. We
obtain explicit high-probability bounds for the individual distances between
certain signal eigenvalues of a graph's adjacency matrix and the corresponding
eigenvalues of the model's edge probability matrix, even when the latter
eigenvalues have multiplicity. Our results extend more broadly to the
perturbation of singular values in the presence of quite general random matrix
noise.


title:
Noncommutative extensions of elliptic integrable Euler-Arnold tops and
  Painleve VI equation

abstract:
  In this paper we suggest generalizations of elliptic integrable tops to
matrix-valued variables. Our consideration is based on $R$-matrix description
which provides Lax pairs in terms of quantum and classical $R$-matrices. First,
we prove that for relativistic (and non-relativistic) tops such Lax pairs with
spectral parameter follow from the associative Yang-Baxter equation and its
degenerations. Then we proceed to matrix extensions of the models and find out
that some additional constraints are required for their construction. We
describe a matrix version of ${\mathbb Z}_2$ reduced elliptic top and verify
that the latter constraints are fulfilled in this case. The construction of
matrix extensions is naturally generalized to the monodromy preserving
equation. In this way we get matrix extensions of the Painlev\'e VI equation
and its multidimensional analogues written in the form of non-autonomous
elliptic tops. Finally, it is mentioned that the matrix valued variables can be
replaced by elements of noncommutative associative algebra. In the end of the
paper we also describe special elliptic Gaudin models which can be considered
as matrix extensions of the (${\mathbb Z}_2$ reduced) elliptic top.


title: On the Type IIb solutions to mean curvature flow

abstract:
  In this paper we study the Type IIb mean curvature flow. We first prove that
if the convex entire graph $(y,u(|y|))$ over $\mathbb{R}^n$, $n\geq 2$,
satisfying there exist positive constants $\epsilon$, $c$ and $N$ such that $
u'(r)\geq c r^{\epsilon} $ for $r\geq N$, the longtime solution to mean
curvature flow with initial data $(y,u(|y|))$ must be Type IIb. We also study
the asymptotic behavior of Type IIb mean curvature flow and show that the limit
of suitable rescaling sequence for mean-convex Type IIb mean curvature flow
satisfying $\delta$-Andrews' noncollapsing condition is translating soliton.


title:
Fixed point proportions for Galois groups of non-geometric iterated
  extensions

abstract:
  Given a map $\varphi:\mathbb{P}^1\rightarrow \mathbb{P}^1$ of degree greater
than 1 defined over a number field $k$, one can define a map
$\varphi_\mathfrak{p}:\mathbb{P}^1(\mathfrak{o}_k/\mathfrak{p})\rightarrow
\mathbb{P}^1(\mathfrak{o}_k/\mathfrak{p})$ for each prime $\mathfrak{p}$ of
good reduction, induced by reduction modulo $\mathfrak{p}$. It has been shown
that for a typical $\varphi$ the proportion of periodic points of
$\varphi_\mathfrak{p}$ should tend to $0$ as
$|\mathbb{P}^1(\mathfrak{o}_k/\mathfrak{p})|$ grows. In this paper, we extend
previous results to include a weaker set of sufficient conditions under which
this property holds. We are also able to show that these conditions are
necessary for certain families of functions, for example, functions of the form
$\varphi(x)=x^d+c$, where $0$ is not a preperiodic point of this map. We study
the proportion of periodic points by looking at the fixed point proportion of
the Galois groups of certain extensions associated to iterates of the map.


title:
Continuity of attractors for a family of $C^1$ perturbations of the
  square

abstract:
  We consider here the family of semilinear parabolic problems
\begin{equation*} \begin{array}{rcl} \left\{ \begin{array}{rcl}
u_t(x,t)&=&\Delta u(x,t) -au(x,t) + f(u(x,t)) ,\,\,\ x \in \Omega_\epsilon
\,\,\,\mbox{and}\,\,\,\,\,\,t>0\,, \\ \displaystyle\frac{\partial u}{\partial
N}(x,t)&=&g(u(x,t)), \,\, x \in \partial\Omega_\epsilon
\,\,\,\mbox{and}\,\,\,\,\,\,t>0\,, \end{array} \right. \end{array}
\end{equation*} where $ {\Omega} $ is the unit square,
$\Omega_{\epsilon}=h_{\epsilon}(\Omega)$ and $h_{\epsilon}$ is a family of
diffeomorphisms converging to the identity in the $C^1$-norm. We show that the
problem is well posed for $\epsilon>0$ sufficiently small in a suitable phase
space, the associated semigroup has a global attractor $\mathcal{A}_{\epsilon}$
and the family $\{\mathcal{A}_{\epsilon}\}$ is continuous at $\epsilon = 0$.


title:
A characterization of nilpotent orbit closures among symplectic
  singularities

abstract:
  We prove that a conical symplectic variety with maximal weight 1 is
isomorphic to one of the following:
  (i) an affine space with the standard symplectic form
  (ii) a nilpotent orbit closure of a complex semisimple Lie algebra with the
Kirillov-Kostant form.


title: Connections in sub-Riemannian geometry of parallelizable distributions

abstract:
  The notion of a parallelizable distribution has been introduced and
investigated. A non-integrable parallelizable distribution carries a natural
sub-Riemannian structure. The geometry of this structure has been studied from
the bi-viewpoint of absolute parallelism geometry and sub-Riemannian geometry.
Two remarkable linear connections have been constructed on a sub-Riemannian
parallelizable distribution, namely, the Weitzenb\"ock connection and the
sub-Riemannian connection. The obtained results have been applied to two
concrete examples: the spheres $S^3$ and $S^7$.


title:
Velocity Amplitudes in Global Convection Simulations: The Role of the
  Prandtl Number and Near-Surface Driving

abstract:
  Several lines of evidence suggest that the velocity amplitude in global
simulations of solar convection, U, may be systematically over-estimated.
Motivated by these recent results, we explore the factors that determine U and
we consider how these might scale to solar parameter regimes. To this end, we
decrease the thermal diffusivity $\kappa$ along two paths in parameter space.
If the kinematic viscosity $\nu$ is decreased proportionally with $\kappa$
(fixing the Prandtl number $P_r = \nu/\kappa$), we find that U increases but
asymptotes toward a constant value, as found by Featherstone & Hindman (2016).
However, if $\nu$ is held fixed while decreasing $\kappa$ (increasing $P_r$),
we find that U systematically decreases. We attribute this to an enhancement of
the thermal content of downflow plumes, which allows them to carry the solar
luminosity with slower flow speeds. We contrast this with the case of
Rayleigh-Benard convection which is not subject to this luminosity constraint.
This dramatic difference in behavior for the two paths in parameter space
(fixed $P_r$ or fixed $\nu$) persists whether the heat transport by unresolved,
near-surface convection is modeled as a thermal conduction or as a fixed flux.
The results suggest that if solar convection can operate in a high-$P_r$
regime, then this might effectively limit the velocity amplitude. Small-scale
magnetism is a possible source of enhanced viscosity that may serve to achieve
this high-$P_r$ regime.


title:
Crosstalk-insensitive method for simultaneously coupling multiple pairs
  of resonators

abstract:
  In a circuit consisting of two or more resonators, the inter-cavity crosstalk
is inevitable, which could create some problems, such as degrading the
performance of quantum operations and the fidelity of various quantum states.
The focus of this work is to propose a crosstalk-insensitive method for
simultaneously coupling multiple pairs of resonators, which is important in
large-scale quantum information processing and communication in a network
consisting of resonators or cavities. In this work, we consider 2N resonators
of different frequencies, which are coupled to a three-level quantum system
(qutrit). By applying a strong pulse to the coupler qutrit, we show that an
effective Hamiltonian can be constructed for simultaneously coupling multiple
pairs of resonators.~The main advantage of this proposal is that the effect of
inter-resonator crosstalks is greatly suppressed by using resonators of
different frequencies. In addition, by employing the qutrit-resonator
dispersive interaction, the intermediate higher-energy level of the qutrit is
virtually excited and thus decoherence from this level is suppressed. This
effective Hamiltonian can be applied to implement quantum operations with
photonic qubits distributed in different resonators. As one application of this
Hamiltonian, we show how to simultaneously generate multiple EPR pairs of
photonic qubits distributed in 2N resonators. Numerical simulations show that
it is feasible to prepare two high-fidelity EPR photonic pairs using a setup of
four one-dimensional transmission line resonators coupled to a superconducting
flux qutrit with current circuit QED technology.


title: Better bounds for coalescing-branching random walks

abstract:
  Coalescing-branching random walks, or {\em cobra walks} for short, are a
natural variant of random walks on graphs that can model the spread of disease
through contacts or the spread of information in networks. In a $k$-cobra walk,
at each time step a subset of the vertices are active; each active vertex
chooses $k$ random neighbors (sampled independently and uniformly with
replacement) that become active at the next step, and these are the only active
vertices at the next step. A natural quantity to study for cobra walks is the
cover time, which corresponds to the expected time when all nodes have become
infected or received the disseminated information.
  In this work, we extend previous results for cobra walks in multiple ways. We
show that the cover time for the 2-cobra walk on $[0,n]^d$ is $O(n)$ (where the
order notation hides constant factors that depend on $d$); previous work had
shown the cover time was $O(n \cdot polylog(n))$. We show that the cover time
for a 2-cobra walk on an $n$-vertex $d$-regular graph with conductance $\phi_G$
is $O(\phi_G^{-2} \log^2 n)$, significantly generalizing a previous result that
held only for expander graphs with sufficiently high expansion. And finally we
show that the cover time for a 2-cobra walk on a graph with $n$ vertices is
always $O(n^{11/4} \log n)$; this is the first result showing that the bound of
$\Theta(n^3)$ for the worst-case cover time for random walks can be beaten
using 2-cobra walks.


title: Inter-Paradigm Translation of Process Models using Simulation and Mining

abstract:
  Process modeling is usually done using imperative modeling languages like
BPMN or EPCs. In order to cope with the complexity of human-centric and
flexible business processes several declarative process modeling languages
(DPMLs) have been developed during the last years. DPMLs allow for the
specification of constraints that restrict execution flows. They differ widely
in terms of their level of expressiveness and tool support. Furthermore,
research has shown that the understandability of declarative process models is
rather low. Since there are applications for both classes of process modeling
languages, there arises a need for an automatic translation of process models
from one language into another. Our approach is based upon well-established
methodologies in process management for process model simulation and process
mining without requiring the specification of model transformation rules. In
this paper, we present the technique in principle and evaluate it by
transforming process models between two exemplary process modeling languages.


title: How Transferable are Neural Networks in NLP Applications?

abstract:
  Transfer learning is aimed to make use of valuable knowledge in a source
domain to help model performance in a target domain. It is particularly
important to neural networks, which are very likely to be overfitting. In some
fields like image processing, many studies have shown the effectiveness of
neural network-based transfer learning. For neural NLP, however, existing
studies have only casually applied transfer learning, and conclusions are
inconsistent. In this paper, we conduct systematic case studies and provide an
illuminating picture on the transferability of neural networks in NLP.


title:
Quantum Superpositions and the Representation of Physical Reality Beyond
  Measurement Outcomes and Mathematical Structures

abstract:
  In this paper we intend to discuss the importance of providing a physical
representation of quantum superpositions which goes beyond the mere reference
to mathematical structures and measurement outcomes. This proposal goes in the
opposite direction to the project present in orthodox contemporary philosophy
of physics which attempts to "bridge the gap" between the quantum formalism and
common sense "classical reality" --precluding, right from the start, the
possibility of interpreting quantum superpositions through non-classical
notions. We will argue that in order to restate the problem of interpretation
of quantum mechanics in truly ontological terms we require a radical revision
of the problems and definitions addressed within the orthodox literature. On
the one hand, we will discuss the need of providing a formal redefinition of
superpositions which captures explicitly their contextual character. On the
other hand, we will attempt to replace the focus on the measurement problem,
which concentrates on the justification of measurement outcomes from "weird"
superposed states, and introduce the superposition problem which focuses
instead on the conceptual representation of superpositions themselves. In this
respect, after presenting three necessary conditions for objective physical
representation, we will provide arguments which show why the classical
(actualist) representation of physics faces severe difficulties to solve the
superposition problem. Finally, we will also argue that, if we are willing to
abandon the (metaphysical) presupposition according to which 'Actuality =
Reality', then there is plenty of room to construct a conceptual representation
for quantum superpositions.


title:
Improved Protocols and Hardness Results for the Two-Player
  Cryptogenography Problem

abstract:
  The cryptogenography problem, introduced by Brody, Jakobsen, Scheder, and
Winkler (ITCS 2014), is to collaboratively leak a piece of information known to
only one member of a group (i)~without revealing who was the origin of this
information and (ii)~without any private communication, neither during the
process nor before. Despite several deep structural results, even the smallest
case of leaking one bit of information present at one of two players is not
well understood. Brody et al.\ gave a 2-round protocol enabling the two players
to succeed with probability $1/3$ and showed the hardness result that no
protocol can give a success probability of more than~$3/8$.
  In this work, we show that neither bound is tight. Our new hardness result,
obtained by a different application of the concavity method used also in the
previous work, states that a success probability better than 0.3672 is not
possible. Using both theoretical and numerical approaches, we improve the lower
bound to $0.3384$, that is, give a protocol leading to this success
probability. To ease the design of new protocols, we prove an equivalent
formulation of the cryptogenography problem as solitaire vector splitting game.
Via an automated game tree search, we find good strategies for this game. We
then translate the splits that occurred in this strategy into inequalities
relating position values and use an LP solver to find an optimal solution for
these inequalities. This gives slightly better game values, but more
importantly, it gives a more compact representation of the protocol and a way
to easily verify the claimed quality of the protocol.
  These improved bounds, as well as the large sizes and depths of the improved
protocols we find, suggests that finding good protocols for the
cryptogenography problem as well as understanding their structure are harder
than what the simple problem formulation suggests.


title: Stochastic evolutionary dynamics of minimum-effort coordination games

abstract:
  The minimum-effort coordination game, having potentially important
implications in both evolutionary biology and sociology, draws recently more
attention for the fact that human behavior in this social dilemma is often
inconsistent with the predictions of classic game theory. In the framework of
classic game theory, any common effort level is a strict and trembling hand
perfect Nash equilibrium, so that no desideratum is provided for selecting
among them. Behavior experiments, however, show that the effort levels employed
by subjects are inversely related to the effort costs. Here, we combine
coalescence theory and evolutionary game theory to investigate this game in
finite populations. Both analytic results and individual-based simulations show
that effort costs play a key role in the evolution of contribution levels,
which is in good agreement with those observed experimentally. Besides
well-mixed populations, set structured populations, where the population
structure itself is a consequence of the evolutionary process, have also been
taken into consideration. Therein we find that large number of sets and
moderate migration rate greatly promote effort levels, especially for high
effort costs. Our results may provide theoretical explanations for coordination
behaviors observed in real life from an evolutionary perspective.


title: Chow's theorem for linear codes

abstract:
  Let $\Gamma_{k}(V)$ be the Grassmann graph formed by $k$-dimensional
subspaces of an $n$-dimensional vector space over the finite field ${\mathbb
F}_{q}$ consisting of $q$ elements and $1<k<n-1$. Denote by $\Gamma(n,k)_q$ the
restriction of the Grassmann graph to the set of all non-degenerate linear
$[n,k]_q$ codes. We describe maximal cliques of the graph $\Gamma(n,k)_q$ and
show that every automorphism of this graph is induced by a monomial semilinear
automorphism of $V$.


title: Scaling limit of subcritical contact process

abstract:
  In this paper we describe the subcritical contact process on $\Z^d$ for large
times, starting with all sites infected. The configuration is described in
terms of the macroscopic locations of infected regions in space and the
relative positions of infected sites in each such region.


title: Vorticity in Heavy-Ion Collisions

abstract:
  We study the event-by-event generation of flow vorticity in RHIC Au + Au
collisions and LHC Pb + Pb collisions by using the HIJING model. Different
definitions of the vorticity field and velocity field are considered. A variety
of properties of the vorticity are explored, including the impact parameter
dependence, the collision energy dependence, the spatial distribution, the
event-by-event fluctuation of the magnitude and azimuthal direction, and the
time evolution. In addition, the spatial distribution of the flow helicity is
also studied.


title: Electrostatics of polymer translocation events in electrolyte solutions

abstract:
  We develop an analytical theory that accounts for the image and surface
charge interactions between a charged dielectric membrane and a DNA molecule
translocating through the membrane. Translocation events through neutral
carbon-based membranes are driven by a competition between the repulsive
DNA-image-charge interactions and the attractive coupling between the DNA
segments on the trans and the cis sides of the membrane. The latter effect is
induced by the reduction of the coupling by the dielectric membrane. In strong
salt solutions where the repulsive image-charge effects dominate the attractive
trans-cis coupling, the DNA molecule encounters a translocation barrier of ~10
kBT. In dilute electrolytes, the trans-cis coupling takes over image-charge
forces and the membrane becomes a metastable attraction point that can trap
translocating polymers over long time intervals. This mechanism can be used in
translocation experiments in order to control the DNA motion by tuning the salt
concentration of the solution.


title:
A Big-Data Approach to Handle Process Variations: Uncertainty
  Quantification by Tensor Recovery

abstract:
  Stochastic spectral methods have become a popular technique to quantify the
uncertainties of nano-scale devices and circuits. They are much more efficient
than Monte Carlo for certain design cases with a small number of random
parameters. However, their computational cost significantly increases as the
number of random parameters increases. This paper presents a big-data approach
to solve high-dimensional uncertainty quantification problems. Specifically, we
simulate integrated circuits and MEMS at only a small number of quadrature
samples, then, a huge number of (e.g., $1.5 \times 10^{27}$) solution samples
are estimated from the available small-size (e.g., $500$) solution samples via
a low-rank and tensor-recovery method. Numerical results show that our
algorithm can easily extend the applicability of tensor-product stochastic
collocation to IC and MEMS problems with over 50 random parameters, whereas the
traditional algorithm can only handle several random parameters.


title:
Principal spectra describing magnetooptic permittivity tensor in cubic
  crystals

abstract:
  We provide unified phenomenological description of magnetooptic effects being
linear and quadratic in magnetization. The description is based on few
principal spectra, describing elements of permittivity tensor up to the second
order in magnetization. Each permittivity tensor element for any magnetization
direction and any sample surface orientation is simply determined by weighted
summation of the principal spectra, where weights are given by crystallographic
and magnetization orientations. The number of principal spectra depends on the
symmetry of the crystal. In cubic crystals owning point symmetry we need only
four principal spectra. Here, the principal spectra are expressed by ab-initio
calculations for bcc Fe, fcc Co and fcc Ni in optical range as well as in hard
and soft x-ray energy range, i.e. at the 2p- and 3p-edges. We also express
principal spectra analytically using modified Kubo formula.


title:
Buried object detection using handheld WEMI with task-driven extended
  functions of multiple instances

abstract:
  Many effective supervised discriminative dictionary learning methods have
been developed in the literature. However, when training these algorithms,
precise ground-truth of the training data is required to provide very accurate
point-wise labels. Yet, in many applications, accurate labels are not always
feasible. This is especially true in the case of buried object detection in
which the size of the objects are not consistent. In this paper, a new multiple
instance dictionary learning algorithm for detecting buried objects using a
handheld WEMI sensor is detailed. The new algorithm, Task Driven Extended
Functions of Multiple Instances, can overcome data that does not have very
precise point-wise labels and still learn a highly discriminative dictionary.
Results are presented and discussed on measured WEMI data.


title: Integer Complexity: Representing Numbers of Bounded Defect

abstract:
  Define $\|n\|$ to be the complexity of $n$, the smallest number of ones
needed to write $n$ using an arbitrary combination of addition and
multiplication. John Selfridge showed that $\|n\|\ge 3\log_3 n$ for all $n$.
Based on this, this author and Zelinsky defined the "defect" of $n$,
$\delta(n):=\|n\|-3\log_3 n$, and this author showed that the set of all
defects is a well-ordered subset of the real numbers. This was accomplished by
showing that for a fixed real number $r$, there is a finite set $S$ of
polynomials called "low-defect polynomials" such that for any $n$ with
$\delta(n)<r$, $n$ has the form $f(3^{k_1},\ldots,3^{k_r})3^{k_{r+1}}$ for some
$f\in S$. However, using the polynomials produced by this method, many
extraneous $n$ with $\delta(n)\ge r$ would also be represented. In this paper
we show how to remedy this and modify $S$ so as to represent precisely the $n$
with $\delta(n)<r$ and remove anything extraneous. Since the same polynomial
can represent both $n$ with $\delta(n)<r$ and $n$ with $\delta(n)\ge r$, this
is not a matter of simply excising the appropriate polynomials, but requires
"truncating" the polynomials to form new ones.


title:
Optimal Lagrange Multipliers for Dependent Rate Allocation in Video
  Coding

abstract:
  In a typical video rate allocation problem, the objective is to optimally
distribute a source rate budget among a set of (in)dependently coded data units
to minimize the total distortion of all units. Conventional Lagrangian
approaches convert the lone rate constraint to a linear rate penalty scaled by
a multiplier in the objective, resulting in a simpler unconstrained
formulation. However, the search for the "optimal" multiplier, one that results
in a distortion-minimizing solution among all Lagrangian solutions that satisfy
the original rate constraint, remains an elusive open problem in the general
setting. To address this problem, we propose a computation-efficient search
strategy to identify this optimal multiplier numerically. Specifically, we
first formulate a general rate allocation problem where each data unit can be
dependently coded at different quantization parameters (QP) using a previous
unit as predictor, or left uncoded at the encoder and subsequently interpolated
at the decoder using neighboring coded units. After converting the original
rate constrained problem to the unconstrained Lagrangian counterpart, we design
an efficient dynamic programming (DP) algorithm that finds the optimal
Lagrangian solution for a fixed multiplier. Finally, within the DP framework,
we iteratively compute neighboring singular multiplier values, each resulting
in multiple simultaneously optimal Lagrangian solutions, to drive the rates of
the computed Lagrangian solutions towards the bit budget. We terminate when a
singular multiplier value results in two Lagrangian solutions with rates below
and above the bit budget. In extensive monoview and multiview video coding
experiments, we show that our DP algorithm and selection of optimal multipliers
on average outperform comparable rate control solutions used in video
compression standards such as HEVC that do not skip frames in Y-PSNR.


title:
Bounding extremal functions of forbidden $0-1$ matrices using
  $(r,s)$-formations

abstract:
  First, we prove tight bounds of $n 2^{\frac{1}{(t-2)!}\alpha(n)^{t-2} \pm
O(\alpha(n)^{t-3})}$ on the extremal function of the forbidden pair of ordered
sequences $(1 2 3 \ldots k)^t$ and $(k \ldots 3 2 1)^t$ using bounds on a class
of sequences called $(r,s)$-formations. Then, we show how an analogous method
can be used to derive similar bounds on the extremal functions of forbidden
pairs of $0-1$ matrices consisting of horizontal concatenations of identical
identity matrices and their horizontal reflections.


title: The Computational Power of Dynamic Bayesian Networks

abstract:
  This paper considers the computational power of constant size, dynamic
Bayesian networks. Although discrete dynamic Bayesian networks are no more
powerful than hidden Markov models, dynamic Bayesian networks with continuous
random variables and discrete children of continuous parents are capable of
performing Turing-complete computation. With modified versions of existing
algorithms for belief propagation, such a simulation can be carried out in real
time. This result suggests that dynamic Bayesian networks may be more powerful
than previously considered. Relationships to causal models and recurrent neural
networks are also discussed.


title: Generalized Nonlinear Proca Equation and its Free-Particle Solutions

abstract:
  We introduce a non-linear extension of Proca's field theory for massive
vector (spin $1$) bosons. The associated relativistic nonlinear wave equation
is related to recently advanced nonlinear extensions of the Schroedinger,
Dirac, and Klein-Gordon equations inspired on the non-extensive generalized
thermostatistics. This is a theoretical framework that has been applied in
recent years to several problems in nuclear and particle physics, gravitational
physics, and quantum field theory. The nonlinear Proca equation investigated
here has a power-law nonlinearity characterized by a real parameter $q$
(formally corresponding to the Tsallis entropic parameter) in such a way that
the standard linear Proca wave equation is recovered in the limit $q
\rightarrow 1$. We derive the nonlinear Proca equation from a Lagrangian that,
besides the usual vectorial field $\Psi^{\mu}(\vec{x},t)$, involves an
additional field $\Phi^{\mu}(\vec{x},t)$. We obtain exact time dependent
soliton-like solutions for these fields having the form of a $q$-plane wave,
and show that both field equations lead to the relativistic energy-momentum
relation $E^{2} = p^{2}c^{2} + m^{2}c^{4}$ for all values of $q$. This suggests
that the present nonlinear theory constitutes a new field theoretical
representation of particle dynamics. In the limit of massless particles the
present $q$-generalized Proca theory reduces to Maxwell electromagnetism, and
the $q$-plane waves yield localized, transverse solutions of Maxwell equations.
Physical consequences and possible applications are discussed.


title: Sentence Pair Scoring: Towards Unified Framework for Text Comprehension

abstract:
  We review the task of Sentence Pair Scoring, popular in the literature in
various forms - viewed as Answer Sentence Selection, Semantic Text Scoring,
Next Utterance Ranking, Recognizing Textual Entailment, Paraphrasing or e.g. a
component of Memory Networks.
  We argue that all such tasks are similar from the model perspective and
propose new baselines by comparing the performance of common IR metrics and
popular convolutional, recurrent and attention-based neural models across many
Sentence Pair Scoring tasks and datasets. We discuss the problem of evaluating
randomized models, propose a statistically grounded methodology, and attempt to
improve comparisons by releasing new datasets that are much harder than some of
the currently used well explored benchmarks. We introduce a unified open source
software framework with easily pluggable models and tasks, which enables us to
experiment with multi-task reusability of trained sentence model. We set a new
state-of-art in performance on the Ubuntu Dialogue dataset.


title: On Serre functor in the category of strict polynomial functors

abstract:
  We introduce and study a Serre functor in the category ${\cal P}_d$ of strict
polynomial functors over a field of positive characteristic. By using it we
obtain the Poincar\'e duality formula for Ext--groups from [C3] in elementary
way. We also show that the derived category of the category of affine strct
polynomial functors in some cases carries the structure of Calabi-Yau category.