title: Instrumental polarisation at the Nasmyth focus of the E-ELT

abstract:
  The ~39-m European Extremely Large Telescope (E-ELT) will be the largest
telescope ever built. This makes it particularly suitable for sensitive
polarimetric observations, as polarimetry is a photon-starved technique.
However, the telescope mirrors may severely limit the polarimetric accuracy of
instruments on the Nasmyth platforms by creating instrumental polarisation
and/or modifying the polarisation signal of the object. In this paper we
characterise the polarisation effects of the two currently considered designs
for the E-ELT Nasmyth ports as well as the effect of ageing of the mirrors. By
means of the Mueller matrix formalism, we compute the response matrices of each
mirror arrangement for a range of zenith angles and wavelengths. We then
present two techniques to correct for these effects that require the addition
of a modulating device at the polarisation-free intermediate focus that acts
either as a switch or as a part of a two-stage modulator. We find that the
values of instrumental polarisation, Stokes transmission reduction and cross-
talk vary significantly with wavelength, and with pointing, for the lateral
Nasmyth case, often exceeding the accuracy requirements for proposed
polarimetric instruments. Realistic ageing effects of the mirrors after perfect
calibration of these effects may cause polarimetric errors beyond the
requirements. We show that the modulation approach with a polarimetric element
located in the intermediate focus reduces the instrumental polarisation effects
down to tolerable values, or even removes them altogether. The E-ELT will be
suitable for sensitive and accurate polarimetry, provided frequent calibrations
are carried out, or a dedicated polarimetric element is installed at the
intermediate focus.


title: On the Semantics of Gringo

abstract:
  Input languages of answer set solvers are based on the mathematically simple
concept of a stable model. But many useful constructs available in these
languages, including local variables, conditional literals, and aggregates,
cannot be easily explained in terms of stable models in the sense of the
original definition of this concept and its straightforward generalizations.
Manuals written by designers of answer set solvers usually explain such
constructs using examples and informal comments that appeal to the user's
intuition, without references to any precise semantics. We propose to approach
the problem of defining the semantics of gringo programs by translating them
into the language of infinitary propositional formulas. This semantics allows
us to study equivalent transformations of gringo programs using natural
deduction in infinitary propositional logic.


title:
A Review on Automated Brain Tumor Detection and Segmentation from MRI of
  Brain

abstract:
  Tumor segmentation from magnetic resonance imaging (MRI) data is an important
but time consuming manual task performed by medical experts. Automating this
process is a challenging task because of the high diversity in the appearance
of tumor tissues among different patients and in many cases similarity with the
normal tissues. MRI is an advanced medical imaging technique providing rich
information about the human soft-tissue anatomy. There are different brain
tumor detection and segmentation methods to detect and segment a brain tumor
from MRI images. These detection and segmentation approaches are reviewed with
an importance placed on enlightening the advantages and drawbacks of these
methods for brain tumor detection and segmentation. The use of MRI image
detection and segmentation in different procedures are also described. Here a
brief review of different segmentation for detection of brain tumor from MRI of
brain has been discussed.


title: Abstract Modular Systems and Solvers

abstract:
  Integrating diverse formalisms into modular knowledge representation systems
offers increased expressivity, modeling convenience and computational benefits.
We introduce concepts of abstract modules and abstract modular systems to study
general principles behind the design and analysis of model-finding programs, or
solvers, for integrated heterogeneous multi-logic systems. We show how abstract
modules and abstract modular systems give rise to transition systems, which are
a natural and convenient representation of solvers pioneered by the SAT
community. We illustrate our approach by showing how it applies to answer set
programming and propositional logic, and to multi-logic systems based on these
two formalisms.


title: A superconducting circuit probe for analog quantum simulators

abstract:
  Analog quantum simulators can be used to study quantum correlation in novel
many-body systems by emulating the Hamiltonian of these systems. One essential
question in quantum simulation is to probe the properties of an emulated
many-body system. Here we present a circuit QED scheme for probing such
properties by measuring the spectrum of a superconducting resonator coupled to
a quantum simulator. We first study a general framework of this approach, and
show that the spectrum of the resonator is directly related to the correlation
function of the coupling operator between the resonator and the simulator. We
then apply this scheme to a simulator of the transverse field Ising model
implemented with superconducting qubits, where the resonance peaks in the
resonator spectrum correspond to the frequencies of the elementary excitations.
The effects of resonator damping, qubit decoherence, and resonator backaction
are also discussed. This setup can be used to probe a broad range of many-body
models.


title:
The tame automorphism group of an affine quadric threefold acting on a
  square complex

abstract:
  We study the group Tame(SL$_2$) of tame automorphisms of a smooth affine
3-dimensional quadric, which we can view as the underlying variety of
SL(2,$\mathbb{C}$). We construct a square complex on which the group admits a
natural cocompact action, and we prove that the complex is CAT(0) and
hyperbolic. We propose two applications of this construction: We show that any
finite subgroup in Tame(SL$_2$) is linearizable, and that Tame(SL$_2$)
satisfies the Tits alternative.


title:
Simplified normal forms near a degenerate elliptic fixed point in
  two-parametric families of area-preserving maps

abstract:
  We derive simplified normal forms for an area-preserving map in a
neighbourhood of a degenerate resonant elliptic fixed point. Such fixed points
appear in generic two-parameter families of area-preserving maps. We also
derive a simplified normal form for a generic two-parametric unfolding. The
normal forms are used to analyse bifurcations of $n$-periodic orbits. In
particular, for $n\ge6$ we find regions of parameters where the normal form has
"meandering'' invariant curves.


title:
Efficient Solution of a Class of Quantified Constraints with Quantifier
  Prefix Exists-Forall

abstract:
  In various applications the search for certificates for certain properties
(e.g., stability of dynamical systems, program termination) can be formulated
as a quantified constraint solving problem with quantifier prefix
exists-forall. In this paper, we present an algorithm for solving a certain
class of such problems based on interval techniques in combination with
conservative linear programming approximation. In comparison with previous
work, the method is more general - allowing general Boolean structure in the
input constraint, and more efficient - using splitting heuristics that learn
from the success of previous linear programming approximations.


title: Negation in the Head of CP-logic Rules

abstract:
  CP-logic is a probabilistic extension of the logic FO(ID). Unlike ASP, both
of these logics adhere to a Tarskian informal semantics, in which
interpretations represent objective states-of-affairs. In other words, these
logics lack the epistemic component of ASP, in which interpretations represent
the beliefs or knowledge of a rational agent. Consequently, neither CP-logic
nor FO(ID) have the need for two kinds of negations: there is only one
negation, and its meaning is that of objective falsehood. Nevertheless, the
formal semantics of this objective negation is mathematically more similar to
ASP's negation-as-failure than to its classical negation. The reason is that
both CP-logic and FO(ID) have a constructive semantics in which all atoms start
out as false, and may only become true as the result of a rule application.
This paper investigates the possibility of adding the well-known ASP feature of
allowing negation in the head of rules to CP-logic. Because CP-logic only has
one kind of negation, it is of necessity this ''negation-as-failure like''
negation that will be allowed in the head. We investigate the intuitive meaning
of such a construct and the benefits that arise from it.


title: Distinction between features extracted using deep belief networks

abstract:
  Data representation is an important pre-processing step in many machine
learning algorithms. There are a number of methods used for this task such as
Deep Belief Networks (DBNs) and Discrete Fourier Transforms (DFTs). Since some
of the features extracted using automated feature extraction methods may not
always be related to a specific machine learning task, in this paper we propose
two methods in order to make a distinction between extracted features based on
their relevancy to the task. We applied these two methods to a Deep Belief
Network trained for a face recognition task.


title: Deep Belief Networks for Image Denoising

abstract:
  Deep Belief Networks which are hierarchical generative models are effective
tools for feature representation and extraction. Furthermore, DBNs can be used
in numerous aspects of Machine Learning such as image denoising. In this paper,
we propose a novel method for image denoising which relies on the DBNs' ability
in feature representation. This work is based upon learning of the noise
behavior. Generally, features which are extracted using DBNs are presented as
the values of the last layer nodes. We train a DBN a way that the network
totally distinguishes between nodes presenting noise and nodes presenting image
content in the last later of DBN, i.e. the nodes in the last layer of trained
DBN are divided into two distinct groups of nodes. After detecting the nodes
which are presenting the noise, we are able to make the noise nodes inactive
and reconstruct a noiseless image. In section 4 we explore the results of
applying this method on the MNIST dataset of handwritten digits which is
corrupted with additive white Gaussian noise (AWGN). A reduction of 65.9% in
average mean square error (MSE) was achieved when the proposed method was used
for the reconstruction of the noisy images.


title:
Learned versus Hand-Designed Feature Representations for 3d
  Agglomeration

abstract:
  For image recognition and labeling tasks, recent results suggest that machine
learning methods that rely on manually specified feature representations may be
outperformed by methods that automatically derive feature representations based
on the data. Yet for problems that involve analysis of 3d objects, such as mesh
segmentation, shape retrieval, or neuron fragment agglomeration, there remains
a strong reliance on hand-designed feature descriptors. In this paper, we
evaluate a large set of hand-designed 3d feature descriptors alongside features
learned from the raw data using both end-to-end and unsupervised learning
techniques, in the context of agglomeration of 3d neuron fragments. By
combining unsupervised learning techniques with a novel dynamic pooling scheme,
we show how pure learning-based methods are for the first time competitive with
hand-designed 3d shape descriptors. We investigate data augmentation strategies
for dramatically increasing the size of the training set, and show how
combining both learned and hand-designed features leads to the highest
accuracy.


title: Purity and Covariance Matrix

abstract:
  Basing on the simplest single-mode field source, we investigate the role of
the various covariance matrices for reconstructing the field state and
describing its quantum statistical properties. In spite of the fact that the
intracavity field is a single-mode field, we take into account the natural
multimode structure arising in the field, when it leaves the cavity for the
free-space propagation. We show how the purity of the field state can be
calculated using the different covariance matrices.


title: Reflection positive one-parameter groups and dilations

abstract:
  The concept of reflection positivity has its origins in the work of
Osterwalder--Schrader on constructive quantum field theory. It is a fundamental
tool to construct a relativistic quantum field theory as a unitary
representation of the Poincare group from a non-relativistic field theory as a
representation of the euclidean motion group. This is the second article in a
series on the mathematical foundations of reflection positivity. We develop the
theory of reflection positive one-parameter groups and the dual theory of
dilations of contractive hermitian semigroups. In particular, we connect
reflection positivity with the outgoing realization of unitary one-parameter
groups by Lax and Phillips. We further show that our results provide effective
tools to construct reflection positive representations of general symmetric Lie
groups, including the ax+b-group, the Heisenberg group, the euclidean motion
group and the euclidean conformal group.


title: Sign patterns with minimum rank 3 and point-line configurations

abstract:
  A \emph{sign pattern (matrix)} is a matrix whose entries are from the set
$\{+, -, 0\}$. The \emph{minimum rank} (respectively, \emph{rational minimum
rank}) of a sign pattern matrix $\cal A$ is the minimum of the ranks of the
real (respectively, rational) matrices whose entries have signs equal to the
corresponding entries of $\cal A$. A sign pattern $\cal A$ is said to be
\emph{condensed} if $\cal A$ has no zero row or column and no two rows or
columns are identical or negatives of each other. In this paper, a new direct
connection between condensed $m \times n $ sign patterns with minimum rank $r$
and $m$ point--$n$ hyperplane configurations in ${\mathbb R}^{r-1}$ is
established. In particular, condensed sign patterns with minimum rank 3 are
closed related to point--line configurations on the plane. It is proved that
for any sign pattern $\cal A$ with minimum rank $r\geq 3$, if the number of
zero entries on each column of $\cal A$ is at most $r-1$, then the rational
minimum rank of $\cal A$ is also $r$. Furthermore, we construct the smallest
known sign pattern whose minimum rank is 3 but whose rational minimum rank is
greater than 3.


title:
Two Weight Inequalities for Riesz Transforms: Uniformly Full Dimension
  Weights

abstract:
  Fix an integer $ n$ and number $d$, $ 0< d\neq n-1 \leq n$, and two weights $
w$ and $ \sigma $ on $ \mathbb R ^{n}$. We two extra conditions (1) no common
point masses and (2) the two weights separately are not concentrated on a set
of codimension one, uniformly over locations and scales. (This condition holds
for doubling weights.) Then, we characterize the two weight inequality for the
$ d$-dimensional Riesz transform on $ \mathbb R ^{n}$, \begin{equation*}
\sup_{0< a < b < \infty}\left\lVert \int_{a < \lvert x-y\rvert < b} f (y) \frac
{x-y} {\lvert x-y\rvert ^{d+1}} \; \sigma (dy) \right\rVert_{L ^{2}
(\mathbb{R}^n;w)} \le \mathscr N \lVert f\rVert_{L ^2 (\mathbb{R}^n;\sigma)}
\end{equation*} in terms of these two conditions, and their duals: For finite
constants $ \mathscr A_2$ and $ \mathscr T$, uniformly over all cubes $
Q\subset \mathbb R ^{n}$ \begin{gather*} \frac {w (Q)} {\lvert Q\rvert ^{d/n}}
\int_{\mathbb R ^{n}} \frac {\lvert Q\rvert ^{d/n}} {\lvert Q\rvert ^{2d/n}
+{dist}(x, Q) ^{2d/n}} \; \sigma (dx) \leq \mathscr A_2 \\ \int_{Q} \lvert
\mathsf R_{\sigma} \mathbf 1_{Q} (x)\rvert ^2 \; w(dx) \le \mathscr T ^2 \sigma
(Q), \end{gather*} where $ \mathsf R_{\sigma}$ denotes any of the truncations
of the Riesz transform as above, the dual conditions are obtained by
interchanging the roles of the two weights. Examples show that a key step of
the proof fails in absence of the extra geometric condition imposed on the
weights.


title: A Note on Lyapunov Exponents of Deterministic Strongly Mixing Potentials

abstract:
  In this Note, we consider 1D lattice Schrodinger operators with deterministic
strongly mixing potentials with very small coupling. We describe a scheme to
establish positiv- ity of the Lyapunov exponent from a statement at some fixed
scale. The required input may then be derived from Furstenberg theory, if the
underlying dynamics are sufficiently mixing, or verified directly by numerical
means.


title: An infinite-dimensional approach to path-dependent Kolmogorov equations

abstract:
  In this paper, a Banach space framework is introduced in order to deal with
finite-dimensional path-dependent stochastic differential equations. A version
of Kolmogorov backward equation is formulated and solved both in the space of
$L^p$ paths and in the space of continuous paths using the associated
stochastic differential equation, thus establishing a relation between
path-dependent SDEs and PDEs in analogy with the classical case. Finally, it is
shown how to establish a connection between such Kolmogorov equation and the
analogue finite-dimensional equation that can be formulated in terms of the
path-dependent derivatives recently introduced by Dupire, Cont and Fourni\'{e}.


title:
Multigap superconductivity in locally non-centrosymmetric SrPtAs: An As
  nuclear quadrupole resonance investigation

abstract:
  We report detailed $^{75}$As-NQR investigations of the locally
non-centrosymmetric superconductor SrPtAs. The spin-lattice relaxation studies
prove weakly coupled multi-gap superconductivity. The Hebel-Slichter peak, a
hallmark of conventional superconductivity, is strongly suppressed, which
points to an unconventional superconducting state. The observed behavior
excludes a superconducting order parameter with line nodes and is consistent
with proposed $f$-wave and chiral $d$-wave order parameters.


title:
Gauge Invariance and Spinon-Dopon Confinement in the t-J Model:
  implications for Fermi Surface Reconstruction in the Cuprates

abstract:
  We discuss the application of the two-band spin-dopon representation of the
t-J model to address the issue of the Fermi surface reconstruction observed in
the cuprates. We show that the electron no double occupancy (NDO) constraint
plays a key role in this formulation. In particular, the auxiliary lattice spin
and itinerant dopon degrees of freedom of the spin-dopon formulation of the t-J
model are shown to be confined in the emergent U(1) gauge theory generated by
the NDO constraint. This constraint is enforced by the requirement of an
infinitely large spin-dopon coupling. As a result, the t-J model is equivalent
to a Kondo-Heisenberg lattice model of itinerant dopons and localized lattice
spins at infinite Kondo coupling at all dopings. We show that mean-field
treatment of the large vs small Fermi surface crossing in the cuprates which
leaves out the NDO constraint, leads to inconsistencies and it is automatically
excluded form the t - J model framework.


title:
Factorial Hidden Markov Models for Learning Representations of Natural
  Language

abstract:
  Most representation learning algorithms for language and image processing are
local, in that they identify features for a data point based on surrounding
points. Yet in language processing, the correct meaning of a word often depends
on its global context. As a step toward incorporating global context into
representation learning, we develop a representation learning algorithm that
incorporates joint prediction into its technique for producing features for a
word. We develop efficient variational methods for learning Factorial Hidden
Markov Models from large texts, and use variational distributions to produce
features for each word that are sensitive to the entire input sequence, not
just to a local context window. Experiments on part-of-speech tagging and
chunking indicate that the features are competitive with or better than
existing state-of-the-art representation learning methods.


title: Learning Information Spread in Content Networks

abstract:
  We introduce a model for predicting the diffusion of content information on
social media. When propagation is usually modeled on discrete graph structures,
we introduce here a continuous diffusion model, where nodes in a diffusion
cascade are projected onto a latent space with the property that their
proximity in this space reflects the temporal diffusion process. We focus on
the task of predicting contaminated users for an initial initial information
source and provide preliminary results on differents datasets.


title:
An Overview of the Commercial Cloud Monitoring Tools: Research
  Dimensions, Design Issues, and State-of-the-Art

abstract:
  Cloud monitoring activity involves dynamically tracking the Quality of
Service (QoS) parameters related to virtualized resources (e.g., VM, storage,
network, appliances, etc.), the physical resources they share, the applications
running on them and data hosted on them. Applications and resources
configuration in cloud computing environment is quite challenging considering a
large number of heterogeneous cloud resources. Further, considering the fact
that at each point of time, there will be a different and specific cloud
service which may be massively required. Hence, cloud monitoring tools can
assist a cloud providers or application developers in: (i) keeping their
resources and applications operating at peak efficiency; (ii) detecting
variations in resource and application performance; (iii) accounting the
Service Level Agreement (SLA) violations of certain QoS parameters; and (iv)
tracking the leave and join operations of cloud resources due to failures and
other dynamic configuration changes.
  In this paper, we identify and discuss the major research dimensions and
design issues related to engineering cloud monitoring tools. We further discuss
how aforementioned research dimensions and design issues are handled by current
academic research as well as by commercial monitoring tools.


title:
Learning Paired-associate Images with An Unsupervised Deep Learning
  Architecture

abstract:
  This paper presents an unsupervised multi-modal learning system that learns
associative representation from two input modalities, or channels, such that
input on one channel will correctly generate the associated response at the
other and vice versa. In this way, the system develops a kind of supervised
classification model meant to simulate aspects of human associative memory. The
system uses a deep learning architecture (DLA) composed of two input/output
channels formed from stacked Restricted Boltzmann Machines (RBM) and an
associative memory network that combines the two channels. The DLA is trained
on pairs of MNIST handwritten digit images to develop hierarchical features and
associative representations that are able to reconstruct one image given its
paired-associate. Experiments show that the multi-modal learning system
generates models that are as accurate as back-propagation networks but with the
advantage of a bi-directional network and unsupervised learning from either
paired or non-paired training examples.


title: Pure scaling operators at the integer quantum Hall plateau transition

abstract:
  Stationary wave functions at the transition between plateaus of the integer
quantum Hall effect are known to exhibit multi-fractal statistics. Here we
explore this critical behavior for the case of scattering states of the
Chalker-Coddington model with point contacts. We argue that moments formed from
the wave amplitudes of critical scattering states decay as pure powers of the
distance between the points of contact and observation. These moments in the
continuum limit are proposed to be correlations functions of primary fields of
an underlying conformal field theory. We check this proposal numerically by
finite-size scaling. We also verify the CFT prediction for a 3-point function
involving two primary fields.


title: Multilingual Distributed Representations without Word Alignment

abstract:
  Distributed representations of meaning are a natural way to encode covariance
relationships between words and phrases in NLP. By overcoming data sparsity
problems, as well as providing information about semantic relatedness which is
not available in discrete representations, distributed representations have
proven useful in many NLP tasks. Recent work has shown how compositional
semantic representations can successfully be applied to a number of monolingual
applications such as sentiment analysis. At the same time, there has been some
initial success in work on learning shared word-level representations across
languages. We combine these two approaches by proposing a method for learning
distributed representations in a multilingual setup. Our model learns to assign
similar embeddings to aligned sentences and dissimilar ones to sentence which
are not aligned while not requiring word alignments. We show that our
representations are semantically informative and apply them to a cross-lingual
document classification task where we outperform the previous state of the art.
Further, by employing parallel corpora of multiple language pairs we find that
our model learns representations that capture semantic relationships across
languages for which no parallel data was used.


title:
Generic regimes of quantum many-body dynamics of trapped bosonic systems
  with strong repulsive interactions

abstract:
  Two generically different but universal dynamical quantum many-body behaviors
are discovered by probing the stability of trapped fragmented bosonic systems
with strong repulsive finite/long range inter-particle interactions. We use
different time-dependent processes to destabilize the systems -- a sudden
displacement of the trap is accompanied by a sudden quench of the strength of
the inter-particle repulsion. A rather moderate non-violent evolution of the
density in the first "topology-preserved" scenario is contrasted with a
highly-non-equilibrium dynamics characterizing an explosive changes of the
density profiles in the second scenario. The many-body physics behind is
identified and interpreted in terms of self-induced time-dependent barriers
governing the respective under- and over-a-barrier dynamical evolutions. The
universality of the discovered scenarios is explicitly confirmed in 1D, 2D and
3D many-body computations in (a)symmetric traps and repulsive finite/long range
inter-particle interaction potentials of different shapes. Implications are
briefly discussed.


title:
Lower bounds for Kolmogorov widths of classes of convolutions with
  Neumann kernel

abstract:
  We obtain exact lower bounds for Kolmogorov $n$-widths in spaces $C$ and $L$
of classes of convolutions with Neumann kernel
$N_{q,\beta}(t)=\sum\limits_{k=1}^{\infty}\dfrac{q^k}{k}\cos\left(kt-\dfrac{\beta\pi}{2}\right)$,
${q\in(0,1)}$, ${\beta\in\mathbb{R}}$, for all natural $n$ greater some number
which depend only on $q$. The obtained estimates coincide with the best uniform
approximations by trigonometric polynomials of mentioned classes. It made
possible to obtain exact values for widths of these classes.


title:
Impact of local-moment fluctuations on the magnetic degeneracy of iron
  arsenide superconductors

abstract:
  We investigate the fate of the orthorhombic stripe-type magnetic state
(ordering vectors $\left(\pi,0\right)$/$\left(0,\pi\right)$), observed in most
iron-pnictide superconductors, in the presence of localized magnetic moments
that tend to form a Neel state (ordering vector $\left(\pi,\pi\right)$). We
show that before long-range Neel order sets in, the coupling between the
conduction electrons and the fluctuations of the local moments favors an
unusual magnetic state consisting of a coherent superposition of the
$\left(\pi,0\right)$ and $\left(0,\pi\right)$ orders that preserves tetragonal
symmetry. The magnetization of this state is non-uniform and induces a
simultaneous checkerboard charge order. We discuss signatures of this magnetic
configuration on the electronic spectrum and its impact on the superconducting
state, showing that its phase space for coexistence with the $s^{+-}$ state is
smaller than the stripe-type state. Our results shed light on recent
experimental observations on $\mathrm{Ba(Fe_{1-x}Mn_{x})_{2}As_{2}}$ compounds,
where the Neel-type local Mn moments interact with the Fe conduction electrons.


title: Quantum Monte Carlo measurement of the chemical potential of helium-4

abstract:
  A path integral Monte Carlo method based on the worm algorithm has been
developed to compute the chemical potential of interacting bosonic quantum
fluids. By applying it to finite-sized systems of helium-4 atoms, we have
confirmed that the chemical potential scales inversely with the number of
particles to lowest order. The introduction of a simple scaling form allows for
the extrapolation of the chemical potential to the thermodynamic limit, where
we observe excellent agreement with known experimental results for helium-4 at
saturated vapor pressure. We speculate on future applications of the proposed
technique, including its use in studies of confined quantum fluids.


title:
Analytical relation between quark confinement and chiral symmetry
  breaking in odd-number lattice QCD

abstract:
  To clarify the relation between confinement and chiral symmetry breaking in
QCD, we consider a temporally odd-number lattice, with the temporal lattice
size $N_t$ being odd. We here use an ordinary square lattice with the normal
(nontwisted) periodic boundary condition for link-variables in the temporal
direction. By considering ${\rm Tr} (\hat{U}_4\hat{\not D}^{N_t-1})$, we
analytically derive a gauge-invariant relation between the Polyakov loop
$\langle L_P \rangle$ and the Dirac eigenvalues $\lambda_n$ in QCD, i.e.,
$\langle L_P \rangle \propto \sum_n \lambda_n^{N_t -1} \langle n|\hat U_4|n
\rangle$, which is a Dirac spectral representation of the Polyakov loop in
terms of Dirac eigenmodes $|n\rangle$. Owing to the factor $\lambda_n^{N_t -1}$
in the Dirac spectral sum, this relation generally indicates fairly small
contribution of low-lying Dirac modes to the Polyakov loop, while the low-lying
Dirac modes are essential for chiral symmetry breaking. Also in lattice QCD
calculations in both confined and deconfined phases, we numerically confirm the
analytical relation, non-zero finiteness of $\langle n|\hat U_4|n \rangle$ for
each Dirac mode, and negligibly small contribution from low-lying Dirac modes
to the Polyakov loop, i.e., the Polyakov loop is almost unchanged even by
removing low-lying Dirac-mode contribution from the QCD vacuum generated by
lattice QCD simulations. We thus conclude that low-lying Dirac modes are not
essential modes for confinement, which indicates no direct one-to-one
correspondence between confinement and chiral symmetry breaking in QCD.


title: Bulk Metallic Glasses Deform via Slip Avalanches

abstract:
  Inelastic deformation of metallic glasses occurs via slip events with
avalanche dynamics similar to those of earthquakes. For the first time in these
materials, measurements have been obtained with sufficiently high temporal
resolution to extract both the exponents and the scaling functions that
describe the nature, statistics and dynamics of the slips according to a simple
mean-field model. These slips originate from localized deformation in shear
bands. The mean-field model describes the slip process as an avalanche of
rearrangements of atoms in shear transformation zones (STZs). Small slips show
the predicted power-law scaling and correspond to limited propagation of a
shear front, while large slips are associated with uniform shear on
unconstrained shear bands. The agreement between the model and data across
multiple independent measures of slip statistics and dynamics provides
compelling evidence for slip avalanches of STZs as the elementary mechanism of
inhomogeneous deformation in metallic glasses.


title: Manifold regularized kernel logistic regression for web image annotation

abstract:
  With the rapid advance of Internet technology and smart devices, users often
need to manage large amounts of multimedia information using smart devices,
such as personal image and video accessing and browsing. These requirements
heavily rely on the success of image (video) annotation, and thus large scale
image annotation through innovative machine learning methods has attracted
intensive attention in recent years. One representative work is support vector
machine (SVM). Although it works well in binary classification, SVM has a
non-smooth loss function and can not naturally cover multi-class case. In this
paper, we propose manifold regularized kernel logistic regression (KLR) for web
image annotation. Compared to SVM, KLR has the following advantages: (1) the
KLR has a smooth loss function; (2) the KLR produces an explicit estimate of
the probability instead of class label; and (3) the KLR can naturally be
generalized to the multi-class case. We carefully conduct experiments on MIR
FLICKR dataset and demonstrate the effectiveness of manifold regularized kernel
logistic regression for image annotation.


title:
Comment on the Nature of the $D_{s1}^*(2710)$ and $D_{sJ}^*(2860)$
  Mesons

abstract:
  Two charm-strange mesons, the $D_{s1}^*(2710)$ and the $D_{sJ}^*(2860)$, have
recently been observed by several experiments. There has been speculation in
the literature that the $D_{s1}^*(2710)$ is the $2^3S_1(c\bar{s})$ state and
the $D_{sJ}^*(2860)$ is the $1^3D_1(c\bar{s})$ state. In this paper we explore
this and other explanations in the context of the relativized quark model and
the pseudoscalar emission decay model. We conclude that the $D_{s1}^*(2710)$ is
most likely the $1^3D_1 (c\bar{s})$ state and the $D_{sJ}^*(2860)$ is most
likely the $1^3D_3 (c\bar{s})$ state with the $1D_2$ resonances also
contributing to the observed signals and explaining the observed ratios of
branching ratios to $D^*K$ and $DK$ final states. We point out that measuring
the $D_{sJ}^*(2860)$ spin can support or eliminate this explanation and that
there are six excited $D_s$ states in this mass region; the $2^3S_1$, $2^1S_0$,
$1^3D_1$, $1^3D_3$ and two $1D_2$ states. Observing some of the missing states
would help confirm the nature of the $D_{s1}^*(2710)$ and the $D_{sJ}^*(2860)$
states.


title: Large-Scale Paralleled Sparse Principal Component Analysis

abstract:
  Principal component analysis (PCA) is a statistical technique commonly used
in multivariate data analysis. However, PCA can be difficult to interpret and
explain since the principal components (PCs) are linear combinations of the
original variables. Sparse PCA (SPCA) aims to balance statistical fidelity and
interpretability by approximating sparse PCs whose projections capture the
maximal variance of original data. In this paper we present an efficient and
paralleled method of SPCA using graphics processing units (GPUs), which can
process large blocks of data in parallel. Specifically, we construct parallel
implementations of the four optimization formulations of the generalized power
method of SPCA (GP-SPCA), one of the most efficient and effective SPCA
approaches, on a GPU. The parallel GPU implementation of GP-SPCA (using CUBLAS)
is up to eleven times faster than the corresponding CPU implementation (using
CBLAS), and up to 107 times faster than a MatLab implementation. Extensive
comparative experiments in several real-world datasets confirm that SPCA offers
a practical advantage.


title:
Spectrum bandwidth narrowing of Thomson scattering X-rays with energy
  chirped electron beams from laser wakefield acceleration

abstract:
  We study incoherent Thomson scattering between an ultrashort laser pulse and
an electron beam accelerated from a laser wakefield. The energy chirp effects
of the accelerated electron beam on the final radiation spectrum bandwidth are
investigated. It is found that the scattered X-ray radiation has the minimum
spectrum width and highest intensity as electrons are accelerated up to around
the dephasing point. Furthermore, it is proposed the electron acceleration
process inside the wakefield can be studied by use of $90^\circ$ Thomson
scattering. The dephasing position and beam energy chirp can be deduced from
the intensity and bandwidth of the scattered radiation.


title: Do Deep Nets Really Need to be Deep?

abstract:
  Currently, deep neural networks are the state of the art on problems such as
speech recognition and computer vision. In this extended abstract, we show that
shallow feed-forward networks can learn the complex functions previously
learned by deep nets and achieve accuracies previously only achievable with
deep models. Moreover, in some cases the shallow neural nets can learn these
deep functions using a total number of parameters similar to the original deep
model. We evaluate our method on the TIMIT phoneme recognition task and are
able to train shallow fully-connected nets that perform similarly to complex,
well-engineered, deep convolutional architectures. Our success in training
shallow neural nets to mimic deeper models suggests that there probably exist
better algorithms for training shallow feed-forward nets than those currently
available.


title:
DNA sequence-dependent mechanics and protein-assisted bending in
  repressor-mediated loop formation

abstract:
  As the chief informational molecule of life, DNA is subject to extensive
physical manipulations. The energy required to deform double-helical DNA
depends on sequence, and this mechanical code of DNA influences gene
regulation, such as through nucleosome positioning. Here we examine the
sequence-dependent flexibility of DNA in bacterial transcription
factor-mediated looping, a context for which the role of sequence remains
poorly understood. Using a suite of synthetic constructs repressed by the Lac
repressor and two well-known sequences that show large flexibility differences
in vitro, we make precise statistical mechanical predictions as to how DNA
sequence influences loop formation and test these predictions using in vivo
transcription and in vitro single-molecule assays. Surprisingly,
sequence-dependent flexibility does not affect in vivo gene regulation. By
theoretically and experimentally quantifying the relative contributions of
sequence and the DNA-bending protein HU to DNA mechanical properties, we reveal
that bending by HU dominates DNA mechanics and masks intrinsic
sequence-dependent flexibility. Such a quantitative understanding of how
mechanical regulatory information is encoded in the genome will be a key step
towards a predictive understanding of gene regulation at single-base pair
resolution.


title:
GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network
  Training

abstract:
  The ability to train large-scale neural networks has resulted in
state-of-the-art performance in many areas of computer vision. These results
have largely come from computational break throughs of two forms: model
parallelism, e.g. GPU accelerated training, which has seen quick adoption in
computer vision circles, and data parallelism, e.g. A-SGD, whose large scale
has been used mostly in industry. We report early experiments with a system
that makes use of both model parallelism and data parallelism, we call GPU
A-SGD. We show using GPU A-SGD it is possible to speed up training of large
convolutional neural networks useful for computer vision. We believe GPU A-SGD
will make it possible to train larger networks on larger training sets in a
reasonable amount of time.


title: Hermite multiplier sequences and their associated operators

abstract:
  We provide an explicit formula for the coefficient polynomials of a Hermite
diagonal differential operator. The analysis of the zeros of these coefficient
polynomials yields the characterization of generalized Hermite multiplier
sequences which arise as Taylor coefficients of real entire functions with
finitely many zeros. We extend our result to functions in $\mathcal{L-P}$ with
infinitely many zeros, under additional hypotheses.


title:
Comment on "Towards universal quantum computation through relativistic
  motion"

abstract:
  The work reported in arXiv:1311.5619v1 proposes to produce
continuous-variable cluster states through relativistic motion of cavities.
This proposal does not produce the states claimed by the authors. The states
actually produced are in general not known to be useful for measurement-based
quantum computation.


title: Coping with Physical Attacks on Random Network Structures

abstract:
  Communication networks are vulnerable to natural disasters, such as
earthquakes or floods, as well as to physical attacks, such as an
Electromagnetic Pulse (EMP) attack. Such real-world events happen at specific
geographical locations and disrupt specific parts of the network. Therefore,
the geographical layout of the network determines the impact of such events on
the network's physical topology in terms of capacity, connectivity, and flow.
  Recent works focused on assessing the vulnerability of a deterministic
network to such events. In this work, we focus on assessing the vulnerability
of (geographical) random networks to such disasters. We consider stochastic
graph models in which nodes and links are probabilistically distributed on a
plane, and model the disaster event as a circular cut that destroys any node or
link within or intersecting the circle.
  We develop algorithms for assessing the damage of both targeted and
non-targeted (random) attacks and determining which attack locations have the
expected most disruptive impact on the network. Then, we provide experimental
results for assessing the impact of circular disasters to communications
networks in the USA, where the network's geographical layout was modeled
probabilistically, relying on demographic information only. Our results
demonstrates the applicability of our algorithms to real-world scenarios.
  Our algorithms allows to examine how valuable is public information about the
network's geographical area (e.g., demography, topography, economy) to an
attacker's destruction assessment capabilities in the case the network's
physical topology is hidden or examine the affect of hiding the actual physical
location of the fibers on the attack strategy. Thereby, our schemes can be used
as a tool for policy makers and engineers to design more robust networks and
identifying locations which require additional protection efforts.


title: Adaptive Feature Ranking for Unsupervised Transfer Learning

abstract:
  Transfer Learning is concerned with the application of knowledge gained from
solving a problem to a different but related problem domain. In this paper, we
propose a method and efficient algorithm for ranking and selecting
representations from a Restricted Boltzmann Machine trained on a source domain
to be transferred onto a target domain. Experiments carried out using the
MNIST, ICDAR and TiCC image datasets show that the proposed adaptive feature
ranking and transfer learning method offers statistically significant
improvements on the training of RBMs. Our method is general in that the
knowledge chosen by the ranking function does not depend on its relation to any
specific target domain, and it works with unsupervised learning and
knowledge-based transfer.


title:
Towards a unified realistic shell-model Hamiltonian with the
  monopole-based universal force

abstract:
  We propose a unified realistic shell-model Hamiltonian employing the pairing
plus multipole Hamiltonian combined with the monopole interaction constructed
starting from the monopole-based universal force by Otsuka it et al. (Phys.
Rev. Lett. 104, 012501 (2010)). It is demonstrated that the proposed PMMU model
can consistently describe a large amount of spectroscopic data as well as
binding energies in the pf and pf5/2g9/2 shell spaces, and could serve as a
practical shell model for even heavier mass regions.


title: Can recursive neural tensor networks learn logical reasoning?

abstract:
  Recursive neural network models and their accompanying vector representations
for words have seen success in an array of increasingly semantically
sophisticated tasks, but almost nothing is known about their ability to
accurately capture the aspects of linguistic meaning that are necessary for
interpretation or reasoning. To evaluate this, I train a recursive model on a
new corpus of constructed examples of logical reasoning in short sentences,
like the inference of "some animal walks" from "some dog walks" or "some cat
walks," given that dogs and cats are animals. This model learns representations
that generalize well to new types of reasoning pattern in all but a few cases,
a result which is promising for the ability of learned representation models to
capture logical reasoning.


title:
Extreme points of the Vandermonde determinant on the sphere and some
  limits involving the generalized Vandermonde determinant

abstract:
  The values of the determinant of Vandermonde matrices with real elements are
analyzed both visually and analytically over the unit sphere in various
dimensions. For three dimensions some generalized Vandermonde matrices are
analyzed visually. The extreme points of the ordinary Vandermonde determinant
on finite-dimensional unit spheres are given as the roots of rescaled Hermite
polynomials and a recursion relation is provided for the polynomial
coefficients. Analytical expressions for these roots are also given for
dimension three to seven. A transformation of the optimization problem is
provided and some relations between the ordinary and generalized Vandermonde
matrices involving limits are discussed.


title:
The Dirichlet problem for the minimal surface equation in $\rm Sol_3$,
  with possible infinite boundary data

abstract:
  In this paper, we study the Dirichlet problem for the minimal surface
equation in $\rm Sol_3$ with possible infinite boundary data, where $\rm Sol_3$
is the non-abelian solvable $3$-dimensional Lie group equipped with its usual
left-invariant metric that makes it into a model space for one of the eight
Thurston geometries. Our main result is a Jenkins-Serrin type theorem which
establishes necessary and sufficient conditions for the existence and
uniqueness of certain minimal Killing graphs with a non-unitary Killing vector
field in $\rm Sol_3$.


title:
Large deviations for zeros of random polynomials with i.i.d. exponential
  coefficients

abstract:
  We derive a large deviation principle for the empirical measure of zeros of
random polynomials with i.i.d. exponential coefficients.


title:
Group Theoretical Approach to the Construction of Conformal Field
  Theories

abstract:
  A conformal field theory (CFT) is a quantum field theory which is invariant
under conformal transformations; a group action that preserve angles but not
necessarily lengths. There are two traditional approaches to the construction
of CFTs: analyzing a statistical system near a critical point as a euclidean
field theory, and in holographic duality within the context of string theory.
This pedagogical paper presents a construction of CFTs using purely group
theoretic techniques. Starting with the basic definition of a Lie algebra and
quantum field theory, we generalize to affine Lie algebras and form a energy
momentum tensor via the Sugawara construction.


title: An empirical analysis of dropout in piecewise linear networks

abstract:
  The recently introduced dropout training criterion for neural networks has
been the subject of much attention due to its simplicity and remarkable
effectiveness as a regularizer, as well as its interpretation as a training
procedure for an exponentially large ensemble of networks that share
parameters. In this work we empirically investigate several questions related
to the efficacy of dropout, specifically as it concerns networks employing the
popular rectified linear activation function. We investigate the quality of the
test time weight-scaling inference procedure by evaluating the geometric
average exactly in small models, as well as compare the performance of the
geometric mean to the arithmetic mean more commonly employed by ensemble
techniques. We explore the effect of tied weights on the ensemble
interpretation by training ensembles of masked networks without tied weights.
Finally, we investigate an alternative criterion based on a biased estimator of
the maximum likelihood ensemble gradient.


title: Categories within the Foundation of Mathematics

abstract:
  The recent trend in mathematics is towards a framework of abstract
mathematical objects, rather than the more concrete approach of explicitly
defining elements which objects were thought to consist of. A natural question
to raise is whether this sort of abstract approach advocated for by Lawvere,
among others, is foundational in the sense that it provides a unified,
universal, system of first order axioms in which we can define the usual
mathematical objects and prove their usual properties. In this way, we view the
``foundation" as something without any necessary justification or starting
point. Some of the main arguments for categories as such a structure are laid
out by MacLane as he argues that the set-theoretic constructions are
inappropriate for current mathematics as practices, and that they are
inadequate to properly encompass category theory itself and therefore cannot
properly encompass all of mathematics, while category theory can be used to
describe set theory and all the natural consequences of a given primitive
system.


title: Intriguing properties of neural networks

abstract:
  Deep neural networks are highly expressive models that have recently achieved
state of the art performance on speech and visual recognition tasks. While
their expressiveness is the reason they succeed, it also causes them to learn
uninterpretable solutions that could have counter-intuitive properties. In this
paper we report two such properties.
  First, we find that there is no distinction between individual high level
units and random linear combinations of high level units, according to various
methods of unit analysis. It suggests that it is the space, rather than the
individual units, that contains of the semantic information in the high layers
of neural networks.
  Second, we find that deep neural networks learn input-output mappings that
are fairly discontinuous to a significant extend. We can cause the network to
misclassify an image by applying a certain imperceptible perturbation, which is
found by maximizing the network's prediction error. In addition, the specific
nature of these perturbations is not a random artifact of learning: the same
perturbation can cause a different network, that was trained on a different
subset of the dataset, to misclassify the same input.


title: Data mining the EXFOR database using network theory

abstract:
  The EXFOR database contains the largest collection of experimental nuclear
reaction data available as well as the data's bibliographic information and
experimental details. We created an undirected graph from the EXFOR datasets
with graph nodes representing single observables and graph links representing
the various types of connections between these observables. This graph is an
abstract representation of the connections in EXFOR, similar to graphs of
social networks, authorship networks, etc. By analyzing this abstract graph, we
are able to address very specific questions such as 1) what observables are
being used as reference measurements by the experimental nuclear science
community? 2) are these observables given the attention needed by various
nuclear data evaluation projects? 3) are there classes of observables that are
not connected to these reference measurements? In addressing these questions,
we propose several (mostly cross section) observables that should be evaluated
and made into reaction reference standards.


title: Coverage Games for Testing Nondeterministic Systems

abstract:
  Modern software systems may exhibit a nondeterministic behavior due to many
unpredictable factors. In this work, we propose the node coverage game, a two
player turn-based game played on a finite game graph, as a formalization of the
problem to test such systems. Each node in the graph represents a {\em
functional equivalence class} of the software under test (SUT). One player, the
tester, wants to maximize the node coverage, measured by the number of nodes
visited when exploring the game graphs, while his opponent, the SUT, wants to
minimize it. An optimal test would maximize the cover, and it is an interesting
problem to find the maximal number of nodes that the tester can guarantee to
visit, irrespective of the responses of the SUT. We show that the decision
problem of whether the guarantee is less than a given number is NP-complete.
Then we present techniques for testing nondeterministic SUTs with existing test
suites for deterministic models. Finally, we report our implementation and
experiments.


title: The WISE Catalog of Galactic HII Regions

abstract:
  Using data from the all-sky Wide-Field Infrared Survey Explorer (WISE)
satellite, we made a catalog of over 8000 Galactic HII regions and HII region
candidates by searching for their characteristic mid-infrared (MIR) morphology.
WISE has sufficient sensitivity to detect the MIR emission from HII regions
located anywhere in the Galactic disk. We believe this is the most complete
catalog yet of regions forming massive stars in the Milky Way. Of the ~8000
cataloged sources, ~1500 have measured radio recombination line (RRL) or
H$\alpha$ emission, and are thus known to be HII regions. This sample improves
on previous efforts by resolving HII region complexes into multiple sources and
by removing duplicate entries. There are ~2500 candidate HII regions in the
catalog that are spatially coincident with radio continuum emission. Our
group's previous RRL studies show that ~95% of such targets are HII regions. We
find that ~500 of these candidates are also positionally associated with known
HII region complexes, so the probability of their being bona fide HII regions
is even higher. At the sensitivity limits of existing surveys, ~4000 catalog
sources show no radio continuum emission. Using data from the literature, we
find distances for ~1500 catalog sources, and molecular velocities for ~1500
HII region candidates.


title: Spectral Networks and Locally Connected Networks on Graphs

abstract:
  Convolutional Neural Networks are extremely efficient architectures in image
and audio recognition tasks, thanks to their ability to exploit the local
translational invariance of signal classes over their domain. In this paper we
consider possible generalizations of CNNs to signals defined on more general
domains without the action of a translation group. In particular, we propose
two constructions, one based upon a hierarchical clustering of the domain, and
another based on the spectrum of the graph Laplacian. We show through
experiments that for low-dimensional graphs it is possible to learn
convolutional layers with a number of parameters independent of the input size,
resulting in efficient deep architectures.


title: One-Shot Adaptation of Supervised Deep Convolutional Models

abstract:
  Dataset bias remains a significant barrier towards solving real world
computer vision tasks. Though deep convolutional networks have proven to be a
competitive approach for image classification, a question remains: have these
models have solved the dataset bias problem? In general, training or
fine-tuning a state-of-the-art deep model on a new domain requires a
significant amount of data, which for many applications is simply not
available. Transfer of models directly to new domains without adaptation has
historically led to poor recognition performance. In this paper, we pose the
following question: is a single image dataset, much larger than previously
explored for adaptation, comprehensive enough to learn general deep models that
may be effectively applied to new image domains? In other words, are deep CNNs
trained on large amounts of labeled data as susceptible to dataset bias as
previous methods have been shown to be? We show that a generic supervised deep
CNN model trained on a large dataset reduces, but does not remove, dataset
bias. Furthermore, we propose several methods for adaptation with deep models
that are able to operate with little (one example per category) or no labeled
domain specific data. Our experiments show that adaptation of deep models on
benchmark visual domain adaptation datasets can provide a significant
performance boost.


title: Relaxations for inference in restricted Boltzmann machines

abstract:
  We propose a relaxation-based approximate inference algorithm that samples
near-MAP configurations of a binary pairwise Markov random field. We experiment
on MAP inference tasks in several restricted Boltzmann machines. We also use
our underlying sampler to estimate the log-partition function of restricted
Boltzmann machines and compare against other sampling-based methods.


title: Consistent high-energy constraints in the anomalous QCD sector

abstract:
  The anomalous <VVP> Green function and related form-factors (pi^0 to gamma^*
gamma^* and tau^- to X^- nu_tau vector form-factors, with X^-=(KKpi)^-, phi^-
gamma, (phi V)^-) are analyzed in this letter in the large-N_C limit. Within
the single (vector and pseudoscalar) resonance approximation and the context of
Resonance Chiral Theory, we show that all these observables over-determine in a
consistent way a unique set of compatible high-energy constraints for the
resonance couplings. This result is in agreement with analogous relations found
in the even intrinsic-parity sector of QCD like, e.g., F_V^2 = 3 F^2. The
antisymmetric tensor formalism is considered for the spin-one resonance fields.
Finally, we have also worked out and provide here the relation between the two
bases of odd intrinsic-parity Lagrangian operators commonly employed in the
literature.


title:
Seven, eight, and nine mutually touching infinitely long straight round
  cylinders: Entanglement in Euclidean space

abstract:
  It has been a challenge to make seven straight round cylinders mutually touch
before our now 10-year old discovery [Phys. Rev. Lett. 93, 015505 (2004)] of
configurations of seven mutually touching infinitely long round cylinders (then
coined 7-knots). Because of the current interest in string-like objects and
entanglement which occur in many fields of Physics it is useful to find a
simple way to treat ensembles of straight infinite cylinders. Here we propose a
treatment with a chirality matrix. By comparing 7-knot with variable radii with
the one where all cylinders are of equal radii (here 7*-knot, which for the
first time appeared in [phys. stat. solidi, b 246, 2098 (2009)]), we show that
the reduction of 7-knot with a set of non-equal cylinder radii to 7*-knot of
equal radii is possible only for one topologically unique configuration, all
other 7-knots being of different topology. We found novel configurations for
mutually touching infinitely long round cylinders when their numbers are eight
and ultimately nine (here coined 8-knots and 9-knots). Unlike the case of
7-knot, where one angular parameter (for a given set of fixed radii) may change
by sweeping a scissor angle between two chosen cylinders, in case of 8- and
9-knots their degrees of freedom are completely exhausted by mutual touching so
that their configurations are "frozen" for each given set of radii. For 8-knot
the radii of any six cylinders may be changeable (for example, all taken equal)
while two remaining are uniquely determined by the others. We show that 9-knot
makes the ultimate configuration where only three cylinders can have changeable
radii and the remaining six are determined by the three. Possible
generalizations and connection with Physics are mentioned.


title:
Total variation with overlapping group sparsity for image deblurring
  under impulse noise

abstract:
  The total variation (TV) regularization method is an effective method for
image deblurring in preserving edges. However, the TV based solutions usually
have some staircase effects. In this paper, in order to alleviate the staircase
effect, we propose a new model for restoring blurred images with impulse noise.
The model consists of an $\ell_1$-fidelity term and a TV with overlapping group
sparsity (OGS) regularization term. Moreover, we impose a box constraint to the
proposed model for getting more accurate solutions. An efficient and effective
algorithm is proposed to solve the model under the framework of the alternating
direction method of multipliers (ADMM). We use an inner loop which is nested
inside the majorization minimization (MM) iteration for the subproblem of the
proposed method. Compared with other methods, numerical results illustrate that
the proposed method, can significantly improve the restoration quality, both in
avoiding staircase effects and in terms of peak signal-to-noise ratio (PSNR)
and relative error (ReE).


title:
What makes the lac-pathway switch: identifying the fluctuations that
  trigger phenotype switching in gene regulatory systems

abstract:
  Multistable gene regulatory systems sustain different levels of gene
expression under identical external conditions. Such multistability is used to
encode phenotypic states in processes including nutrient uptake and persistence
in bacteria, fate selection in viral infection, cell cycle control, and
development. Stochastic switching between different phenotypes can occur as the
result of random fluctuations in molecular copy numbers of mRNA and proteins
arising in transcription, translation, transport, and binding. However, which
component of a pathway triggers such a transition is generally not known. By
linking single-cell experiments on the lactose-uptake pathway in E. coli to
molecular simulations, we devise a general method to pinpoint the particular
fluctuation driving phenotype switching and apply this method to the transition
between the uninduced and induced states of the lac genes. We find that the
transition to the induced state is not caused only by the single event of
lac-repressor unbinding, but depends crucially on the time period over which
the repressor remains unbound from the lac-operon. We confirm this notion in
strains with a high expression level of the repressor (leading to shorter
periods over which the lac-operon remains unbound), which show a reduced
switching rate. Our techniques apply to multi-stable gene regulatory systems in
general and allow to identify the molecular mechanisms behind stochastic
transitions in gene regulatory circuits.


title: Some remarks on the qualitative questions for biharmonic equations

abstract:
  In this article, we obtain several interesting remarks on the qualitative
questions such as stability criteria, Morse index, Picone's identity for
biharmonic equations.


title:
An Empirical Investigation of Catastrophic Forgetting in Gradient-Based
  Neural Networks

abstract:
  Catastrophic forgetting is a problem faced by many machine learning models
and algorithms. When trained on one task, then trained on a second task, many
machine learning models "forget" how to perform the first task. This is widely
believed to be a serious problem for neural networks. Here, we investigate the
extent to which the catastrophic forgetting problem occurs for modern neural
networks, comparing both established and recent gradient-based training
algorithms and activation functions. We also examine the effect of the
relationship between the first task and the second task on catastrophic
forgetting. We find that it is always best to train using the dropout
algorithm--the dropout algorithm is consistently best at adapting to the new
task, remembering the old task, and has the best tradeoff curve between these
two extremes. We find that different tasks and relationships between tasks
result in very different rankings of activation function performance. This
suggests the choice of activation function should always be cross-validated.


title:
Pumping of the 4.8 GHz H$_{\text{2}}$CO masers and its implications for
  the periodic masers in G37.55+0.20

abstract:
  Periodic or regular flaring of class II methanol masers in nine high mass
star forming regions is now a well established phenomenon. Amongst the nine
star forming regions, G37.55+0.20 is the only case at present where apart from
the presence of a periodic class II methanol maser, correlated flaring of
another masing species, formaldehyde in this case, has been detected. We
perform numerical calculations to investigate under which conditions the 4.8
GHz transition of ortho-formaldehyde is inverted in order to address the
question of the correlated flaring of the 6.7 GHz methanol and 4.8 GHz
formaldehyde masers in G37.55+0.20. We developed a numerical code to study the
population inversion of o-formaldehyde. Equilibrium solutions for the level
populations are found by integrating the rate equations using Heun's method. It
is found that collisional excitation with H$_2$ as well as radiative excitation
by the free-free radio continuum radiation from a nearby ultra- or
hyper-compact HII region can invert the 4.8 GHz transition. It is also found
that radiative excitation by the dust infrared radiation field does not lead to
an inversion of the 4.8 GHz transition. The 14.5 GHz and 28.9 GHz transitions
are inverted only in the presence of the free-free continuum radiation field of
a very compact HII region. Due to the different pumping mechanisms of the
formaldehyde and methanol masers it is unlikely that the near simultaneous
flaring of the methanol and formaldehyde masers in G37.55+0.20 is due to
changes in the pumping of the masers.


title: Subdivisions of a large clique in $C_6$-free graphs

abstract:
  Mader conjectured that every $C_4$-free graph has a subdivision of a clique
of order linear in its average degree. We show that every $C_6$-free graph has
such a subdivision of a large clique.
  We also prove the dense case of Mader's conjecture in a stronger sense, i.e.
for every $c$, there is a $c'$ such that every $C_4$-free graph with average
degree $cn^{1/2}$ has a subdivision of a clique $K_\ell$ with $\ell=\lfloor
c'n^{1/2}\rfloor$ where every edge is subdivided exactly $3$ times.


title: Volumetric Spanners: an Efficient Exploration Basis for Learning

abstract:
  Numerous machine learning problems require an exploration basis - a mechanism
to explore the action space. We define a novel geometric notion of exploration
basis with low variance, called volumetric spanners, and give efficient
algorithms to construct such a basis.
  We show how efficient volumetric spanners give rise to the first efficient
and optimal regret algorithm for bandit linear optimization over general convex
sets. Previously such results were known only for specific convex sets, or
under special conditions such as the existence of an efficient self-concordant
barrier for the underlying set.


title:
Sensor management for multi-target tracking via Multi-Bernoulli
  filtering

abstract:
  In multi-object stochastic systems, the issue of sensor management is a
theoretically and computationally challenging problem. In this paper, we
present a novel random finite set (RFS) approach to the multi-target sensor
management problem within the partially observed Markov decision process
(POMDP) framework. The multi-target state is modelled as a multi-Bernoulli RFS,
and the multi-Bernoulli filter is used in conjunction with two different
control objectives: maximizing the expected R\'enyi divergence between the
predicted and updated densities, and minimizing the expected posterior
cardinality variance. Numerical studies are presented in two scenarios where a
mobile sensor tracks five moving targets with different levels of
observability.


title:
Integrable hydrodynamic equations for initial chiral currents and
  infinite hydrodynamic chains from WZNW model and string model of WZNW type
  with $SU(2),$ $SO(3),$ $SP(2),$ $SU(\infty)$, $SO(\infty)$, $SP(\infty)$
  constant torsions

abstract:
  The WZNW and string models are considered in the terms of the initial and
invariant chiral currents assuming that the internal and external torsions
coincide (anticoincide) and they are the structure constants of the
$SU(n),SO(n),$ $SP(n)$ Lie algebras. These models are the auxiliary problems in
order to construct integrable equations of hydrodynamic type. It was shown that
the WZNW and string models in terms of invariant chiral currents are integrable
for the constant torsion associated with the structure constants of the
$SU(2),$ $SO(3),$ $SP(2)$ and $SU(3)$ algebras only. The equation of motion for
the density of the first Casimir operator was obtained in the form of the
inviscid Burgers equation. The solution of this equation is presented through
the Lambert function. Also, a new equation of motion for the initial chiral
current was found.
  The integrable infinite hydrodynamic chains obtained from the WZNW and string
models are given in terms of invariant chiral currents with the $SU(2)$,
$SO(3)$, $SP(2)$ and with $SU(\infty)$, $SO(\infty)$, $SP(\infty)$ constant
torsions. Also, the equations of motion for the density of any Casimir operator
and new infinite dimensional equations of hydrodynamic type for the initial
chiral currents through the symmetric structure constant of $SU(\infty)$,
$SO(\infty),$ $SP(\infty)$ algebras are obtained.


title: Triplet Dark Matter from leptogenesis

abstract:
  A triplet dark matter candidate from thermal leptogenesis is considered with
building a model. The model is based on the standard two Higgs doublet model
and seesaw mechanism with Higgs triplets. The parameters (couplings and masses)
are adjusted for the observed small neutrino mass and the leptogenesis. Dark
matter particles can annihilate and decay in this model. The time evolution of
the dark matter number is governed by (co)annihilations in the expanding
universe, and its mass is constrained by the observed relic density. The dark
matter can decay into final states with three leptons (two charged leptons and
one neutrino). We investigate whether the decay in the galaxy can account for
cosmic ray anomalies in the positron and electron spectrum. A noticeable point
is that if the dark matter decays into each lepton with different branching
ratios, cosmic ray anomalies in AMS-02 measurements of the positron fraction
and the Fermi LAT measurements of the electrons-plus-positrons flux could be
simultaneously accounted for from its decay products. The leptogenesis within
this model is studied in an appendix.


title:
On the theory of normalized Shintani L-function and its application to
  Hecke L-function

abstract:
  We define the class of normalized Shintani L-functions of several variables.
Unlike Shintani zeta functions, the normalized Shintani L-function is a
holomorphic function. Moreover it satisfies a good functional equation. We show
that any Hecke L-function of a totally real field can be expressed as a
diagonal part of some normalized Shintani L-function of several variables. This
gives a good several variables generalization of a Hecke L-function of a
totally real field. This also gives a new proof of the functional equation of
the Hecke L-function of a totally real field.


title: Extracting Region of Interest for Palm Print Authentication

abstract:
  Biometrics authentication is an effective method for automatically
recognizing individuals. The authentication consists of an enrollment phase and
an identification or verification phase. In the stages of enrollment known
(training) samples after the pre-processing stage are used for suitable feature
extraction to generate the template database. In the verification stage, the
test sample is similarly pre processed and subjected to feature extraction
modules, and then it is matched with the training feature templates to decide
whether it is a genuine or not. This paper presents use of a region of interest
(ROI) for palm print technology. First some of the existing methods for palm
print identification have been introduced. Then focus has been given on
extraction of a suitable smaller region from the acquired palm print to improve
the identification method accuracy. Several existing work in the topic of
region extraction have been examined. Subsequently, a simple and original
method has then proposed for locating the ROI that can be effectively used for
palm print analysis. The ROI extracted using this new technique is suitable for
different types of processing as it creates a rectangular or square area around
the center of activity represented by the lines, wrinkles and ridges of the
palm print. The effectiveness of the ROI approach has been tested by
integrating it with a texture based identification / authentication system
proposed earlier. The improvement has been shown by comparing the
identification accuracy rate before and after the ROI pre-processing.


title:
Dynamic modelling of hepatitis C virus transmission among people who
  inject drugs: a methodological review

abstract:
  Equipment sharing among people who inject drugs (PWID) is a key risk factor
in infection by hepatitis C virus (HCV). Both the effectiveness and
cost-effectiveness of interventions aimed at reducing HCV transmission in this
population (such as opioid substitution therapy, needle exchange programs or
improved treatment) are difficult to evaluate using field surveys. Ethical
issues and complicated access to the PWID population make it difficult to
gather epidemiological data. In this context, mathematical modelling of HCV
transmission is a useful alternative for comparing the cost and effectiveness
of various interventions. Several models have been developed in the past few
years. They are often based on strong hypotheses concerning the population
structure. This review presents compartmental and individual-based models in
order to underline their strengths and limits in the context of HCV infection
among PWID. The final section discusses the main results of the papers.


title: Laser Doppler Imaging of Microflow

abstract:
  We report a pilot study with a wide-field laser Doppler detection scheme used
to perform laser Doppler anemometry and imaging of particle seeded microflow.
The optical field carrying the local scatterers (particles) dynamic state, as a
consequence of momentum transfer at each scattering event, is analyzed in the
temporal frequencies domain. The setup is based on heterodyne digital
holography, which is used to map the scattered field in the object plane at a
tunable frequency with a multipixel detector. We show that wide-field
heterodyne laser Doppler imaging can be used for quantitative microflow
diagnosis; in the presented study, maps of the first-order moment of the
Doppler frequency shift are used as a quantitative and directional estimator of
the Doppler signature of particles velocity.


title:
The Galactic O-Star Spectroscopic Survey (GOSSS). II. Bright Southern
  Stars

abstract:
  We present the second installment of GOSSS, a massive spectroscopic survey of
Galactic O stars, based on new homogeneous, high signal-to-noise ratio, R ~
2500 digital observations from both hemispheres selected from the Galactic
O-Star Catalog (GOSC). In this paper we include bright stars and other objects
drawn mostly from the first version of GOSC, all of them south of delta = -20
degrees, for a total number of 258 O stars. We also revise the northern sample
of paper I to provide the full list of spectroscopically classified Galactic O
stars complete to B = 8, bringing the total number of published GOSSS stars to
448. Extensive sequences of exceptional objects are given, including the early
Of/WN, O Iafpe, Ofc, ON/OC, Onfp, Of?p, and Oe types, as well as
double/triple-lined spectroscopic binaries. The new spectral subtype O9.2 is
also discussed. The magnitude and spatial distributions of the observed sample
are analyzed. We also present new results from OWN, a multi-epoch
high-resolution spectroscopic survey coordinated with GOSSS that is assembling
the largest sample of Galactic spectroscopic massive binaries ever attained.
The OWN data combined with additional information on spectroscopic and visual
binaries from the literature indicate that only a very small fraction (if any)
of the stars with masses above 15-20 M_Sol are born as single systems. In the
future we will publish the rest of the GOSSS survey, which is expected to
include over 1000 Galactic O stars.


title: Electronic structure of CaFe2As2

abstract:
  We investigate the electronic structure of CaFe$_2$As$_2$ using high
resolution photoemission spectroscopy. Experimental results exhibit three
energy bands crossing the Fermi level making hole pockets around the
$\Gamma$-point. Temperature variation reveal a gradual shift of an energy band
away from the Fermi level with the decrease in temperature in addition to the
spin density wave (SDW) transition induced Fermi surface reconstruction of the
second energy band across SDW transition temperature. The hole pocket in the
former case eventually disappears at lower temperatures while the hole Fermi
surface of the third energy band possessing finite $p$ orbital character
survives till the lowest temperature studied. These results reveal signature of
a complex charge redistribution among various energy bands as a function of
temperature that might be associated to the exotic properties of this system.


title: The Cauchy-Schwarz divergence for Poisson point processes

abstract:
  In this paper, we extend the notion of Cauchy-Schwarz divergence to point
processes and establish that the Cauchy-Schwarz divergence between the
probability densities of two Poisson point processes is half the squared
$\mathbf{L^{2}}$-distance between their intensity functions. Extension of this
result to mixtures of Poisson point processes and, in the case where the
intensity functions are Gaussian mixtures, closed form expressions for the
Cauchy-Schwarz divergence are presented. Our result also implies that the
Bhattachryaa distance between the probability distributions of two Poisson
point processes is equal to the square of the Hellinger distance between their
intensity measures. We illustrate the result via a sensor management
application where the system states are modeled as point processes.


title:
Ultimate communication capacity of quantum optical channels by solving
  the Gaussian minimum-entropy conjecture

abstract:
  Optical channels, such as fibers or free-space links, are ubiquitous in
today's telecommunication networks. They rely on the electromagnetic field
associated with photons to carry information from one point to another in
space. As a result, a complete physical model of these channels must
necessarily take quantum effects into account in order to determine their
ultimate performances. Specifically, Gaussian photonic (or bosonic) quantum
channels have been extensively studied over the past decades given their
importance for practical purposes. In spite of this, a longstanding conjecture
on the optimality of Gaussian encodings has yet prevented finding their
communication capacity. Here, this conjecture is solved by proving that the
vacuum state achieves the minimum output entropy of a generic Gaussian bosonic
channel. This establishes the ultimate achievable bit rate under an energy
constraint, as well as the long awaited proof that the single-letter classical
capacity of these channels is additive. Beyond capacities, it also has broad
consequences in quantum information sciences.


title:
Generating continuous variable entangled states for quantum
  teleportation using a superposition of number-conserving operations

abstract:
  We investigate the states generated in continuous variable (CV) optical
fields on operating them with a number-conserving operator of the type
$s\hat{a}\hat{a}^\dag + t\hat{a}^\dag\hat{a}$, formed by the generalised
superposition of products of field annihilation ($\hat{a}$) and creation
($\hat{a}^\dag$) operators, with $s^2+t^2=1$. Such an operator is
experimentally realizable and can be suitably manipulated to generate
nonclassical optical states when applied on single- and two-mode coherent,
thermal, and squeezed input states. At low intensities, these nonclassical
states can interact with a secondary mode via a linear optical device to
generate two-mode discrete entangled states, which can serve as a resource in
quantum information protocols. The advantage of these operations are tested by
applying the generated entangled states as quantum channels in CV quantum
teleportation, under the Braunstein and Kimble protocol. We observe that, under
these operations, while the average fidelity of CV teleportation is enhanced
for the nonclassical channel formed using input squeezed states, it remains at
the classical threshold for input coherent and thermal states. This is due to
the fact that though these operations can introduce discrete entanglement in
all input states, it enhances the Einstein-Podolosky-Rosen (EPR) correlations
only in the nonclassical squeezed state inputs, leading to an advantage in CV
teleportation. This shows that nonclassical optical states generated using the
above operations on classical coherent and thermal state inputs are not
resourceful for CV teleportation. This investigation could prove useful in
efficient implementation of noisy non-Gaussian channels, formed by linear
operations, in future teleportation protocols.


title: Higher Loop Nonplanar Anomalous Dimensions from Symmetry

abstract:
  In this article we study the action of the one loop dilatation operator on
operators with a classical dimension of order N. These operators belong to the
su(2) sector and are constructed using two complex fields Y and Z. For these
operators non-planar diagrams contribute already at the leading order in N and
the planar and large N limits are distinct. The action of the one loop and the
two loop dilatation operator reduces to a set of decoupled oscillators and
factorizes into an action on the Z fields and an action on the Y fields. Direct
computation has shown that the action on the Y fields is the same at one and
two loops. In this article, using the su(2) symmetry algebra as well as
structural features of field theory, we give compelling evidence that the
factor in the dilatation operator that acts on the Ys is given by the one loop
expression, at any loop order.


title: Recent tau physics at BaBar

abstract:
  We report some new results on tau decays obtained by the BaBar collaboration
using 468 inverse femtobarn of electron-positron collisions recorded at the
PEP-II asymmetric collider at Stanford Linear Accelerator Center. First We will
show the results for the branching fractions for the decay of the tau to a
charged hadron and two neutral kaons and the branching fractions for
high-multiplicity decays with 3 or 5 charged particles in the final state,
either pions or kaons. We will then show the results for the search of second
class hadronic current decays involving eta-prime mesons and the invariant mass
spectra for tau decays to three charged particles, either pions or kaons.


title:
OverFeat: Integrated Recognition, Localization and Detection using
  Convolutional Networks

abstract:
  We present an integrated framework for using Convolutional Networks for
classification, localization and detection. We show how a multiscale and
sliding window approach can be efficiently implemented within a ConvNet. We
also introduce a novel deep learning approach to localization by learning to
predict object boundaries. Bounding boxes are then accumulated rather than
suppressed in order to increase detection confidence. We show that different
tasks can be learned simultaneously using a single shared network. This
integrated framework is the winner of the localization task of the ImageNet
Large Scale Visual Recognition Challenge 2013 (ILSVRC2013) and obtained very
competitive results for the detection and classifications tasks. In
post-competition work, we establish a new state of the art for the detection
task. Finally, we release a feature extractor from our best model called
OverFeat.


title: Subleading corrections to the Double Coset Ansatz preserve integrability

abstract:
  In this article we compute the anomalous dimensions for a class of operators,
belonging to the SU(3) sector of the theory, that have a bare dimension of
order N. For these operators the large N limit and the planar limit are
distinct and summing only the planar diagrams will not capture the large N
dynamics. Although the spectrum of anomalous dimensions has been computed for
this class of operators, previous studies have neglected certain terms which
were argued to be small. After dropping these terms diagonalizing the
dilatation operator reduces to diagonalizing a set of decoupled oscillators. In
this article we explicitly compute the terms which were neglected previously
and show that diagonalizing the dilatation operator still reduces to
diagonalizing a set of decoupled oscillators.


title: Four approaches to hydrodynamic Green's functions -- the Oseen tensors

abstract:
  We present four different ways of deriving the Oseen tensor which is the
fundamental solution to the Stokes equations for an incompressible viscous
fluid. This solution corresponds to a point force acting on an infinite fluid.
The derivations follow the books of Kim & Karilla, Zapryanov & Tabakova, Dhont,
and Pozrikidis.


title:
From Filamentary Networks to Dense Cores in Molecular Clouds: Toward a
  New Paradigm for Star Formation

abstract:
  Recent studies of the nearest star-forming clouds of the Galaxy at
submillimeter wavelengths with the Herschel Space Observatory have provided us
with unprecedented images of the initial and boundary conditions of the star
formation process. The Herschel results emphasize the role of interstellar
filaments in the star formation process and connect remarkably well with nearly
a decade's worth of numerical simulations and theory that have consistently
shown that the ISM should be highly filamentary on all scales and star
formation is intimately related to self-gravitating filaments. In this review,
we trace how the apparent complexity of cloud structure and star formation is
governed by relatively simple universal processes - from filamentary clumps to
galactic scales. We emphasize two crucial and complementary aspects: (i) the
key observational results obtained with Herschel over the past three years,
along with relevant new results obtained from the ground on the kinematics of
interstellar structures, and (ii) the key existing theoretical models and the
many numerical simulations of interstellar cloud structure and star formation.
We then synthesize a comprehensive physical picture that arises from the
confrontation of these observations and simulations.


title:
Solutions alg\'ebriques. Solutions alg\'ebriques partielles des
  \'equations isomonodromiques sur les courbes de genre $2$

abstract:
  On \'etudie la possibilit\'e de construire des solutions alg\'ebriques
partielles des \'equations d'isomonodromie pour les connections holomorphes de
rang $2$ sur les courbes de genre $2$ en adaptant la m\'ethode d'Andreev et
Kitaev par les familles de Hurwitz. Nous classifions tous les cas o\`u la
connection est \`a monodromie Zariski dense.


title: The stochastic porous media equation in $\R^d$

abstract:
  Existence and uniqueness of solutions to the stochastic porous media equation
$dX-\D\psi(X) dt=XdW$ in $\rr^d$ are studied. Here, $W$ is a Wiener process,
$\psi$ is a maximal monotone graph in $\rr\times\rr$ such that $\psi(r)\le
C|r|^m$, $\ff r\in\rr$, $W$ is a coloured Wiener process. In this general case
the dimension is restricted to $d\ge 3$, the main reason being the absence of a
convenient multiplier result in the space
$\calh=\{\varphi\in\mathcal{S}'(\rr^d);\ |\xi|(\calf\varphi)(\xi)\in
L^2(\rr^d)\}$, for $d\le2$. When $\psi$ is Lipschitz, the well-posedness,
however, holds for all dimensions on the classical Sobolev space
$H^{-1}(\rr^d)$. If $\psi(r)r\ge\rho|r|^{m+1}$ and $m=\frac{d-2}{d+2}$, we
prove the finite time extinction with strictly positive probability.


title: Optimal $L^p$ Hardy inequalities

abstract:
  Let $\mathcal{Q}(\varphi):=\int_\Omega \big(|\nabla
\varphi|^p+V|\varphi|^p\big)\dnu$ on $\core$, and assume that $\mathcal{Q}\geq
0$. The aim of the paper is to obtain ''as large as possible" nonnegative
(optimal) Hardy-type weight $W$ satisfying $$\mathcal{Q}(\varphi)\geq
\int_{\Omega} W|\varphi|^p\dnu \quad\forall \varphi\in\core,$$ on punctured
domains $\Omega$.


title: A dynamical system approach to Heisenberg Uniqueness Pairs

abstract:
  Let $\Lambda$ be a set of lines in $\mathbb{R}^2$ that intersect at the
origin. For $\Gamma\subset\mathbb{R}^2$ a smooth curve, we denote by
$\mathcal{A}\mathcal{C}(\Gamma)$ the subset of finite measures on $\Gamma$ that
are absolutely continuous with respect to arc length on $\Gamma$. For such a
$\mu$, $\widehat{\mu}$ denotes the Fourier transform of $\mu$. Following
Hendenmalm and Montes-Rodr\'iguez, we will say that $(\Gamma,\Lambda)$ is a
Heisenberg Uniqueness Pair if $\mu\in\mathcal{A}\mathcal{C}(\Gamma)$ is such
that $\widehat{\mu}=0$ on $\Lambda$, then $\mu=0$. The aim of this paper is to
provide new tools to establish this property. To do so, we will reformulate the
fact that $\widehat{\mu}$ vanishes on $\Lambda$ in terms of an invariance
property of $\mu$ induced by $\Lambda$. This leads us to a dynamical system on
$\Gamma$ generated by $\Lambda$. The investigation of this dynamical system
allows us to establish that $(\Gamma,\Lambda)$ is a Heisenberg Uniqueness Pair.
This way we both unify proofs of known cases (circle, parabola, hyperbola) and
obtain many new examples. This method also allows to have a better geometric
intuition on why $(\Gamma,\Lambda)$ is a Heisenberg Uniqueness Pair.


title:
Effects of space structure and combination therapies on phenotypic
  heterogeneity and drug resistance in solid tumors

abstract:
  Histopathological evidence supports the idea that the emergence of phenotypic
heterogeneity and resistance to cytotoxic drugs can be considered as a process
of adaptation, or evolution, in tumor cell populations. In this framework, can
we explain intra-tumor heterogeneity in terms of cell adaptation to local
conditions? How do anti-cancer therapies affect the outcome of cell competition
for nutrients within solid tumors? Can we overcome the emergence of resistance
and favor the eradication of cancer cells by using combination therapies?
Bearing these questions in mind, we develop a model describing cell dynamics
inside a tumor spheroid under the effects of cytotoxic and cytostatic drugs.
Cancer cells are assumed to be structured as a population by two real variables
standing for space position and the expression level of a cytotoxic resistant
phenotype. The model takes explicitly into account the dynamics of resources
and anti-cancer drugs as well as their interactions with the cell population
under treatment. We analyze the effects of space structure and combination
therapies on phenotypic heterogeneity and chemotherapeutic resistance.
Furthermore, we study the efficacy of combined therapy protocols based on
constant infusion and/or bang-bang delivery of cytotoxic and cytostatic drugs.


title:
Finite-dimensional pointed Hopf algebras over finite simple groups of
  Lie type I. Non-semisimple classes in PSL(n,q)

abstract:
  We show that Nichols algebras of most simple Yetter-Drinfeld modules over the
projective special linear group over a finite field, corresponding to
non-semisimple orbits, have infinite dimension. We spell out a new criterium to
show that a rack collapses.


title:
Extensions of line bundles and Brill--Noether loci of rank-two vector
  bundles on a general curve

abstract:
  In this paper we study Brill-Noether loci for rank-two vector bundles and
describe the general member of some components as suitable extensions of line
bundles.


title:
Molecular-Level Switching of Polymer/Nanocrystal Non-Covalent
  Interactions and Application in Hybrid Solar Cells

abstract:
  Hy brid composites obtained upon blending conjugated polymers and colloidal
inorganic semiconductor nanocrystals are regarded as attractive photo-active
materials for optoelectronic applications. Here we demonstrate that tailoring
nanocrystal surface chemistry permits to exert control on non-covalent bonding
and electronic interactions between organic and inorganic components. The
pendant moieties of organic ligands at the nanocrystal surface do not merely
confer colloidal stability while hindering charge separation and transport, but
drastically impact morphology of hybrid composites during formation from blend
solutions. The relevance of our approach to photovoltaic applications is
demonstrated for composites based on poly(3-hexylthiophene) and Pbs
nanocrystals, considered as inadequate before the submission of this
manuscript, which enable the fabrication of hybrid solar cells displaying a
power conversion efficiency that reaches 3 %. Upon (quasi)steady-state and
time-resolved analisys of the photo-induced processes in the nanocomposites and
their organic and inorganic components, we ascertained that electron transfer
occurs at the hybrid interface yielding long-lived separated charge carriers,
whereas interfacial hole transfer appears slow. Here we provide a reliable
alternative aiming at gaining control over macroscopic optoelectronic
properties of polymer/nanocrystal composites by acting at the molecular-level
via ligands' pendant moieties, thus opening new possibilities towards efficient
solution-processed hybrid solar cells.


title: Gauge Fields in the 5D Gravity-Scalar Standing Wave Braneworld

abstract:
  We investigate localization problem for gauge fields within the 5D standing
wave braneworld with real scalar field and show that there exist normalizable
vector field zero modes on the brane.


title: Generating Matrix Identities and Proof Complexity

abstract:
  Motivated by the fundamental lower bounds questions in proof complexity, we
initiate the study of matrix identities as hard instances for strong proof
systems. A matrix identity of $d \times d$ matrices over a field $\mathbb{F}$,
is a non-commutative polynomial $f(x_1,\ldots,x_n)$ over $\mathbb{F}$ such that
$f$ vanishes on every $d \times d$ matrix assignment to its variables.
  We focus on arithmetic proofs, which are proofs of polynomial identities
operating with arithmetic circuits and whose axioms are the polynomial-ring
axioms (these proofs serve as an algebraic analogue of the Extended Frege
propositional proof system; and over $GF(2)$ they constitute formally a
sub-system of Extended Frege [HT12]). We introduce a decreasing in strength
hierarchy of proof systems within arithmetic proofs, in which the $d$th level
is a sound and complete proof system for proving $d \times d$ matrix identities
(over a given field). For each level $d>2$ in the hierarchy, we establish a
proof-size lower bound in terms of the number of variables in the matrix
identity proved: we show the existence of a family of matrix identities $f_n$
with $n$ variables, such that any proof of $f_n=0$ requires $\Omega(n^{2d})$
number of lines. The lower bound argument uses fundamental results from the
theory of algebras with polynomial identities together with a generalization of
the arguments in [Hru11].
  We then set out to study matrix identities as hard instances for (full)
arithmetic proofs. We present two conjectures, one about non-commutative
arithmetic circuit complexity and the other about proof complexity, under which
up to exponential-size lower bounds on arithmetic proofs (in terms of the
arithmetic circuit size of the identities proved) hold. Finally, we discuss the
applicability of our approach to strong propositional proof systems such as
Extended Frege.


title:
Extinction of solutions to a class of fast diffusion systems with
  nonlinear sources

abstract:
  In this paper, the finite time extinction of solutions to the fast diffusion
system $u_t=\mathrm{div}(|\nabla u|^{p-2}\nabla u)+v^m$,
$v_t=\mathrm{div}(|\nabla v|^{q-2}\nabla v)+u^n$ is investigated, where
$1<p,q<2$, $m,n>0$ and $\Omega\subset \mathbb{R}^N\ (N\geq1)$ is a bounded
smooth domain. After establishing the local existence of weak solutions, the
authors show that if $mn>(p-1)(q-1)$, then any solution vanishes in finite time
provided that the initial data are ``comparable"; if $mn=(p-1)(q-1)$ and
$\Omega$ is suitably small, then the existence of extinction solutions for
small initial data is proved by using the De Giorgi iteration process and
comparison method. On the other hand, for $1<p=q<2$ and $mn<(p-1)^2$, the
existence of at least one non-extinction solution for any positive smooth
initial data is proved.


title:
Metal enhanced fluorescence in rare earth doped plasmonic core-shell
  nanoparticles

abstract:
  We theoretically and numerically investigate metal enhanced fluorescence of
plasmonic core-shell nanoparticles doped with rare earth (RE) ions. Particle
shape and size are engineered to maximize the average enhancement factor (AEF)
of the overall doped shell. We show that the highest enhancement (11 in the
visible and 7 in the near-infrared) are achieved by tuning either the dipolar
or quadrupolar particle resonance to the rare earth ions excitation wavelength.
Additionally, the calculated AEFs are compared to experimental data reported in
the literature, obtained in similar conditions (plasmon mediated enhancement)
or when a metal-RE energy transfer mechanism is involved.


title:
Probing the localization length of photo-generated charges in organic
  materials

abstract:
  We report a new experimental method to measure the localization length of
photo-generated carriers in an organic donor-acceptor photovoltaic blend by
comparing their dielectric and electron spin-resonance susceptibilities which
are simultaneously measured by monitoring the resonance frequency of a
superconducting resonator. We show that at cryogenic temperatures excitons are
dissociated into long lived states, but that these are confined within a
separation of around $4\;{\rm nm}$. We determine the Debye and recombination
times, showing the coexistence of a fast electrical response corresponding to
delocalized motion, with glass-like recombination kinetics.