title: Convergence rate of stochastic k-means

abstract:
  We analyze online \cite{BottouBengio} and mini-batch \cite{Sculley} $k$-means
variants. Both scale up the widely used $k$-means algorithm via stochastic
approximation, and have become popular for large-scale clustering and
unsupervised feature learning. We show, for the first time, that starting with
any initial solution, they converge to a "local optimum" at rate
$O(\frac{1}{t})$ (in terms of the $k$-means objective) under general
conditions. In addition, we show if the dataset is clusterable, when
initialized with a simple and scalable seeding algorithm, mini-batch $k$-means
converges to an optimal $k$-means solution at rate $O(\frac{1}{t})$ with high
probability. The $k$-means objective is non-convex and non-differentiable: we
exploit ideas from recent work on stochastic gradient descent for non-convex
problems \cite{ge:sgd_tensor, balsubramani13} by providing a novel
characterization of the trajectory of $k$-means algorithm on its solution
space, and circumvent the non-differentiability problem via geometric insights
about $k$-means update.


title: The Structure of the Local Hot Bubble

abstract:
  DXL (Diffuse X-rays from the Local Galaxy) is a sounding rocket mission
designed to quantify and characterize the contribution of Solar Wind Charge
eXchange (SWCX) to the Diffuse X-ray Background and study the properties of the
Local Hot Bubble (LHB). Based on the results from the DXL mission, we
quantified and removed the contribution of SWCX to the diffuse X-ray background
measured by the ROSAT All Sky Survey (RASS). The "cleaned" maps were used to
investigate the physical properties of the LHB. Assuming thermal ionization
equilibrium, we measured a highly uniform temperature distributed around
kT=0.097 keV+/-0.013 keV (FWHM)+/-0.006 keV (systematic). We also generated a
thermal emission measure map and used it to characterize the three-dimensional
(3D) structure of the LHB which we found to be in good agreement with the
structure of the local cavity measured from dust and gas.


title: Cost-Sensitive Deep Learning with Layer-Wise Cost Estimation

abstract:
  While deep neural networks have succeeded in several visual applications,
such as object recognition, detection, and localization, by reaching very high
classification accuracies, it is important to note that many real-world
applications demand varying costs for different types of misclassification
errors, thus requiring cost-sensitive classification algorithms. Current models
of deep neural networks for cost-sensitive classification are restricted to
some specific network structures and limited depth. In this paper, we propose a
novel framework that can be applied to deep neural networks with any structure
to facilitate their learning of meaningful representations for cost-sensitive
classification problems. Furthermore, the framework allows end-to-end training
of deeper networks directly. The framework is designed by augmenting auxiliary
neurons to the output of each hidden layer for layer-wise cost estimation, and
including the total estimation loss within the optimization objective.
Experimental results on public benchmark visual data sets with two cost
information settings demonstrate that the proposed framework outperforms
state-of-the-art cost-sensitive deep learning models.


title:
Testing the dark matter subhalo hypothesis of the gamma-ray source 3FGL
  J2212.5+0703

abstract:
  N-body simulations predict that galaxies at the Milky Way scale host a large
number of dark matter (DM) subhalos. Some of these subhalos, if they are
massive enough or close enough to the Earth, might be detectable in $\gamma$
rays due to the DM annihilation. 3FGL J2212.5+0703, an unidentified gamma-ray
source, has been suggested to be the counterpart candidate of a DM subhalo by
Bertoni et al. (2015, 2016). In this work we analyze the Fermi-LAT Pass 8 data
of 3FGL J2212.5+0703 to independently test the DM subhalo hypothesis of this
source. In order to suppress the possible contamination from two nearby
very-bright blazars, we just take into account the front-converting gamma-rays
which have better angular resolutions than that of the back-converting photons.
In addition to the spatial distribution analysis, we have extended the spectrum
analysis down to the energies of $\sim 100$ MeV, and thoroughly examined the
variability of the emission during the past 8 years. We confirm that 3FGL
J2212.5+0703 is a steady and spatially-extended gamma-ray emitter at a high
confidence level. The spectrum is well consistent with that expected from DM
annihilation into $b\bar{b}$. The introduction of a phenomenological
LogParabola spectrum just improves the fit slightly. All these results suggest
that 3FGL J2212.5+0703 could be indicative of a DM subhalo.


title:
Machine Learning Approach for Skill Evaluation in Robotic-Assisted
  Surgery

abstract:
  Evaluating surgeon skill has predominantly been a subjective task.
Development of objective methods for surgical skill assessment are of increased
interest. Recently, with technological advances such as robotic-assisted
minimally invasive surgery (RMIS), new opportunities for objective and
automated assessment frameworks have arisen. In this paper, we applied machine
learning methods to automatically evaluate performance of the surgeon in RMIS.
Six important movement features were used in the evaluation including
completion time, path length, depth perception, speed, smoothness and
curvature. Different classification methods applied to discriminate expert and
novice surgeons. We test our method on real surgical data for suturing task and
compare the classification result with the ground truth data (obtained by
manual labeling). The experimental results show that the proposed framework can
classify surgical skill level with relatively high accuracy of 85.7%. This
study demonstrates the ability of machine learning methods to automatically
classify expert and novice surgeons using movement features for different RMIS
tasks. Due to the simplicity and generalizability of the introduced
classification method, it is easy to implement in existing trainers.


title: Energy landscape analysis of neuroimaging data

abstract:
  Computational neuroscience models have been used for understanding neural
dynamics in the brain and how they may be altered when physiological or other
conditions change. We review and develop a data-driven approach to neuroimaging
data called the energy landscape analysis. The methods are rooted in
statistical physics theory, in particular the Ising model, also known as the
(pairwise) maximum entropy model and Boltzmann machine. The methods have been
applied to fitting electrophysiological data in neuroscience for a decade, but
their use in neuroimaging data is still in its infancy. We first review the
methods and discuss some algorithms and technical aspects. Then, we apply the
methods to functional magnetic resonance imaging data recorded from healthy
individuals to inspect the relationship between the accuracy of fitting, the
size of the brain system to be analyzed, and the data length.


title: S3Pool: Pooling with Stochastic Spatial Sampling

abstract:
  Feature pooling layers (e.g., max pooling) in convolutional neural networks
(CNNs) serve the dual purpose of providing increasingly abstract
representations as well as yielding computational savings in subsequent
convolutional layers. We view the pooling operation in CNNs as a two-step
procedure: first, a pooling window (e.g., $2\times 2$) slides over the feature
map with stride one which leaves the spatial resolution intact, and second,
downsampling is performed by selecting one pixel from each non-overlapping
pooling window in an often uniform and deterministic (e.g., top-left) manner.
Our starting point in this work is the observation that this regularly spaced
downsampling arising from non-overlapping windows, although intuitive from a
signal processing perspective (which has the goal of signal reconstruction), is
not necessarily optimal for \emph{learning} (where the goal is to generalize).
We study this aspect and propose a novel pooling strategy with stochastic
spatial sampling (S3Pool), where the regular downsampling is replaced by a more
general stochastic version. We observe that this general stochasticity acts as
a strong regularizer, and can also be seen as doing implicit data augmentation
by introducing distortions in the feature maps. We further introduce a
mechanism to control the amount of distortion to suit different datasets and
architectures. To demonstrate the effectiveness of the proposed approach, we
perform extensive experiments on several popular image classification
benchmarks, observing excellent improvements over baseline models. Experimental
code is available at https://github.com/Shuangfei/s3pool.


title:
Synthesis, Optical, and Magnetic Properties of Ba$_2$Ni$_3$F$_{10}$
  Nanowires

abstract:
  A low temperature hydrothermal route has been developed, and pure phase
Ba$_2$Ni$_3$F$_{10}$ nanowires have been successfully prepared under the
optimized conditions. Under the 325 nm excitation, the Ba$_2$Ni$_3$F$_{10}$
nanowires exhibit three emission bands with peak positions locating at 360 nm,
530 nm, and 700 nm, respectively. Combined with the first-principles
calculations, the photoluminescence property can be explained by the electron
transitions between the t2g and eg orbitals. Clear hysteresis loops observed
below the temperature of 60 K demonstrates the weak ferromagnetism in
Ba$_2$Ni$_3$F$_{10}$ nanowires, which has been attributed to the surface strain
of nanowires. Exchange bias with blocking temperature of 55 K has been
observed, which originates from the magnetization pinning under the cooling
field due to antiferromagnetic core/weak ferromagnetic shell structure of
Ba2Ni3F10 nanowires.


title:
Neutrino-nucleon scattering in supernova matter from the virial
  expansion

abstract:
  We generalize our virial approach to study the neutral current neutrino
response of nuclear matter at low densities. In the long-wavelength limit, the
virial expansion makes model-independent predictions for neutrino-nucleon
scattering rates and the density S_V and spin S_A responses. We find S_A is
significantly reduced from one even at low densities. We provide a simple fit
S_A^f(n,T,Y_p) of the axial response as a function of density n, temperature T
and proton fraction Y_p. This fit reproduces our model independent virial
results at low densities and reproduces the Burrows and Sawyer random phase
approximation (RPA) results at high densities. Our fit can be incorporated into
supernova simulations in a straight forward manner. Preliminary one dimensional
supernova simulations suggest that the reduction in the axial response may
enhance neutrino heating rates in the gain region during the accretion phase of
a core-collapse supernovae.


title: Training Spiking Deep Networks for Neuromorphic Hardware

abstract:
  We describe a method to train spiking deep networks that can be run using
leaky integrate-and-fire (LIF) neurons, achieving state-of-the-art results for
spiking LIF networks on five datasets, including the large ImageNet ILSVRC-2012
benchmark. Our method for transforming deep artificial neural networks into
spiking networks is scalable and works with a wide range of neural
nonlinearities. We achieve these results by softening the neural response
function, such that its derivative remains bounded, and by training the network
with noise to provide robustness against the variability introduced by spikes.
Our analysis shows that implementations of these networks on neuromorphic
hardware will be many times more power-efficient than the equivalent
non-spiking networks on traditional hardware.


title:
A randomized intertial primal-dual fixed point algorithm for monotone
  inclusions

abstract:
  In this paper, we propose a randomized intertial block-coordinate primaldual
fixed point algorithm to solve a wide array of monotone inclusion problems base
on the modification of the heavy ball method of Nesterov. These methods rely on
a sweep of blocks of variables which are activated at each iteration according
to a random rule. To this end we formulate the inertial version of the
Krasnosel'skii-Mann algorithm for approximating the set of fixed points of a
quasinonexpansive operator, for which we also provide an exhaustive convergence
analysis. As a by-product, we can obtain some intertial block-coordinate
operator splitting methods for solving composite monotone inclusion and convex
minimization problems.


title:
Magnetism induced by nonlocal spin-entangled electrons in a
  superconducting spin-valve

abstract:
  In the traditional view, the magnetic moment appearing in the superconducting
region is induced by equal-spin triplet superconducting correlations in
superconductor ($S$) ferromagnet ($F$) heterostructure with noncollinear
magnetization. In this paper, we represent that in $NSF_1F_2$
($N$--normal-metal) spin-valve structure the induced magnetic moment emerging
in both the $S$ and $N$ regions can also be generated by Cooper pair splitting:
one electron coherently tunnels from the $S$ layer into the $F_1$ layer, and
the other one stays in the $S$ layer or tunnels into the $N$ layer. Two
electrons are spatially separated from each other but their total spin ground
state is entangled in this process. In contrast, the magnetic moment induced by
the equal-spin triplet correlations hardly penetrates from the $S$ layer into
the $N$ layer. In particular, by tuning the size of the exchange field and the
thickness of the $F_1$ layer, one may control the direction of the induced
magnetic moment in the $N$ layer. This interesting phenomenon can be attributed
to the phase-shift obtained by the spin-entangled electrons. Our theoretical
proposal will offer an effective way to control the entanglement of the
nonlocal electrons, and also may provide possible explanations for previous and
recent experimental observations [Stamopoulos et al 2005 Phys. Rev. B 72
212514; Ovsyannikov et al 2016 J. Exp. Theor. Phys. 122 738; Flokstra et al
2016 Nat. Phys. 12 57].


title:
The effect of clay on the mechanical properties of epoxy resins
  subjected to hygrothermal ageing

abstract:
  Epoxy polymers are an important class of material for use in various
applications. Due to their hydrophilic nature, epoxy resins tend to absorb
moisture. Absorption of moisture degrades the functional, structural and
mechanical properties. For polymers, it is known that moisture absorption can
lead to both reversible and irreversible changes. In this study, the combined
effect of moisture and elevated temperature on the mechanical properties of
Epon 862 and its nanocomposites were investigated. The extent of permanent
damage on fracture toughness and flexural properties of epoxy, due to the
aggressive degradation provided by hygrothermal ageing, was determined by
drying the epoxy and their clay/epoxy nanocomposites after moisture absorption.
From the investigation it was found that, hygrothermal ageing has detrimental
effect on mechanical properties of both neat polymer and clay/polymer
nanocomposite. Significant permanent damage was observed for fracture toughness
and modulus, while the extent of permanent damage was less significant for
flexural strength.


title: Ultra-peripheral Collisions with the ATLAS Detector

abstract:
  The first ATLAS measurement of ultra-peripheral collisions is described.
Dimuon pairs from photon--photon scattering have been measured with data of
Pb+Pb collisions at $\sqrt{s_{\mathrm{NN}}} = 5.02$ TeV taken with the ATLAS
detector at the LHC. The measured cross-section is presented as a function of
dimuon invariant mass and rapidity and is well described by STARLIGHT 1.1
calculations. This measurement paves the way for new studies of photon-induced
reactions at the LHC.


title:
A Semi-Markov Switching Linear Gaussian Model for Censored Physiological
  Data

abstract:
  Critically ill patients in regular wards are vulnerable to unanticipated
clinical dete- rioration which requires timely transfer to the intensive care
unit (ICU). To allow for risk scoring and patient monitoring in such a setting,
we develop a novel Semi- Markov Switching Linear Gaussian Model (SSLGM) for the
inpatients' physiol- ogy. The model captures the patients' latent clinical
states and their corresponding observable lab tests and vital signs. We present
an efficient unsupervised learn- ing algorithm that capitalizes on the
informatively censored data in the electronic health records (EHR) to learn the
parameters of the SSLGM; the learned model is then used to assess the new
inpatients' risk for clinical deterioration in an online fashion, allowing for
timely ICU admission. Experiments conducted on a het- erogeneous cohort of
6,094 patients admitted to a large academic medical center show that the
proposed model significantly outperforms the currently deployed risk scores
such as Rothman index, MEWS, SOFA and APACHE.


title:
A Lynden-Bell integral estimator for the tail index of right-truncated
  data with a random threshold

abstract:
  By means of a Lynden-Bell integral with deterministic threshold, Worms and
Worms [A Lynden-Bell integral estimator for extremes of randomly truncated
data. Statist. Probab. Lett. 2016; 109: 106-117] recently introduced an
asymptotically normal estimator of the tail index for randomly right-truncated
Pareto-type data. In this context, we consider the random threshold case to
derive a Hill-type estimator and establish its consistency and asymptotic
normality. A simulation study is carried out to evaluate the finite sample
behavior of the proposed estimator.


title:
Variational Deep Embedding: An Unsupervised and Generative Approach to
  Clustering

abstract:
  Clustering is among the most fundamental tasks in computer vision and machine
learning. In this paper, we propose Variational Deep Embedding (VaDE), a novel
unsupervised generative clustering approach within the framework of Variational
Auto-Encoder (VAE). Specifically, VaDE models the data generative procedure
with a Gaussian Mixture Model (GMM) and a deep neural network (DNN): 1) the GMM
picks a cluster; 2) from which a latent embedding is generated; 3) then the DNN
decodes the latent embedding into observables. Inference in VaDE is done in a
variational way: a different DNN is used to encode observables to latent
embeddings, so that the evidence lower bound (ELBO) can be optimized using
Stochastic Gradient Variational Bayes (SGVB) estimator and the
reparameterization trick. Quantitative comparisons with strong baselines are
included in this paper, and experimental results show that VaDE significantly
outperforms the state-of-the-art clustering methods on 4 benchmarks from
various modalities. Moreover, by VaDE's generative nature, we show its
capability of generating highly realistic samples for any specified cluster,
without using supervised information during training. Lastly, VaDE is a
flexible and extensible framework for unsupervised generative clustering, more
general mixture models than GMM can be easily plugged in.


title: Bridging the time scales of single-cell and population dynamics

abstract:
  How are granular details of stochastic growth and division of individual
cells reflected in smooth deterministic growth of population numbers? We
provide an integrated, multiscale perspective of microbial growth dynamics by
formulating a data-validated theoretical framework that accounts for
observables at both single-cell and population scales. We derive exact
analytical complete time-dependent solutions to cell-age distributions and
population growth rates as functionals of the underlying interdivision time
distributions, for symmetric and asymmetric cell division. These results
provide insights into the surprising implications of stochastic single-cell
dynamics for population growth. Using our results for asymmetric division, we
deduce the time to transition from the reproductively quiescent (swarmer) to
replication-competent (stalked) stage of the {\em Caulobacter crescentus}
lifecycle. Remarkably, population numbers can spontaneously oscillate with
time. We elucidate the physics leading to these population oscillations. For
{\em C. crescentus} cells, we show that a simple measurement of the population
growth rate, for a given growth condition, is sufficient to characterize the
condition-specific cellular unit of time, and thus yields the mean
(single-cell) growth and division timescales, fluctuations in cell division
times, the cell age distribution, and the quiescence timescale.


title: Positive Feedback and Synchronized Bursts in Neuronal Cultures

abstract:
  Synchronized bursts (SBs) with complex structures are common in neuronal
cultures. Although the origin of SBs is still unclear, they have been studied
for their information processing capabilities. Here, we investigate the
properties of these SBs in a culture on multi-electrode array system. We find
that structures of these SBs are related to the different developmental stages
of the cultures. A model based on short term synaptic plasticity, recurrent
connections and astrocytic recycling of neurotransmitters has been developed
successfully to understand these structures. A phase diagram obtained from this
model shows that networks exhibiting SBs are in an oscillatory state due to
large enough positive feedback provided by synaptic facilitation and recurrent
connections. In this model, the structures of the SBs are the results of
intrinsic synaptic interactions; not information stored in the network.


title: Nearly cloaking for the elasticity system with residual stress

abstract:
  The nearly cloaking via transformation optics approach for the isotropic
elastic wave fields is considered. This work extends the study of the nearly
cloaking scheme to the elasticity system with residual stress in \mathbb{R}^{N}
for N=2,3, which is an anisotropic elasticity system. It is worth to mention
that there are no minor symmetric properties for the elastic tensor with
residual stress and this system is invariant under a coordinate transformation.
Therefore, we think the elasticity system residual stress model is more natural
than the isotropic elasticity system in designing the elastic cloaking medium
in the physical sense. In addition, the main difficulty of treating this
problem lies in the fact that there are no layer potential theory for the
residual stress system. Instead, we will derive suitable elliptic estimates for
the elasticity system residual stress by comparing with the Lam\'e system to
achieve desired results.


title:
Scalable and Robust Local Community Detection via Adaptive Subgraph
  Extraction and Diffusions

abstract:
  Local community detection, the problem of identifying a set of relevant nodes
nearby a small set of input seed nodes, is an important graph primitive with a
wealth of applications and research activity. Recent approaches include using
local spectral information, graph diffusions, and random walks to determine a
community from input seeds. As networks grow to billions of nodes and exhibit
diverse structures, it is important that community detection algorithms are not
only efficient, but also robust to different structural features.
  Toward this goal, we explore pre-processing techniques and modifications to
existing local methods aimed at improving the scalability and robustness of
algorithms related to community detection. Experiments show that our
modifications improve both speed and quality of existing methods for locating
ground truth communities, and are more robust across graphs and communities of
varying sizes, densities, and diameters. Our subgraph extraction method uses
adaptively selected PageRank parameters to improve on the recall and runtime of
a walk-based pre-processing technique of Li et al. for extracting subgraphs
before searching for a community. We then use this technique to enable the
first scalable implementation of the recent Local Fiedler method of Mahoney et
al. Our experimental evaluation shows our pre-processed version of Local
Fiedler, as well as our novel simplification of the LEMON community detection
framework of Li et al., offer significant speedups over their predecessors and
obtain cluster quality competitive with the state of the art.


title: Central charges of T-dual branes for toric varieties

abstract:
  Given any equivariant coherent sheaf $\mathcal L$ on a compact semi-positive
toric orbifold $\mathcal X$, its SYZ T-dual mirror dual is a Lagrangian brane
in the Landau-Ginzburg mirror. We prove the oscillatory integral of the
equivariant superpotential in the Landau Ginzburg mirror over this Lagrangian
brane is the genus-zero $1$-descendant Gromov-Witten potential with a
Gamma-type class of $\mathcal L$ inserted.


title:
Locomotion of the generalized Purcell's swimmer : Modelling,
  controllability and motion primitives

abstract:
  Micro-robotics at low Reynolds number has been a growing area of research
over the past decade. We propose and study a generalized 3-link robotic swimmer
inspired by the planar Purcell's swimmer. By incorporating out-of-plane motion
of the outer limbs, this mechanism generalizes the planar Purcell's swimmer,
which has been widely studied in the literature. Such an evolution of the
limbs' motion results in the swimmer's base link evolving in a 3-dimensional
space. The swimmer's configuration space admits a trivial principal fiber
bundle structure, which along with the slender body theory at the low Reynolds
number regime, facilitates in obtaining a principal kinematic form of the
equations. We derive a coordinate-free expression for the local form of the
kinematic connection. A novel approach for local controllability analysis of
this 3-dimensional swimmer in the low Reynolds number regime is presented by
employing the controllability results of the planar Purcell's swimmer. This is
followed by control synthesis using the motion primitives approach. We prove
the existence of motion primitives based control sequence for maneuvering the
swimmer's base link whose motion evolves on a Lie group. Using the principal
fiber bundle structure, an algorithm for point to point reconfiguration of the
swimmer is presented. A set of control sequences for translational and
rotational maneuvers is then provided along with numerical simulations.


title: Absorptive pinhole collimators for ballistic Dirac fermions in graphene

abstract:
  Ballistic electrons in solids can have mean free paths far larger than the
smallest features patterned by lithography. This has allowed development and
study of solid-state electron-optical devices such as beam splitters and
quantum point contacts, which have informed our understanding of electron flow
and interactions. Recently, high-mobility graphene has emerged as an ideal
two-dimensional semimetal that hosts unique chiral electron-optical effects due
to its honeycomb crystalline lattice. However, this chiral transport prevents
simple use of electrostatic gates to define electron-optical devices in
graphene. Here, we present a method of creating highly-collimated electron
beams in graphene based on collinear pairs of slits, with absorptive sidewalls
between the slits. By this method, we achieve beams with angular width 18
degrees or narrower, and transmission matching semiclassical predictions.


title:
Superconducting Resonator-Rydberg Atom Hybrid in the Strong Coupling
  Regime

abstract:
  We propose a promising hybrid quantum system, where a highly-excited atom
strongly interacts with a superconducting LC oscillator via the electric field
of capacitor. An external electrostatic field is applied to tune the energy
spectrum of atom. The atomic qubit is implemented by two eigenstates near an
avoided-level crossing in the DC Stark map of Rydberg atom. Varying the
electrostatic field brings the atomic-qubit transition on- or off-resonance to
the microwave resonator, leading to a strong atom-resonator coupling with an
extremely large cooperativity. Like the nonlinearity induced by Josephson
junctions in superconducting circuits, the large atom-resonator interface
disturbs the harmonic potential of resonator, resulting in an artificial
two-level particle. Different universal two-qubit logic gates can also be
performed on our hybrid system within the space where an atomic qubit couples
to a single photon with an interaction strength much larger than any relaxation
rates, opening the door to the cavity-mediated state transmission.


title:
Hopf polyads, Hopf categories and Hopf group monoids viewed as Hopf
  monads

abstract:
  We associate, in a functorial way, a monoidal bicategory $\mathsf{Span}|
\mathcal V$ to any monoidal bicategory $\mathcal V$. Two examples of this
construction are of particular interest: Hopf polyads (due to Brugui\`eres) can
be seen as Hopf monads in $\mathsf{Span}| \mathsf{Cat}$ while Hopf group
monoids in a braided monoidal category $V$ (in the spirit of Turaev and
Zunino), and Hopf categories over $V$ (by Batista, Caenepeel and Vercruysse)
both turn out to be Hopf monads in $\mathsf{Span}| V$. Hopf group monoids and
Hopf categories are Hopf monads on a distinguished type of monoidales fitting
the framework studied recently by B\"ohm and Lack. These examples are related
by a monoidal pseudofunctor $V\to \mathsf{Cat}$.


title: Proximity effects and pair currents in cuprate junctions

abstract:
  Proximity effects and pair currents were measured in epitaxial trilayer
\textit{c-axis} junctions comprise of a $PrBa_2Cu_3O_{7-\delta}$ barrier
sandwiched in between an overdoped $Y_{0.94}Ca_{0.06}Ba_2Cu_3O_{7-\delta}$ and
underdoped $YBa_2Cu_{2.7}Co_{0.3}O_y$ layers. These junctions had two $\rm T_c$
values of $\rm T_c(high)=84-86$ K and $\rm T_c(low)=50-55$ K, allowing
investigation when both electrodes are superconducting, or when only one is
superconducting while the other is in its pseudogap regime. For T below $\rm
T_c(high)$ but much above $\rm T_c(low)$, two distinct proximity effect
transitions were observed in the resistance at two temperature regimes, between
80 and 84 K, and 76 to 80 K. The first is a conventional proximity effect with
the $\rm T_c(high)$ electrode, while the second is a second-order proximity
effect of this electrode with uncorrelated pairs in the pseudogap regime.
Conductance spectra measured between 2 and 86 K showed four different $I_c$
pair currents which were attributed to coherent pairs tunneling through the
barrier below 42 K, to fluctuating pairs current up to $\sim$77 K, and to
proximity pairs current between 77 and 84 K. All pair currents were suppressed
under magnetic fields, with two distinct decay parameters that originated in
the two different electrodes, with a significant suppression observed in the
pseudogap regime.


title:
The classification of simple separable KK-contractible C*-algebras with
  finite nuclear dimension

abstract:
  The class of simple separable KK-contractible (KK-equivalent to $\{0\}$)
C*-algebras which have finite nuclear dimension is shown to classified by the
Elliott invariant. In particular, the class of C*-algebras $A\otimes \mathcal
W$ is classifiable, where $A$ is a simple separable C*-algebra with finite
nuclear dimension and $\mathcal W$ is the simple inductive limit of Razak
algebras with unique trace, which is bounded.


title: Continuous-Time Quantum Walk on Penrose Lattice

abstract:
  In this paper, we study the quantum walk on the 2D Penrose Lattice, which is
intermediate between periodic and disordered structure. Quantum walk on Penrose
Lattice is less efficient in transport comparing to the regular lattices. By
calculating the final remaining probability on the initial nodes and estimating
the low bound. Our results show that the broken of translational symmetry
induces both the localized states and degeneracy of eigenstates at $E=0$, this
two differences from regular lattices influence efficiency of quantum walk.
Also, we observe the transition from inefficient to efficient transport after
introducing the near hopping terms, which suggests that we can adjust the
"hopping strength" and achieve a "phase transition" progress.


title: Possibility and Impossibility of Reliable Broadcast in the Bounded Model

abstract:
  The Reliable Broadcast concept allows an honest party to send a message to
all other parties and to make sure that all honest parties receive this
message. In addition, it allows an honest party that received a message to know
that all other honest parties would also receive the same message. This
technique is important to ensure distributed consistency when facing failures.
  In the current paper, we study the ability to use \RR to consistently
transmit a sequence of input values in an asynchronous environment with a
designated sender. The task can be easily achieved using counters, but cannot
be achieved with a bounded memory facing failures. We weaken the problem and
ask whether the receivers can at least share a common suffix. We prove that in
a standard (lossless) asynchronous system no bounded memory protocol can
guarantee a common suffix at all receivers for every input sequence if a single
party might crash.
  We further study the problem facing transient faults and prove that when
limiting the problem to transmitting a stream of a single value being sent
repeatedly we show a bounded memory self-stabilizing protocol that can ensure a
common suffix even in the presence of transient faults and an arbitrary number
of crash faults. We further prove that this last problem is not solvable in the
presence of a single Byzantine fault. Thus, this problem {\bf separates}
Byzantine behavior from crash faults in an asynchronous environment.


title:
Net-Trim: Convex Pruning of Deep Neural Networks with Performance
  Guarantee

abstract:
  We introduce and analyze a new technique for model reduction for deep neural
networks. While large networks are theoretically capable of learning
arbitrarily complex models, overfitting and model redundancy negatively affects
the prediction accuracy and model variance. Our Net-Trim algorithm prunes
(sparsifies) a trained network layer-wise, removing connections at each layer
by solving a convex optimization program. This program seeks a sparse set of
weights at each layer that keeps the layer inputs and outputs consistent with
the originally trained model. The algorithms and associated analysis are
applicable to neural networks operating with the rectified linear unit (ReLU)
as the nonlinear activation. We present both parallel and cascade versions of
the algorithm. While the latter can achieve slightly simpler models with the
same generalization performance, the former can be computed in a distributed
manner. In both cases, Net-Trim significantly reduces the number of connections
in the network, while also providing enough regularization to slightly reduce
the generalization error. We also provide a mathematical analysis of the
consistency between the initial network and the retrained model. To analyze the
model sample complexity, we derive the general sufficient conditions for the
recovery of a sparse transform matrix. For a single layer taking independent
Gaussian random vectors of length $N$ as inputs, we show that if the network
response can be described using a maximum number of $s$ non-zero weights per
node, these weights can be learned from $\mathcal{O}(s\log N)$ samples.


title:
Einstein-Podolsky-Rosen Steering and Quantum Steering Ellipsoids:
  Optimal Two-Qubit States and Projective Measurements

abstract:
  We identify the families of states that maximise some recently proposed
quantifiers of Einstein-Podolsky-Rosen (EPR) steering and the volume of the
Quantum Steering Ellipsoid (QSE). The optimal measurements which maximise
genuine EPR steering measures are discussed and we develop a novel way to find
them using the QSE. We thus explore the links between genuine EPR steering and
the QSE and introduce states that can be the most useful for one-sided
device-independent quantum cryptography for a given amount of noise.


title:
Single Chip Self-Tunable N-Input N-Output PID Control System with
  Integrated Analog Front-end for Miniature Robotics

abstract:
  In this work, we explore the design of an integrated, low power single chip
multi-channel Proportional-Integral-Derivative (PID) controller for emerging
miniature robotics, that includes N inputs and N corresponding outputs thereby
resulting in N parallel channels in the control system. It includes analog
front-end (AFE) and analog PID controllers for PID parameter tuning based on
PSO algorithm. The AFE incorporates adaptive biasing to ensure low power. The
PSO is optimized with respect to tuning precision, power and area. This makes
it attractive for real-time tuning of multiple miniaturized robotic devices
with a single PSO tuning algorithm block assigned for the task. For simulation
and testing purposes, we take N as 3 with the channels being defined by their
application-ends or plants, namely: dc motor, temperature sensor and gyroscope.


title:
A physically-based model of the ionizing radiation from active galaxies
  for photoionization modeling

abstract:
  We present a simplified model of Active Galactic Nucleus (AGN) continuum
emission designed for photoionization modeling. The new model {\sc oxaf}
reproduces the diversity of spectral shapes that arise in physically-based
models. We identify and explain degeneracies in the effects of AGN parameters
on model spectral shapes, with a focus on the complete degeneracy between the
black hole mass and AGN luminosity. Our re-parametrized model {\sc oxaf}
removes these degeneracies and accepts three parameters which directly describe
the output spectral shape: the energy of the peak of the accretion disk
emission $E_\mathrm{peak}$, the photon power-law index of the non-thermal
emission $\Gamma$, and the proportion of the total flux which is emitted in the
non-thermal component $p_\mathrm{NT}$. The parameter $E_\mathrm{peak}$ is
presented as a function of the black hole mass, AGN luminosity, and `coronal
radius' of the {\sc optxagnf} model upon which {\sc oxaf} is based. We show
that the soft X-ray excess does not significantly affect photoionization
modeling predictions of strong emission lines in Seyfert narrow-line regions.
Despite its simplicity, {\sc oxaf} accounts for opacity effects where the
accretion disk is ionized because it inherits the `color correction' of {\sc
optxagnf}. We use a grid of {\sc mappings} photoionization models with {\sc
oxaf} ionizing spectra to demonstrate how predicted emission-line ratios on
standard optical diagnostic diagrams are sensitive to each of the three {\sc
oxaf} parameters. The {\sc oxaf} code is publicly available in the Astrophysics
Source Code Library.


title:
Convergence of Partial maps via bornology through ideal and its
  Characterization

abstract:
  In this paper we consider the idea of I - convergence of nets of partial
function from a metric space (X; d) to a metric space (Y; ?) and derive several
basic characterization. This idea extends the concept of convergence of nets of
partial function introduced by G. Beer et.al [1].


title: Nanodiamond-enhanced MRI

abstract:
  Nanodiamonds are of interest as nontoxic substrates for targeted drug
delivery and as highly biostable fluorescent markers for cellular tracking.
Beyond optical techniques however, options for noninvasive imaging of
nanodiamonds in vivo are severely limited. Here, we demonstrate that the
Overhauser effect, a proton-electron double resonance technique developed to
detect free radicals in vivo, can enable high contrast magnetic resonance
imaging (MRI) of nanodiamonds in water at room temperature and ultra-low
magnetic field. The technique transfers spin polarization from paramagnetic
impurities at nanodiamond surfaces to $^1$H spins in the surrounding water
solution, creating MRI contrast on-demand. We further examine the conditions
required for maximum enhancement as well as the ultimate sensitivity of the
technique. The ability to perform continuous hyperpolarization via the
Overhauser mechanism, in combination with excellent in vivo stability, raises
the possibility of performing noninvasive tracking of nanodiamonds over
indefinitely long periods of time.


title:
Finite-orbit-width effects on the geodesic acoustic mode in the
  toroidally rotating tokamak plasma

abstract:
  The Landau damping of geodesic acoustic mode (GAM) in a torodial rotating
tokamak plasma is analytically investigated by taking into account the
finite-orbit-width (FOW) resonance effect to the 3rd order. The analytical
result is shown to agree well with the numerical solution. The dependence of
the damping rate on the toroidal Mach number $M$ relies on $k_r \rho_i$. For
sufficiently small $k_r \rho_i$, the damping rate monotonically decreases with
$M$. For relatively large $k_r \rho_i$, the damping rate increases with $M$
until approaching the maximum and then decreases with $M$.


title:
Switching based Spin Transfer Torque Oscillator with zero-bias field and
  large tuning-ratio

abstract:
  We propose a novel concept of obtaining oscillations with frequencies in
very-high frequency (VHF) and ultra-high frequency (UHF) bands. A traditional
spin torque nano-oscillator (STNO) consists of at least one pinned layer (PL)
and one free layer (FL) which precesses in a fixed orbit, defined by a
precession angle, which results in magneto-resistance (MR) oscillations. In
STNO, with aligned or even orthogonal easy-axis of the magnetic layers and with
or without external bias magnetic field, it is not possible to attain full MR
swing. The constringed MR swing jeopardizes the extracted output power.
Furthermore, the orbit is strongly disturbed by the thermal fluctuations
resulting in strong magnetic noise. In stark contrast to the operation
principle of a STNO, we theoretically demonstrate, with the practical
parameters from the experiments, that with a unidirectional current in a dual
asymmetric free-layers (with no pinned layer) based perpendicular magnetic
tunnel junction (pMTJ), both of the free layers can attain a complete and
out-of-phase self-sustained switching without the aid of any external magnetic
field. This design facilitates a switching based spin torque oscillator
(SW-STO) with a full MR swing, and hence a larger output power, for stable and
more thermally robust free-running oscillations. Furthermore, the integration
with the n-type metal-oxide-semiconductor (NMOS) field-effect transistors at
130, 65 and 14 nm node is appraised to expound its effect on the oscillator
performance, controllability with DC bias and the design constraints, to
demonstrate the viability of the design as a dynamically controllable
oscillator for practical on-chip implementation.


title:
The Effects of Relative Importance of User Constraints in Cloud of
  Things Resource Discovery: A Case Study

abstract:
  Over the last few years, the number of smart objects connected to the
Internet has grown exponentially in comparison to the number of services and
applications. The integration between Cloud Computing and Internet of Things,
named as Cloud of Things, plays a key role in managing the connected things,
their data and services. One of the main challenges in Cloud of Things is the
resource discovery of the smart objects and their reuse in different contexts.
Most of the existent work uses some kind of multi-criteria decision analysis
algorithm to perform the resource discovery, but do not evaluate the impact
that the user constraints has in the final solution. In this paper, we analyse
the behaviour of the SAW, TOPSIS and VIKOR multi-objective decision analyses
algorithms and the impact of user constraints on them. We evaluated the quality
of the proposed solutions using the Pareto-optimality concept.


title:
An $L^{2}$-isolation theorem for Yang-Mills fields on K\"{a}hler
  surfaces

abstract:
  We prove an $L^{2}$ energy gap result for Yang-Mills connections on principal
$G$-bundles over compact K\"{a}hler surfaces with positive scalar curvature. We
prove related results for compact simply-connected Calabi-Yau $2$-folds.


title: Multi-criteria IoT Resource Discovery: A Comparative Analysis

abstract:
  The growth of real world objects with embedded and globally networked sensors
allows to consolidate the Internet of Things paradigm and increase the number
of applications in the domains of ubiquitous and context-aware computing. The
merging between Cloud Computing and Internet of Things named Cloud of Things
will be the key to handle thousands of sensors and their data. One of the main
challenges in the Cloud of Things is context-aware sensor search and selection.
Typically, sensors require to be searched using two or more conflicting context
properties. Most of the existing work uses some kind of multi-criteria decision
analysis to perform the sensor search and selection, but does not show any
concern for the quality of the selection presented by these methods. In this
paper, we analyse the behaviour of the SAW, TOPSIS and VIKOR multi-objective
decision methods and their quality of selection comparing them with the
Pareto-optimality solutions. The gathered results allow to analyse and compare
these algorithms regarding their behaviour, the number of optimal solutions and
redundancy.


title:
K-property for Maharam extensions of nonsingular Bernoulli and Markov
  shifts

abstract:
  It is shown that each conservative nonsingular Bernoulli shift is either of
type $II_1$ or $III_1$. Moreover, in the latter case the corresponding Maharam
extension of the shift is a $K$-automorphism. This extends earlier results
obtained by Z.~Kosloff for the equilibrial shifts. Nonequilibrial shifts of
type $III_1$ are constructed. We further generalize (partly) the main results
to nonsingular Markov shifts.


title:
Variational Wavefunction for the Periodic Anderson Model with Onsite
  Correlation Factors

abstract:
  We propose a variational wavefunction containing parameters to tune the
probabilities of all the possible onsite configurations for the periodic
Anderson model. We call it the full onsite-correlation wavefunction (FOWF).
This is a simple extension of the Gutzwiller wavefunction (GWF), in which one
parameter is included to tune the double occupancy of the f electrons at the
same site. We compare the energy of the GWF and the FOWF evaluated by the
variational Monte Carlo method and that obtained with the density-matrix
renormalization group method. We find that the energy is considerably improved
in the FOWF. On the other hand, the physical quantities do not change
significantly between these two wavefunctions as long as they describe the same
phase, such as the paramagnetic phase. From these results, we not only
demonstrate the improvement by the FOWF, but we also gain insights on the
applicability and limitation of the GWF to the periodic Anderson model.


title: A new MHD-assisted Stokes inversion technique

abstract:
  We present a new method of Stokes inversion of spectropolarimetric data and
evaluate it by taking the example of a SUNRISE/IMaX observation. An archive of
synthetic Stokes profiles is obtained by the spectral synthesis of
state-of-the-art magnetohydrodynamics (MHD) simulations and a realistic
degradation to the level of the observed data. The definition of a merit
function allows the archive to be searched for the synthetic Stokes profiles
that match the observed profiles best. In contrast to traditional Stokes
inversion codes, which solve the Unno-Rachkovsky equations for the polarized
radiative transfer numerically and fit the Stokes profiles iteratively, the new
technique provides the full set of atmospheric parameters. This gives us the
ability to start an MHD simulation that takes the inversion result as initial
condition. After a relaxation process of half an hour solar time we obtain
physically consistent MHD data sets with a target similar to the observation.
The new MHD simulation is used to repeat the method in a second iteration,
which further improves the match between observation and simulation, resulting
in a factor of 2.2 lower mean $\chi^2$ value. One advantage of the new
technique is that it provides the physical parameters on a geometrical height
scale. It constitutes a first step towards inversions giving results consistent
with the MHD equations.


title: The strength of the SCT criterion

abstract:
  We undertake the study of size-change analysis in the context of Reverse
Mathematics. In particular, we prove that the SCT criterion is equivalent to
$\Sigma^0_2$-induction over RCA$_0$.


title: Leveraging Decoupling in Enabling Energy Aware D2D Communications

abstract:
  Downlink/Uplink decoupling (DUDe) in LTE net- works has caught the attention
of researchers as it provides better uplink SINR and reduced power consumption
per device due to decoupled connection of a device with the Macro (in downlink)
and a small cell (in uplink). These characteristics of DUDe can be exploited to
encourage more D2D communications in the network. This paper first proposes a
model to estimate decoupling region within which a device is allowed to perform
DUDe. Then, it formulates an equation to calculate the total power saved by
devices due to decoupling. Finally, the extra area due to decoupling which can
be used to enable D2D pairs is calculated. Simulation results are shown based
on different simulation scenarios for different objectives for better
understanding the idea proposed.


title: Detecting the Neutrinos Mass Hierarchy from Cosmological Data

abstract:
  We propose a new parameterization to measure the neutrino mass hierarchy,
namely $\Delta=(m_3-m_1)/(m_1+m_3)$ which is dimensionless and varies in the
range $[-1,1]$. Taking into account the results of neutrino oscillation
experiments, $\Delta$ is the unique parameter for determining all the masses of
neutrinos, and a positive (negative) sign of $\Delta$ denotes the normal
(inverted) mass hierarchy. Adopting the currently available cosmic
observations, we find that the normal mass hierarchy is slightly favored, and
the mass of lightest neutrino is less than $0.030$ eV for the normal mass
hierarchy and $0.024$ eV for the inverted mass hierarchy at $95\%$ confidence
level.


title:
$\gamma$-ray polarimetry with conversions to $e^+e^-$ pairs:
  polarization asymmetry and the way to measure it

abstract:
  We revisit the measurement of the polarization fraction, $P$, and the
measurement of the polarization angle of partially linearly-polarized gamma
rays using their conversion to $e^+e^-$ pairs in the field of a nucleus. We
show that an inappropriate definition of the azimuthal angle, $\varphi$, used
to reference the orientation of the final state degrades the precision of the
measurement of $P$, by comparison to the optimal case where the bisector angle
of the electron and of the positron momenta is used. We then focus on the
lowest part of the energy spectrum, below $\approx 10\,$MeV, where a large part
of the statistics lie for a cosmic source. We obtain the value of the
polarization asymmetry, $A$, of pair conversion at threshold and we show that
in the case where the correct expression is used for $\varphi$, the measured
value of $A$ tends to the limit.


title:
Evidence of electronic cloaking from chiral electron transport in
  bilayer graphene nanostructures

abstract:
  The coupling of charge carrier motion and pseudospin via chirality for
massless Dirac fermions in monolayer graphene has generated dramatic
consequences, such as the unusual quantum Hall effect and Klein tunneling. In
bilayer graphene, charge carriers are massive Dirac fermions with a finite
density of states at zero energy. Because of their non-relativistic nature,
massive Dirac fermions can provide an even better test bed with which to
clarify the importance of chirality in transport measurement than massless
Dirac fermions in monolayer graphene. Here, we report an electronic cloaking
effect as a manifestation of chirality by probing phase coherent transport in
chemical-vapor-deposited bilayer graphene. Conductance oscillations with
different periodicities were observed on extremely narrow bilayer graphene
heterojunctions through electrostatic gating. Using a Fourier analysis
technique, we identified the origin of each individual interference pattern.
Importantly, the electron waves on the two sides of the potential barrier can
be coupled through the evanescent waves inside the barrier, making the confined
states underneath the barrier invisible to electrons. These findings provide
direct evidence for the electronic cloaking effect and hold promise for the
realization of pseudospintronics based on bilayer graphene.


title: Graph Learning from Data under Structural and Laplacian Constraints

abstract:
  Graphs are fundamental mathematical structures used in various fields to
represent data, signals and processes. In this paper, we propose a novel
framework for learning/estimating graphs from data. The proposed framework
includes (i) formulation of various graph learning problems, (ii) their
probabilistic interpretations and (iii) associated algorithms. Specifically,
graph learning problems are posed as estimation of graph Laplacian matrices
from some observed data under given structural constraints (e.g., graph
connectivity and sparsity level). From a probabilistic perspective, the
problems of interest correspond to maximum a posteriori (MAP) parameter
estimation of Gaussian-Markov random field (GMRF) models, whose precision
(inverse covariance) is a graph Laplacian matrix. For the proposed graph
learning problems, specialized algorithms are developed by incorporating the
graph Laplacian and structural constraints. The experimental results
demonstrate that the proposed algorithms outperform the current
state-of-the-art methods in terms of accuracy and computational efficiency.


title: Detecting tala Computationally in Polyphonic Context - A Novel Approach

abstract:
  In North-Indian-Music-System(NIMS),tabla is mostly used as percussive
accompaniment for vocal-music in polyphonic-compositions. The human auditory
system uses perceptual grouping of musical-elements and easily filters the
tabla component, thereby decoding prominent rhythmic features like tala, tempo
from a polyphonic composition. For Western music, lots of work have been
reported for automated drum analysis of polyphonic composition. However,
attempts at computational analysis of tala by separating the tabla-signal from
mixed signal in NIMS have not been successful. Tabla is played with two
components - right and left. The right-hand component has frequency overlap
with voice and other instruments. So, tala analysis of polyphonic-composition,
by accurately separating the tabla-signal from the mixture is a baffling task,
therefore an area of challenge. In this work we propose a novel technique for
successfully detecting tala using left-tabla signal, producing meaningful
results because the left-tabla normally doesn't have frequency overlap with
voice and other instruments. North-Indian-rhythm follows complex cyclic
pattern, against linear approach of Western-rhythm. We have exploited this
cyclic property along with stressed and non-stressed methods of playing
tabla-strokes to extract a characteristic pattern from the left-tabla strokes,
which, after matching with the grammar of tala-system, determines the tala and
tempo of the composition. A large number of
polyphonic(vocal+tabla+other-instruments) compositions has been analyzed with
the methodology and the result clearly reveals the effectiveness of proposed
techniques.


title: Coalgebraic trace semantics via forgetful logics

abstract:
  We use modal logic as a framework for coalgebraic trace semantics, and show
the flexibility of the approach with concrete examples such as the language
semantics of weighted, alternating and tree automata, and the trace semantics
of generative probabilistic systems. We provide a sufficient condition under
which a logical semantics coincides with the trace semantics obtained via a
given determinization construction. Finally, we consider a condition that
guarantees the existence of a canonical determinization procedure that is
correct with respect to a given logical semantics. That procedure is closely
related to Brzozowski's minimization algorithm.


title: Effect of Kepler calibration on global seismic and background parameters

abstract:
  Calibration issues associated to scrambled collateral smear affecting the
Kepler short-cadence data were discovered in the Data Release 24 and were found
to be present in all the previous data releases since launch. In consequence, a
new Data Release 25 was reprocessed to correct for these problems. We perform
here a preliminary study to evaluate the impact on the extracted global seismic
and background parameters between data releases. We analyze the sample of
seismic solar analogs observed by Kepler in short cadence between Q5 and Q17.
We start with this set of stars as it constitutes the best sample to put the
Sun into context along its evolution, and any significant differences on the
seismic and background parameters need to be investigated before any further
studies of this sample can take place. We use the A2Z pipeline to derive both
global seismic parameters and background parameters from the Data Release 25
and previous data releases and report on the measured differences.


title:
Investigating the NCQ scaling of elliptic flow at LHC with a multiphase
  transport model

abstract:
  The number of constituent quark (NCQ) scaling behavior of elliptic flow has
been systematically studied at the LHC energy within the framework of a
multiphase transport model (AMPT) in this work. We find that the parameters
used to generate the initial states and the collision centrality are important
for the existence of NCQ scaling even when hadronic rescattering contribution
is off in Pb-Pb collisions of $\sqrt{s_{NN}}=2.76$ TeV. By turning on the
hadron rescattering process, the hadronic evolution impacts are also found to
be significant. Extending the analysis to Pb-Pb collsions of
$\sqrt{s_{NN}}=5.02$ TeV, one would observe similar qualitative features.


title:
Multi-Agent Motion Planning and Object Transportation under High Level
  Goals

abstract:
  This paper presents a hybrid control framework for the motion planning of a
multi-agent system including N robotic agents and M objects, under high level
goals. In particular, we design control protocols that allow the transition of
the agents as well as the transportation of the objects by the agents, among
predefined regions of interest in the workspace. This allows us to abstract the
coupled behavior of the agents and the objects as a finite transition system
and to design a high-level multi-agent plan that satisfies the agents' and the
objects' specifications, given as temporal logic formulas. Simulation results
verify the proposed framework.


title:
Variable Neighborhood Search Algorithms for the multi-depot dial-a-ride
  problem with heterogeneous vehicles and users

abstract:
  In this work, a study on Variable Neighborhood Search algorithms for
multi-depot dial-a-ride problems is presented. In dial-a-ride problems patients
need to be transported from pre-specified pickup locations to pre-specified
delivery locations, under different considerations. The addressed problem
presents several constraints and features, such as heterogeneous vehicles,
distributed in different depots, and heterogeneous patients. The aim is of
minimizing the total routing cost, while respecting time-window, ride-time,
capacity and route duration constraints. The objective of the study is of
determining the best algorithm configuration in terms of initial solution,
neighborhood and local search procedures. At this aim, two different procedures
for the computation of an initial solution, six different type of neighborhoods
and five local search procedures, where only intra-route changes are made, have
been considered and compared.
  We have also evaluated an "adjusting procedure" that aims to produce feasible
solutions from infeasible solutions with small constraints violations. The
different VNS algorithms have been tested on instances from literature as well
as on random instances arising from a real-world healthcare application.


title:
Thermo-visco-elasticity for Norton-Hoff-type models with homogeneous
  thermal expansion

abstract:
  In this work we study a quasi-static evolution of thermo-visco-elastic model
with homogeneous thermal expansion. We assume that material is subject to two
kinds of mechanical deformations: elastic and inelastic. Inelastic deformation
is related to a hardening rule of Norton-Hoff type. Appearance of inelastic
deformation causes transformation of mechanical energy into thermal one, hence
we also take into the consideration changes of material's temperature.
  The novelty of this paper is to take into account the thermal expansion of
material. We are proposing linearisation of the model for homogeneous thermal
expansion, which preserves symmetry of system and therefore total energy is
conserved. Linearisation of material's thermal expansion is performed in
definition of Cauchy stress tensor and in heat equation. In previous studies,
it was done in different way. Considering of such linearisation leads to system
where the coupling between temperature and displacement occurs in two places,
i.e. in the constitutive function for the evolution of visco-elastic strain and
in the additional term in the heat equation, in comparison to models without
thermal expansion. The second coupling was not considered previously. For such
system of equations we prove the existence of solutions. Moreover, we obtain
existence of displacement's time derivative, which has not been done
previously.


title:
First-principles calculations that clarify energetics and reactions of
  oxygen adsorption and carbon desorption on 4H-SiC ($11\bar20$) surface

abstract:
  We report static and dynamic first-principles calculations that provide
atomistic pictures of the initial stage of the oxidation processes occurring at
the ($11\bar20$) surface of 4H-SiC. Our results unveil reaction pathways and
their associated free-energy barriers for the adsorption of oxygen and the
desorption of carbon atoms. We find that oxygen adsorption shows structural
multi-stability and that the surface-bridge sites are the most stable and
crucial sites for subsequent oxidation. We find that an approaching O$_2$
molecule is adsorbed, then dissociated and finally migrates toward these
surface-bridge sites with a free-energy barrier of 0.7 eV at the ($11\bar20$)
surface. We also find that a CO molecule is desorbed from the metastable
oxidized structure upon the overcoming of a free-energy barrier of 2.4$\sim$2.6
eV, thus constituting one of the annihilation process of C during the
oxidation. The results of the CO molecule desorption on the ($11\bar20$)
surface are compared with the ($000\bar1$) surface. A catalytic effect of
dangling bonds at the surface, causing a drastic reduction of the CO desorption
energy, is found on the ($000\bar1$) surface and the microscopic picture of the
effect is ascribed to an electron transfer from the Si to C dangling bonds. The
intrinsic ($11\bar20$) surface does not show this catalytic effect, and this is
because the surface consists of an equal amount of Si and C dangling bonds and
the electron transfer occurs before the desorption.


title: Driving CDCL Search

abstract:
  The CDCL algorithm is the leading solution adopted by state-of-the-art
solvers for SAT, SMT, ASP, and others. Experiments show that the performance of
CDCL solvers can be significantly boosted by embedding domain-specific
heuristics, especially on large real-world problems. However, a proper
integration of such criteria in off-the-shelf CDCL implementations is not
obvious. In this paper, we distill the key ingredients that drive the search of
CDCL solvers, and propose a general framework for designing and implementing
new heuristics. We implemented our strategy in an ASP solver, and we
experimented on two industrial domains. On hard problem instances,
state-of-the-art implementations fail to find any solution in acceptable time,
whereas our implementation is very successful and finds all solutions.


title:
Constraint on a varying proton-to-electron mass ratio from H2 and HD
  absorption at z = 2.34

abstract:
  Molecular hydrogen absorption in the damped Lyman-alpha system at z = 2.34
towards quasar Q1232+082 is analyzed in order to derive a constraint on a
possible temporal variation of the proton-to-electron mass ratio, mu, over
cosmological timescales. Some 106 H2 and HD transitions, covering the range
3290-3726 \AA, are analyzed with a comprehensive fitting technique, allowing
for the inclusion of overlapping lines associated with hydrogen molecules, the
atomic hydrogen lines in the Lyman-alpha forest as well as metal lines. The
absorption model, based on the most recent and accurate rest wavelength for H2
and HD transitions, delivers a value of dmu/mu = (19 +/- 9 +/- 5)x 10^(-6). An
attempt to correct the spectrum for possible long-range wavelength distortions
is made and the uncertainty on the distortion correction is included in the
total systematic uncertainty. The present result is an order of magnitude more
stringent than a previous measurement from the analysis of this absorption
system, based on a line-by-line comparison of only 12 prominent and isolated H2
absorption lines. This is consistent with other measurements of dmu/mu from 11
other absorption systems in showing a null variation of the proton-to-electron
mass ratio over a look-back time of 11 Gyrs.


title:
Projected Axis Ratios of Galaxy Clusters in the Horizon-AGN Simulation:
  Impact of Baryon Physics and Comparison with Observations

abstract:
  We characterize the non-sphericity of galaxy clusters by the projected axis
ratio of spatial distribution of star, dark matter, and X-ray surface
brightness (XSB). We select 40 simulated groups and clusters of galaxies with
mass larger than 5E13 Msun from the Horizon simulation that fully incorporates
the relevant baryon physics, in particular, the AGN feedback. We find that the
baryonic physics around the central region of galaxy clusters significantly
affects the non-sphericity of dark matter distribution even beyond the central
region, approximately up to the half of the virial radius. Therefore it is very
difficult to predict the the probability density function (PDF) of the
projected axis ratio of XSB from dark-matter only N-body simulations as
attempted in previous studies. Indeed we find that the PDF derived from our
simulated clusters exhibits much better agreement with that from the observed
X-ray clusters. This indicates that our present methodology to estimate the
non-sphericity directly from the Horizon simulation is useful and promising.
Further improvements in both numerical modeling and observational data will
establish the non-sphericity of clusters as a cosmological test complementary
to more conventional statistics based on spherically averaged quantities.


title: Bayesian optimization of hyper-parameters in reservoir computing

abstract:
  We describe a method for searching the optimal hyper-parameters in reservoir
computing, which consists of a Gaussian process with Bayesian optimization. It
provides an alternative to other frequently used optimization methods such as
grid, random, or manual search. In addition to a set of optimal
hyper-parameters, the method also provides a probability distribution of the
cost function as a function of the hyper-parameters. We apply this method to
two types of reservoirs: nonlinear delay nodes and echo state networks. It
shows excellent performance on all considered benchmarks, either matching or
significantly surpassing results found in the literature. In general, the
algorithm achieves optimal results in fewer iterations when compared to other
optimization methods. We have optimized up to six hyper-parameters
simultaneously, which would have been infeasible using, e.g., grid search. Due
to its automated nature, this method significantly reduces the need for expert
knowledge when optimizing the hyper-parameters in reservoir computing. Existing
software libraries for Bayesian optimization, such as Spearmint, make the
implementation of the algorithm straightforward. A fork of the Spearmint
framework along with a tutorial on how to use it in practice is available at
https://bitbucket.org/uhasseltmachinelearning/spearmint/


title:
Computation of first-order Greeks for barrier options using chain rules
  for Wiener path integrals

abstract:
  This paper presents a new methodology to compute first-order Greeks for
barrier options under the framework of path-dependent payoff functions with
European, Lookback, or Asian type and with time-dependent trigger levels. In
particular, we develop chain rules for Wiener path integrals between two curves
that arise in the computation of first-order Greeks for barrier options. We
also illustrate the effectiveness of our method through numerical examples.


title:
Tunneling anomalous Hall effect in the nanogranular CoFe-B-Al-O films
  near the metal-insulator transition

abstract:
  We present results of experimental studies of structural, magneto-transport
and magnetic properties of CoFe-B-Al-O films deposited onto a glass ceramic
substrate by the ion-beam sputtering of the target composed of Co40Fe40B20 and
Al2O3 plates. The system consists on the strained crystalline CoFe metallic
nanogranules with the size 2-5 nm which are embedded into the B-Al-O oxide
insulating matrix. Our investigations are focused on the anomalous Hall effect
(AHE) resistivity Rh and longitudinal resistivity R at T=5-200 K on the
metallic side of metal-insulator transition in samples with the metal content
x=49-56 at.%, that nominally corresponds to (Co40Fe40B20)x(Al2O3)100-x in the
formula approximation. The conductivity at T > 15 K follows the lnT behavior
that matches a strong tunnel coupling between nanogranules. It is shown that
the scaling power-laws between AHE resistivity and longitudinal resistivity
strongly differ, if temperature T or metal content x are variable parameters:
Rh(T)~R(T)^0.4-0.5 obtained from the temperature variation of R and Rh at fixed
x, while Rh(x)/x~R(x)^0.24, obtained from measurements at the fixed low
temperature region (10-40 K) for samples with different x. We qualitatively
describe our experimental data in the frame of phenomenological model of two
sources of AHE e.m.f. arising from metallic nanogranules and insulating
tunneling regions, respectively, at that the tunneling AHE (TAHE) source is
strongly shunted due to generation of local circular Hall currents. We consider
our experimental results as the first experimental proof of the TAHE
manifestation.


title:
Cooperative Aerial Coverage Path Planning for Visual Inspection of
  Complex Infrastructures

abstract:
  This article addresses the problem of Cooperative Coverage Path Planning
(C-CPP) for the inspection of complex infrastructures (offline 3D
reconstruction) by utilizing multiple Unmanned Autonomous Vehicles (UAVs). The
proposed scheme, based on a priori 3D model of the infrastructure under
inspection, is able to generate multiple paths for UAVs in order to achieve a
complete cooperative coverage in a short time. Initially the infrastructure
under inspection is being sliced by horizontal planes, which has the capability
of recognizing the branches of the structure and these branches will be handled
as breaking points for the path planning of the UAVs to collaboratively execute
the coverage task in less time and more realistically, based on the current
flying times of the UAVs. The multiple data sets collected from the coverage
are merged for the offline sparse and dense 3D reconstruction of the
infrastructure by utilizing SLAM and Structure from Motion approaches, with
either monocular or stereo sensors. The performance of the proposed C-CPP has
been experimentally evaluated in multiple indoor and realistic outdoor
infrastructure inspection experiments.


title:
Earliest Datable Records of Aurora-like Phenomena in the Astronomical
  Diaries from Babylonia

abstract:
  The Astronomical Diaries from Babylonia (ADB) are an excellent source of
information of natural phenomena, including astronomical ones, in pre-Christ
era because it contains the record of highly continuous and systematic
observations. In this article we present results of a survey of aurora-like
phenomena in ADB, spanning from BCE 652 to BCE 61. We have found 9 records of
aurora-like phenomena. Philological and scientific examinations suggest 5 of
them can be considered as likely candidate for aurora observations. They
provide unique information about the solar and aurora activities in the first
millennium BCE.


title: One-Shot Video Object Segmentation

abstract:
  This paper tackles the task of semi-supervised video object segmentation,
i.e., the separation of an object from the background in a video, given the
mask of the first frame. We present One-Shot Video Object Segmentation (OSVOS),
based on a fully-convolutional neural network architecture that is able to
successively transfer generic semantic information, learned on ImageNet, to the
task of foreground segmentation, and finally to learning the appearance of a
single annotated object of the test sequence (hence one-shot). Although all
frames are processed independently, the results are temporally coherent and
stable. We perform experiments on two annotated video segmentation databases,
which show that OSVOS is fast and improves the state of the art by a
significant margin (79.8% vs 68.0%).


title: Quaternionic Fock space on slice hyperholomorphic functions

abstract:
  In this paper, we define the quaternionic Fock spaces
$\mathfrak{F}_{\alpha}^p$ of entire slice hyperholomorphic functions in a
quaternionic unit ball $\mathbb{B}$ in $\mathbb{H}.$ We also study growth
estimate and various results of entire slice regular functions in these spaces.
The work of this paper is motivated by the recent work of \cite{alpa12} and
\cite{marco}.


title:
H\"older stability estimate in an inverse source problem for a first and
  half order time fractional diffusion equation

abstract:
  We consider the first and half order time fractional equation with the zero
initial condition. We investigate an inverse source problem of determining the
time-independent source factor by the data at an arbitrarily fixed time and we
establish the conditional stability estimate of H\"older type in our inverse
problem. Our method is based on the Bukhgeim-Klibanov method by means of the
Carleman estimate. We also derive the Carleman estimate for the first and half
order time fractional diffusion equation.


title: Multiscale inference for multivariate deconvolution

abstract:
  In this paper we provide new methodology for inference of the geometric
features of a multivariate density in deconvolution. Our approach is based on
multiscale tests to detect significant directional derivatives of the unknown
density at arbitrary points in arbitrary directions. The multiscale method is
used to identify regions of monotonicity and to construct a general procedure
for the detection of modes of the multivariate density. Moreover, as an
important application a significance test for the presence of a local maximum
at a pre-specified point is proposed. The performance of the new methods is
investigated from a theoretical point of view and the finite sample properties
are illustrated by means of a small simulation study.


title: Quantum revival for elastic waves in thin plate

abstract:
  Quantum revival is described as the time-periodic reconstruction of a wave
packet initially localized in space and time. This effect is expected in
finite-size systems which exhibits commensurable discrete spectrum such as the
infinite quantum well. Here, we report on the experimental observation of full
and fractional quantum revival for classical waves in a two dimensional cavity.
We consider flexural waves propagating in thin plates, as their quadratic
dispersion at low frequencies mimics the dispersion relation of quantum systems
governed by Schr\"{o}dinger equation. Time-dependent excitation and measurement
are performed at ultrasonic frequencies and reveal a periodic reconstruction of
the initial elastic wave packet.


title: Will People Like Your Image? Learning the Aesthetic Space

abstract:
  Rating how aesthetically pleasing an image appears is a highly complex matter
and depends on a large number of different visual factors. Previous work has
tackled the aesthetic rating problem by ranking on a 1-dimensional rating
scale, e.g., incorporating handcrafted attributes. In this paper, we propose a
rather general approach to automatically map aesthetic pleasingness with all
its complexity into an "aesthetic space" to allow for a highly fine-grained
resolution. In detail, making use of deep learning, our method directly learns
an encoding of a given image into this high-dimensional feature space
resembling visual aesthetics. Additionally to the mentioned visual factors,
differences in personal judgments have a large impact on the likeableness of a
photograph. Nowadays, online platforms allow users to "like" or favor certain
content with a single click. To incorporate a huge diversity of people, we make
use of such multi-user agreements and assemble a large data set of 380K images
(AROD) with associated meta information and derive a score to rate how visually
pleasing a given photo is. We validate our derived model of aesthetics in a
user study. Further, without any extra data labeling or handcrafted features,
we achieve state-of-the art accuracy on the AVA benchmark data set. Finally, as
our approach is able to predict the aesthetic quality of any arbitrary image or
video, we demonstrate our results on applications for resorting photo
collections, capturing the best shot on mobile devices and aesthetic key-frame
extraction from videos.


title: The emergence and evolution of the research fronts in HIV/AIDS research

abstract:
  In this paper, we have identified and analyzed the emergence, structure and
dynamics of the paradigmatic research fronts that established the fundamentals
of the biomedical knowledge on HIV/AIDS. A search of papers with the
identifiers "HIV/AIDS", "Human Immunodeficiency Virus", "HIV-1" and "Acquired
Immunodeficiency Syndrome" in the Web of Science (Thomson Reuters), was carried
out. A citation network of those papers was constructed. Then, a sub-network of
the papers with the highest number of inter-citations (with a minimal in-degree
of 28) was selected to perform a combination of network clustering and text
mining to identify the paradigmatic research fronts and analyze their dynamics.
Thirteen research fronts were identified in this sub-network. The biggest and
oldest front is related to the clinical knowledge on the disease in the
patient. Nine of the fronts are related to the study of specific molecular
structures and mechanisms and two of these fronts are related to the
development of drugs. The rest of the fronts are related to the study of the
disease at the cellular level. Interestingly, the emergence of these fronts
occurred in successive "waves" over the time which suggest a transition in the
paradigmatic focus. The emergence and evolution of the biomedical fronts in
HIV/AIDS research is explained not just by the partition of the problem in
elements and interactions leading to increasingly specialized communities, but
also by changes in the technological context of this health problem and the
dramatic changes in the epidemiological reality of HIV/AIDS that occurred
between 1993 and 1995.


title: Search-and-Rescue Rendezvous

abstract:
  We consider a new type of asymmetric rendezvous search problem in which Agent
II needs to give Agent I a `gift' which can be in the form of information or
material. The gift can either be transfered upon meeting, as in traditional
rendezvous, or it can be dropped o? by II at a location he passes, in the hope
it will be found by I. The gift might be a water bottle for a traveller lost in
the desert; a supply cache for Lieutenant Scott in the Antarctic; or important
information (left as a gift). The common aim of the two agents is to minimize
the time taken for I to either meet II or find the gift. We find optimal agent
paths and droppo? times when the search region is a line, the initial distance
between the players is known and one or both of the players can leave gifts.
When there are no gifts this is the classical asymmetric rendezvous problem
solved by Alpern and Gal in 1995 [10]. We exhibit strategies solving these
various problems and use a `rendezvous algorithm' to establish their
optimality.


title: Expected values in percentile indicators

abstract:
  PP(top x%) is the proportion of papers of a unit (e.g. an institution or a
group of researchers), which belongs to the x% most frequently cited papers in
the corresponding fields and publication years. It has been proposed that x% of
papers can be expected which belongs to the x% most frequently cited papers. In
this Letter to the Editor we will present the results of an empirical test
whether we can really have this expectation and how strong the deviations from
the expected values are when many random samples are drawn from the database.


title:
Generating a stationary infinite range tractor force via a multimode
  optical fiber

abstract:
  Optical fibers confine and guide light almost unattenuated and thus convey
light forces to polarizable nano-particles over very long distances. Radiation
pressure forces arise from scattering of guided photons into free space while
gradient forces are based on coherent scattering between different fiber modes
or propagation directions. Interestingly, even scattering between
co-propagating modes induces longitudinal forces as the transverse confinement
of the light modes creates mode dependent longitudinal wave-vectors and photon
momenta. We generalize a proven scattering matrix based approach to calculate
single as well as inter-particle forces to include several forward and backward
propagating modes. We show that an injection of the higher order mode only in a
two mode fiber will induce a stationary tractor force against the injection
direction, when the mode coupling to the lower order mode dominates against
backscattering and free space losses. Generically this arises for non-absorbing
particles at the center of a waveguide. The model also gives improved
predictions for inter-particle forces in evanescent nanofiber fields as
experimentally observed recently. Surprisingly strong tractor forces can also
act on whole optically bound arrays.


title:
Half-filled intermediate bands Si material formed by energetically
  metastable interstitial sulfur atom

abstract:
  Hyperdoped metastable sulfur atoms endow crystalline silicon with a strong
sub-bandgap light absorption. In order to explore such metastable states, we
develop a new high-throughput first-principles calculation method to search for
all of the energetically metastable states for an interstitial sulfur atom
inside crystalline silicon. Finally, we obtain sixty-three metastable
interstitial states and they can be classified into ten types. Interestingly,
twenty-eight (44% in total) of lower-energy metastable states can produce a
well-isolated and half-filled intermediate band (IB) inside silicon forbidden
gap, which makes sulfur hyperdoped silicon to be a desirable material for IB
solar cells.


title: Deep Variational Inference Without Pixel-Wise Reconstruction

abstract:
  Variational autoencoders (VAEs), that are built upon deep neural networks
have emerged as popular generative models in computer vision. Most of the work
towards improving variational autoencoders has focused mainly on making the
approximations to the posterior flexible and accurate, leading to tremendous
progress. However, there have been limited efforts to replace pixel-wise
reconstruction, which have known shortcomings. In this work, we use real-valued
non-volume preserving transformations (real NVP) to exactly compute the
conditional likelihood of the data given the latent distribution. We show that
a simple VAE with this form of reconstruction is competitive with complicated
VAE structures, on image modeling tasks. As part of our model, we develop
powerful conditional coupling layers that enable real NVP to learn with fewer
intermediate layers.


title:
Dispersion Estimates for Spherical Schr\"odinger Equations with Critical
  Angular Momentum

abstract:
  We derive a dispersion estimate for one-dimensional perturbed radial
Schr\"odinger operators where the angular momentum takes the critical value
$l=-\frac{1}{2}$. We also derive several new estimates for solutions of the
underlying differential equation and investigate the behavior of the Jost
function near the edge of the continuous spectrum.


title: Leptonic mono-top from single stop production at LHC

abstract:
  Top squark (stop) can be produced via QCD interaction but also the
electroweak interaction at the LHC. In this paper, we investigate the
observability of the associated production of stop and chargino, $pp \to
\tilde{t}_1\tilde{\chi}^-_1$, in compressed electroweakino scenario at the 14
TeV LHC. Due to the small mass-splitting between the lightest neutralino
($\tilde{\chi}^0_1$) and chargino ($\tilde{\chi}^-_1$), such a single stop
production can give a mono-top signature through the stop decay $\tilde{t}_1
\to t \tilde{\chi}^0_1$. Focusing on the leptonic mono-top channel, we propose
a lab-frame observable $\cos\theta_{b\ell}$ to reduce the SM backgrounds in
virtue of a boosted top quark from the stop decay. We find that the single stop
production can be probed at $2\sigma$ level at the HL-LHC for
$m_{\tilde{t}_1}<760$ GeV and $m_{\tilde{\chi}^0_1}<150$ GeV.


title: Rate optimal adaptive FEM with inexact solver for nonlinear operators

abstract:
  We prove convergence with optimal algebraic rates for an adaptive finite
element method for nonlinear equations with strongly monotone operator. Unlike
prior works, our analysis also includes the iterative and inexact solution of
the arising nonlinear systems by means of the Picard iteration. Using nested
iteration, we prove, in particular, that the number of of Picard iterations is
uniformly bounded in generic cases, and the overall computational cost is
(almost) optimal. Numerical experiments confirm the theoretical results.


title:
Two phase formation of massive elliptical galaxies : study through
  cross-correlation including spatial effect

abstract:
  Formation mechanism of present day population of elliptical galaxies have
been revisited in the context of hierarchical cosmological models accompanied
by accretion and minor mergers through cross correlation function including
spatial effect. The present work investigates the formation and evolution of
several components of nearby massive early type galaxies (ETGs) through
cross-correlation in the spatial coordinates, right ascension and declination
(RA, DEC) and mass-size parameter space with high redshift $(0.5\leq z\leq2.7)$
ETGs. It is found that innermost components of nearby ETGs are highly
correlated with ETGs in the redshift range $(2\leq z\leq2.7)$ known as 'red
nuggets'. The intermediate and outermost parts have moderate correlations with
ETGs in the redshift range $(0.5\leq z\leq0.75)$. The quantitative measures are
highly consistent with the two phase formation scenario of massive nearby early
type galaxies as suggested by various authors and resolves the conflict raised
in a previous work suggesting other possibilities for the formation of
outermost part of nearby massive ETGs. The improvement is expected to be due to
inclusion of spatial effects in addition to other linear parameters.


title:
Transverse double-spin asymmetries for electroweak gauge-boson
  production in high-energy polarized $p^{\uparrow} + p^{\uparrow}$ collisions

abstract:
  We consider the production of $W$ and $Z / \gamma^{*}$ gauge bosons in
proton-proton collisions at a center-of-mass energy of $\sqrt{s} = 510
\mbox{GeV}$ available at RHIC at BNL, operating at high luminosity. We stress
the importance of measuring the transverse double-spin asymmetries $A_{TT}$, in
connection with available transversely polarized beams with a high degree of
polarisation. We will discuss some theoretical issues related to the predicted
asymmetries. These studies are contrasted to the 2017 RHIC running operation of
transversely polarized beams of mid-rapidity $W$ and $Z$ boson production at a
center-of-mass energy of $\sqrt{s}=510\,$GeV along with long-term prospects
beyond 2020 at RHIC.


title: Joint Network based Attention for Action Recognition

abstract:
  By extracting spatial and temporal characteristics in one network, the
two-stream ConvNets can achieve the state-of-the-art performance in action
recognition. However, such a framework typically suffers from the separately
processing of spatial and temporal information between the two standalone
streams and is hard to capture long-term temporal dependence of an action. More
importantly, it is incapable of finding the salient portions of an action, say,
the frames that are the most discriminative to identify the action. To address
these problems, a \textbf{j}oint \textbf{n}etwork based \textbf{a}ttention
(JNA) is proposed in this study. We find that the fully-connected fusion,
branch selection and spatial attention mechanism are totally infeasible for
action recognition. Thus in our joint network, the spatial and temporal
branches share some information during the training stage. We also introduce an
attention mechanism on the temporal domain to capture the long-term dependence
meanwhile finding the salient portions. Extensive experiments are conducted on
two benchmark datasets, UCF101 and HMDB51. Experimental results show that our
method can improve the action recognition performance significantly and
achieves the state-of-the-art results on both datasets.


title:
Learning long-term dependencies for action recognition with a
  biologically-inspired deep network

abstract:
  Despite a lot of research efforts devoted in recent years, how to efficiently
learn long-term dependencies from sequences still remains a pretty challenging
task. As one of the key models for sequence learning, recurrent neural network
(RNN) and its variants such as long short term memory (LSTM) and gated
recurrent unit (GRU) are still not powerful enough in practice. One possible
reason is that they have only feedforward connections, which is different from
the biological neural system that is typically composed of both feedforward and
feedback connections. To address this problem, this paper proposes a
biologically-inspired deep network, called shuttleNet\footnote{Our code is
available at \url{https://github.com/shiyemin/shuttlenet}}. Technologically,
the shuttleNet consists of several processors, each of which is a GRU while
associated with multiple groups of cells and states. Unlike traditional RNNs,
all processors inside shuttleNet are loop connected to mimic the brain's
feedforward and feedback connections, in which they are shared across multiple
pathways in the loop connection. Attention mechanism is then employed to select
the best information flow pathway. Extensive experiments conducted on two
benchmark datasets (i.e UCF101 and HMDB51) show that we can beat
state-of-the-art methods by simply embedding shuttleNet into a CNN-RNN
framework.


title:
Exact Propagator of a two dimensional anisotropic Harmonic Oscillator in
  the presence of a Magnetic Field

abstract:
  In this paper we solve exactly the problem of the spectrum and Feynman
propagator of a charged particle submitted to both an anharmonic oscillator in
the plane and a constant and homogeneous magnetic field of arbitrary strength
aligned with the perpendicular direction to the plane. As we shall see in the
beginning of the letter the Hamiltonian, being a quadratic form, is easily
diagonalizable and the Classical Action can be used to construct the exact
Feynman Propagator using the Stationary Phase Approximation. The result is
useful for the treatment of quasi two dimensional samples in the field of
magnetic effects in nano-structures and quantum optics. The presented solution,
after minor extensions, can also be used for motion in three dimensions, and in
fact it has been used for years in such cases. Also it can be used as a good
exercise of a Feynman Path Integral that can be calculated easily with just the
help of the Classical Action.


title: Stratified Langlands duality in the $A_n$ tower

abstract:
  Let $\mathbf{S}_k$ denote a maximal torus in the complex Lie group
$\mathbf{G} = \mathrm{SL}_n(\mathbb{C})/C_k$ and let $T_k$ denote a maximal
torus in its compact real form $\mathrm{SU}_n(\mathbb{C})/C_k$, where $k$
divides $n$. Let $W$ denote the Weyl group of $\mathbf{G}$, namely the
symmetric group $\mathfrak{S}_n$. We elucidate the structure of the extended
quotient $\mathbf{S}_k // W$ as an algebraic variety and of $T_k // W$ as a
topological space, in both cases describing them as bundles over unions of
tori. Corresponding to the invariance of $K$-theory under Langlands duality,
this calculation provides a homotopy equivalence between $T_k // W$ and its
dual $T_{\frac{n}{k}} // W$. Hence there is an isomorphism in cohomology for
the extended quotients which is stratified as a direct sum over conjugacy
classes of the Weyl group. We use our formula to compute a number of examples.


title:
A Sufficient Condition for a Unique Invariant Distribution of a
  Higher-Order Markov Chain

abstract:
  We derive a sufficient condition for a $k$-th order homogeneous Markov chain
$\mathbf{Z}$ with finite alphabet $\mathcal{Z}$ to have a unique invariant
distribution on $\mathcal{Z}^k$. Specifically, let $\mathbf{X}$ be a
first-order, stationary Markov chain with finite alphabet $\mathcal{X}$ and a
single recurrent class, let $g{:}\ \mathcal{X}\to\mathcal{Z}$ be non-injective,
and define the (possibly non-Markovian) process $\mathbf{Y}:=g(\mathbf{X})$
(where $g$ is applied coordinate-wise). If $\mathbf{Z}$ is the $k$-th order
Markov approximation of $\mathbf{Y}$, its invariant distribution is unique. We
generalize this to non-Markovian processes $\mathbf{X}$.


title:
Convergence of complex martingales in the branching random walk: the
  boundary

abstract:
  Biggins [Uniform convergence of martingales in the branching random walk.
{\em Ann. Probab.}, 20(1):137--151, 1992] proved local uniform convergence of
additive martingales in $d$-dimensional supercritical branching random walks at
complex parameters $\lambda$ from an open set $\Lambda \subseteq \mathbb{C}^d$.
We investigate the martingales corresponding to parameters from the boundary
$\partial \Lambda$ of $\Lambda$. The boundary can be decomposed into several
parts. There may be a part of the boundary, on which the martingales do not
exist, on other parts it exists, but diverges or vanishes in the limit. In the
remaining part, there is convergence to a non-degenerate limit. The arguments
that give this convergence also apply in $\Lambda$ and require weaker moment
assumptions than the ones used by Biggins.


title: Two-electron bound states near a Coulomb impurity in gapped graphene

abstract:
  We formulate and solve the perhaps simplest two-body bound state problem for
interacting Dirac fermions in two spatial dimensions. A two-body bound state is
predicted for gapped graphene monolayers in the presence of weakly repulsive
electron-electron interactions and a Coulomb impurity with charge $Ze>0$, where
the most interesting case corresponds to $Z=1$. We introduce a variational
Chandrasekhar-Dirac spinor wave function and show the existence of at least one
bound state. This state leaves clear signatures accessible by scanning
tunneling microscopy. One may thereby obtain direct information about the
strength of electron-electron interactions in graphene.


title:
Simple Yet Effective Methods for Large-Scale Scholarly Publication
  Ranking

abstract:
  With the growing amount of published research, automatic evaluation of
scholarly publications is becoming an important task. In this paper we address
this problem and present a simple and transparent approach for evaluating the
importance of scholarly publications. Our method has been ranked among the top
performers in the WSDM Cup 2016 Challenge. The first part of this paper
describes our method. In the second part we present potential improvements to
the method and analyse the evaluation setup which was provided during the
challenge. Finally, we discuss future challenges in automatic evaluation of
papers including the use of full-texts based evaluation methods.


title:
A study of the effect of rotational mixing on massive stars evolution:
  surface abundances of Galactic O7-8 giant stars

abstract:
  Massive star evolution remains only partly constrained. In particular, the
exact role of rotation has been questioned by puzzling properties of OB stars
in the Magellanic Clouds. Our goal is to study the relation between surface
chemical composition and rotational velocity, and to test predictions of
evolutionary models including rotation. We have performed a spectroscopic
analysis of a sample of fifteen Galactic O7-8 giant stars. This sample is
homogeneous in terms of mass, metallicity and evolutionary state. It is made of
stars with a wide range of projected rotational velocities. We show that the
sample stars are located on the second half of the main sequence, in a
relatively narrow mass range (25-40 Msun). Almost all stars with projected
rotational velocities above 100 km/s have N/C ratios about ten times the
initial value. Below 100 km/s a wide range of N/C values is observed. The
relation between N/C and surface gravity is well reproduced by various sets of
models. Some evolutionary models including rotation are also able to
consistently explain slowly rotating, highly enriched stars. This is due to
differential rotation which efficiently transports nucleosynthesis products and
allows the surface to rotate slower than the core. In addition, angular
momentum removal by winds amplifies surface braking on the main sequence.
Comparison of the surface composition of O7-8 giant stars with a sample of B
stars with initial masses about four times smaller reveal that chemical
enrichment scales with initial mass, as expected from theory. Although
evolutionary models that include rotation face difficulties in explaining the
chemical properties of O- and B-type stars at low metallicity, some of them can
consistently account for the properties of main-sequence Galactic O stars in
the mass range 25-40 Msun