title:
Measuring the stellar wind parameters in IGR J17544-2619 and Vela X-1
  constrains the accretion physics in Supergiant Fast X-ray Transient and
  classical Supergiant X-ray Binaries

abstract:
  Classical Supergiant X-ray Binaries (SGXBs) and Supergiant Fast X-ray
Transients (SFXTs) are two types of High-mass X-ray Binaries (HMXBs) that
present similar donors but, at the same time, show very different behavior in
the X-rays. The reason for this dichotomy of wind-fed HMXBs is still a matter
of debate. Among the several explanations that have been proposed, some of them
invoke specific stellar wind properties of the donor stars. Only dedicated
empiric analysis of the donors' stellar wind can provide the required
information to accomplish an adequate test of these theories. However, such
analyses are scarce. To close this gap, we perform a comparative analysis of
the optical companion in two important systems: IGR J17544-2619 (SFXT) and Vela
X-1 (SGXB). We analyse the spectra of each star in detail and derive their
stellar and wind properties. We compare the wind parameters, giving us an
excellent chance of recognizing key differences between donor winds in SFXTs
and SGXBs. We find that the stellar parameters derived from the analysis
generally agree well with the spectral types of the two donors: O9I (IGR
J17544-2619) and B0.5Iae (Vela X-1). An important difference between the
stellar winds of the two stars is their terminal velocities v_inf=1500km/s in
IGR J17544-2619 and v_inf=700km/s in Vela~X-1, which has important consequences
on the X-ray luminosity of these sources. Their specific combination of wind
speed and pulsar spin favours an accretion regime with a persistently high
luminosity in Vela X-1, while it favours an inhibiting accretion mechanism in
IGR~J17544-2619. Our study demonstrates that the wind relative velocity is
critical in the determination of the class of HMXBs hosting a supergiant donor,
given that it may shift the accretion mechanism from direct accretion to
propeller regimes when combined with other parameters.


title: Small generators of cocompact arithmetic Fuchsian groups

abstract:
  In the study of Fuchsian groups, it is a nontrivial problem to determine a
set of generators. Using a dynamical approach we construct for any cocompact
arithmetic Fuchsian group a fundamental region in $\mathbf{SL}_2(\mathbb{R})$
from which we determine a set of small generators.


title:
Voltage controlled core reversal of fixed magnetic skyrmions without a
  magnetic field

abstract:
  Using micromagnetic simulations we demonstrate core reversal of a fixed
magnetic skyrmion by modulating the perpendicular magnetic anisotropy of a
nanomagnet with an electric field. We can switch reversibly between two
skyrmion states and two ferromagnetic states, i.e. skyrmion states with the
magnetization of the core pointing down/up and periphery pointing up/down, and
ferromagnetic states with magnetization pointing up/down, by sequential
increase and decrease of the perpendicular magnetic anisotropy. The switching
between these states is explained by the fact that the spin texture
corresponding to each of these stable states minimizes the sum of the magnetic
anisotropy, demagnetization, Dzyaloshinskii-Moriya interaction (DMI) and
exchange energies. This could lead to the possibility of energy efficient
nanomagnetic memory and logic devices implemented with fixed skyrmions without
using a magnetic field and without moving skyrmions with a current.


title: Trainyard is NP-Hard

abstract:
  Recently, due to the widespread diffusion of smart-phones, mobile puzzle
games have experienced a huge increase in their popularity. A successful puzzle
has to be both captivating and challenging, and it has been suggested that this
features are somehow related to their computational complexity \cite{Eppstein}.
Indeed, many puzzle games --such as Mah-Jongg, Sokoban, Candy Crush, and 2048,
to name a few-- are known to be NP-hard \cite{CondonFLS97,
culberson1999sokoban, GualaLN14, Mehta14a}. In this paper we consider
Trainyard: a popular mobile puzzle game whose goal is to get colored trains
from their initial stations to suitable destination stations. We prove that the
problem of determining whether there exists a solution to a given Trainyard
level is NP-hard. We also \href{http://trainyard.isnphard.com}{provide} an
implementation of our hardness reduction.


title: A Kernel Test for Three-Variable Interactions with Random Processes

abstract:
  We apply a wild bootstrap method to the Lancaster three-variable interaction
measure in order to detect factorisation of the joint distribution on three
variables forming a stationary random process, for which the existing
permutation bootstrap method fails. As in the i.i.d. case, the Lancaster test
is found to outperform existing tests in cases for which two independent
variables individually have a weak influence on a third, but that when
considered jointly the influence is strong. The main contributions of this
paper are twofold: first, we prove that the Lancaster statistic satisfies the
conditions required to estimate the quantiles of the null distribution using
the wild bootstrap; second, the manner in which this is proved is novel,
simpler than existing methods, and can further be applied to other statistics.


title: Super Mario as a String: Platformer Level Generation Via LSTMs

abstract:
  The procedural generation of video game levels has existed for at least 30
years, but only recently have machine learning approaches been used to generate
levels without specifying the rules for generation. A number of these have
looked at platformer levels as a sequence of characters and performed
generation using Markov chains. In this paper we examine the use of Long
Short-Term Memory recurrent neural networks (LSTMs) for the purpose of
generating levels trained from a corpus of Super Mario Brothers levels. We
analyze a number of different data representations and how the generated levels
fit into the space of human authored Super Mario Brothers levels.


title:
Enhancement of Thermally Injected Spin Current through an
  Antiferromagnetic Insulator

abstract:
  We report large enhancement of thermally injected spin current in normal
metal (NM)/antiferromagnet(AF)/yttrium iron garnet(YIG), where a thin AF
insulating layer of NiO or CoO can enhance spin current from YIG to a NM by up
to a factor of 10. The spin current enhancement in NM/AF/YIG, with a pronounced
maximum near the N\'eel temperature of the thin AF layer, has been found to
scale linearly with the spin-mixing conductance at the NM/YIG interface for NM
= 3d, 4d, and 5d metals. Calculations of spin current enhancement and spin
mixing conductance are qualitatively consistent with the experimental results.


title: A Generalization of the Stone Duality Theorem

abstract:
  We prove a new duality theorem for the category of precontact algebras which
implies the Stone Duality Theorem, its connected version obtained in
arXiv:1508.02220v3, 1-44 (to appear in Topology Appl.), the recent duality
theorems of Bezhanishvili, G., Bezhanishvili, N., Sourabh, S., Venema, Y. and
Goldblatt, R. and Grice, M, and some new duality theorems for the category of
contact algebras and for the category of complete contact algebras.


title:
Frequency driven inversion of tunnel magnetoimpedance in magnetic tunnel
  junctions

abstract:
  Magnetic tunnel junctions (MTJs) are basic building blocks for devices such
as magnetic random access memories (MRAMs). The relevance for modern
computation of non-volatile high-frequency memories makes ac-transport
measurements of MTJs crucial for exploring this regime. Here we demonstrate a
frequency-mediated effect in which the tunnel magnetoimpedance reverses its
sign in a classical Co/Al{_2}O{_3}/NiFe MTJ, whereas we only observe a gradual
decrease of tunnel magnetophase. Such effects are explained by the capacitive
coupling of a parallel resistor and capacitor in the equivalent circuit model
of the MTJ. Furthermore, we report a positive tunnel magnetocapacitance effect,
suggesting the presence of a spin-capacitance at the two
ferromagnet/tunnel-barrier interfaces. Our results are important for
understanding spin transport phenomena at the high frequency regime, in which
the spin-polarized charge accumulation at the two interfaces plays a crucial
role.


title: Discovery of Dirac Node Arcs in PtSn4

abstract:
  In topological quantum materials the conduction and valence bands are
connected at points (Dirac/Weyl semimetals) or along lines (Line Node
semimetals) in the momentum space. Numbers of studies demonstrated that several
materials are indeed Dirac/Weyl semimetals. However, there is still no
experimental confirmation of materials with line nodes, in which the Dirac
nodes form closed loops in the momentum space. Here we report the discovery of
a novel topological structure - Dirac node arcs - in the ultrahigh
magnetoresistive material PtSn4 using laser-based angle-resolved photoemission
spectroscopy (ARPES) data and density functional theory (DFT) calculations.
Unlike the closed loops of line nodes, the Dirac node arc structure resembles
the Dirac dispersion in graphene that is extended along one dimension in
momentum space and confined by band gaps on either end. We propose that this
reported Dirac node arc structure is a novel topological state that provides a
novel platform for studying the exotic properties of Dirac Fermions.


title: Dynamics of Nonlinear Waves on Bounded Domains

abstract:
  This thesis is concerned with dynamics of conservative nonlinear waves on
bounded domains. In general, there are two scenarios of evolution. Either the
solution behaves in an oscillatory, quasiperiodic manner or the nonlinear
effects cause the energy to concentrate on smaller scales leading to a
turbulent behaviour. Which of these two possibilities occurs depends on a model
and the initial conditions. In the quasiperiodic scenario there exist very
special time-periodic solutions. They result for a delicate balance between
dispersion and nonlinear interaction. The main body of this dissertation is
concerned with construction (by means of perturbative and numerical methods) of
time-periodic solutions for various nonlinear wave equations on bounded
domains. While turbulence is mainly associated with hydrodynamics, recent
research in General Relativity has also revealed turbulent phenomena. Numerical
studies of a self-gravitating massless scalar field in spherical symmetry gave
evidence that anti-de Sitter space is unstable against black hole formation. On
the other hand there appeared many examples of asymptotically anti-de Sitter
solutions which evade turbulent behaviour and appear almost periodic for long
times. We discuss here these two contrasting scenarios putting special
attention to the construction and properties of strictly time-periodic
solutions. We analyze different models where solutions of this type exist.
Moreover, we describe similarities and differences among these models
concerning properties of time-periodic solutions and methods used for their
construction.


title: A size-sensitive inequality for cross-intersecting families

abstract:
  Two families $\mathcal A$ and $\mathcal B$ of $k$-subsets of an $n$-set are
called cross-intersecting if $A\cap B\ne\emptyset$ for all $A\in \mathcal A,
B\in \mathcal B $. Strengthening the classical Erd\H os-Ko-Rado theorem, Pyber
proved that $|\mathcal A||\mathcal B|\le {n-1\choose k-1}^2$ holds for $n\ge
2k$. In the present paper we sharpen this inequality. We prove that assuming
$|\mathcal B|\ge {n-1\choose k-1}+{n-i\choose k-i+1}$ for some $3\le i\le k+1$
the stronger inequality $$|\mathcal A||\mathcal B|\le \Bigl({n-1\choose
k-1}+{n-i\choose k-i+1}\Bigr)\Bigl({n-1\choose k-1}-{n-i\choose k-1}\Bigr)$$
holds. These inequalities are best possible.


title: Graph-based linear scaling electronic structure theory

abstract:
  We show how graph theory can be combined with quantum theory to calculate the
electronic structure of large complex systems. The graph formalism is general
and applicable to a broad range of electronic structure methods and materials,
including challenging systems such as biomolecules. The methodology combines
well-controlled accuracy, low computational cost, and natural low-communication
parallelism. This combination addresses substantial shortcomings of linear
scaling electronic structure theory, in particular with respect to
quantum-based molecular dynamics simulations.


title:
Intersection theorems for $\{0,\pm 1\}$-vectors and
  $s$-cross-intersecting families

abstract:
  In this paper we study two directions of extending the classical Erd\H
os-Ko-Rado theorem which states that any family of $k$-element subsets of the
set $[n] = \{1,\ldots,n\}$ in which any two sets intersect, has cardinality at
most ${n-1\choose k-1}$.
  In the first part of the paper we study the families of $\{0,\pm
1\}$-vectors. Denote by $\mathcal L_k$ the family of all vectors $\mathbf v$
from $\{0,\pm 1\}^n$ such that $\langle\mathbf v,\mathbf v\rangle = k$. For any
$k$, most $l$ and sufficiently large $n$ we determine the maximal size of the
family $\mathcal V\subset \mathcal L_k$ such that for any $\mathbf v,\mathbf
w\in \mathcal V$ we have $\langle \mathbf v,\mathbf w\rangle\ge l$. We find
some exact values of this function for all $n$ for small values of $k$.
  In the second part of the paper we study cross-intersecting pairs of
families. We say that two families are $\mathcal A, \mathcal B$ are
\textit{$s$-cross-intersecting}, if for any $A\in\mathcal A,B\in \mathcal B$ we
have $|A\cap B|\ge s$. We also say that a set family $\mathcal A$ is {\it
$t$-intersecting}, if for any $A_1,A_2\in \mathcal A$ we have $|A_1\cap A_2|\ge
t$. For a pair of nonempty $s$-cross-intersecting $t$-intersecting families
$\mathcal A,\mathcal B$ of $k$-sets, we determine the maximal value of
$|\mathcal A|+|\mathcal B|$ for $n$ sufficiently large.


title:
Routing Autonomous Vehicles in Congested Transportation Networks:
  Structural Properties and Coordination Algorithms

abstract:
  This paper considers the problem of routing and rebalancing a shared fleet of
autonomous (i.e., self-driving) vehicles providing on-demand mobility within a
capacitated transportation network, where congestion might disrupt throughput.
We model the problem within a network flow framework and show that under
relatively mild assumptions the rebalancing vehicles, if properly coordinated,
do not lead to an increase in congestion (in stark contrast to common belief).
From an algorithmic standpoint, such theoretical insight suggests that the
problem of routing customers and rebalancing vehicles can be decoupled, which
leads to a computationally-efficient routing and rebalancing algorithm for the
autonomous vehicles. Numerical experiments and case studies corroborate our
theoretical insights and show that the proposed algorithm outperforms
state-of-the-art point-to-point methods by avoiding excess congestion on the
road. Collectively, this paper provides a rigorous approach to the problem of
congestion-aware, system-wide coordination of autonomously driving vehicles,
and to the characterization of the sustainability of such robotic systems.


title:
Regularity for free interface variational problems in a general class of
  gradients

abstract:
  We present a way to study a wide class of optimal design problems with a
perimeter penalization. More precisely, we address existence and regularity
properties of saddle points of energies of the form $$ (u,A) \quad \mapsto
\quad \int_\Omega 2fu \; \text{d}x \; - \int_{\Omega \cap A} \sigma_1 \mathscr
A u \cdot \mathscr A u \; \text{d}x \; - \int_{\Omega \setminus A}
\sigma_2\mathscr A u\cdot \mathscr A u \; \text{d}x \; + \;
\text{Per}(A;\overline \Omega),$$ where $\Omega$ is a bounded Lipschitz domain,
$A\subset \mathbb R^N$ is a Borel set, $u:\Omega \subset \mathbb R^N \to
\mathbb R^d$, $\mathscr A$ is an operator of gradient form, and $\sigma_1,
\sigma_2$ are two not necessarily well-ordered symmetric tensors. The class of
operators of gradient form includes scalar- and vector-valued gradients,
symmetrized gradients, and higher order gradients. Therefore, our results may
be applied to a wide range of problems in elasticity, conductivity or
plasticity models.
  In this context and under mild assumptions on $f$, we show for a solution
$(w,A)$, that the topological boundary of $A \cap \Omega$ is locally a
$\rm{C}^1$-hypersurface up to a closed set of zero $\mathscr H^{N-1}$-measure.


title:
Bidirectional outflows as evidence of magnetic reconnection leading to a
  solar microflare

abstract:
  Magnetic reconnection is a rapid energy release process that is believed to
be responsible for flares on the Sun and stars. Nevertheless, such
flare-related reconnection is mostly detected to occur in the corona, while
there have been few studies concerning the reconnection in the chromosphere or
photosphere. Here we present both spectroscopic and imaging observations of
magnetic reconnection in the chromosphere leading to a microflare. During the
flare peak time, chromospheric line profiles show significant
blueshifted/redshifted components on the two sides of the flaring site,
corresponding to upflows and downflows with velocities of $\pm$(70--80) km
s$^{-1}$, comparable with the local Alfv\'{e}n speed as expected by the
reconnection in the chromosphere. The three-dimensional nonlinear force-free
field configuration further discloses twisted field lines (a flux rope) at a
low altitude, cospatial with the dark threads in He I 10830 \r{A} images. The
instability of the flux rope may initiate the flare-related reconnection. These
observations provide clear evidence of magnetic reconnection in the
chromosphere and show the similar mechanisms of a microflare to those of major
flares.


title:
Thermal spin current and spin accumulation at ferromagnetic
  insulator/nonmagnetic metal interface

abstract:
  Spin current injection and spin accumulation near a ferromagnetic insulator
(FI)/nonmagnetic metal (NM) bilayer film under a thermal gradient is
investigated theoretically. Using the Fermi golden rule and the Boltzmann
equations, we find that FI and NM can exchange spins via interfacial
electron-magnon scattering because of the imbalance between magnon emission and
absorption caused by either non-equilibrium distribution of magnons or
non-equilibrium between magnons and electrons. A temperature gradient in FI
and/or a temperature difference across the FI/NM interface generates a spin
current which carries angular momenta parallel to the magnetization of FI from
the hotter side to the colder one. Interestingly, the spin current induced by a
temperature gradient in NM is negligibly small due to the nonmagnetic nature of
the non-equilibrium electron distributions. The results agree well with all
existing experiments.


title: CVXPY: A Python-Embedded Modeling Language for Convex Optimization

abstract:
  CVXPY is a domain-specific language for convex optimization embedded in
Python. It allows the user to express convex optimization problems in a natural
syntax that follows the math, rather than in the restrictive standard form
required by solvers. CVXPY makes it easy to combine convex optimization with
high-level features of Python such as parallelism and object-oriented design.
CVXPY is available at http://www.cvxpy.org/ under the GPL license, along with
documentation and examples.


title: PCANet: An energy perspective

abstract:
  The principal component analysis network (PCANet), which is one of the
recently proposed deep learning architectures, achieves the state-of-the-art
classification accuracy in various databases. However, the explanation of the
PCANet is lacked. In this paper, we try to explain why PCANet works well from
energy perspective point of view based on a set of experiments. The impact of
various parameters on the error rate of PCANet is analyzed in depth. It was
found that this error rate is correlated with the logarithm of energy of image.
The proposed energy explanation approach can be used as a testing method for
checking if every step of the constructed networks is necessary.


title:
High-Order, Stable, And Efficient Pseudospectral Method Using
  Barycentric Gegenbauer Quadratures

abstract:
  The work reported in this article presents a high-order, stable, and
efficient Gegenbauer pseudospectral method to solve numerically a wide variety
of mathematical models. The proposed numerical scheme exploits the stability
and the well-conditioning of the numerical integration operators to produce
well-conditioned systems of algebraic equations, which can be solved easily
using standard algebraic system solvers. The core of the work lies in the
derivation of novel and stable Gegenbauer quadratures based on the stable
barycentric representation of Lagrange interpolating polynomials and the
explicit barycentric weights for the Gegenbauer-Gauss (GG) points. A rigorous
error and convergence analysis of the proposed quadratures is presented along
with a detailed set of pseudocodes for the established computational
algorithms. The proposed numerical scheme leads to a reduction in the
computational cost and time complexity required for computing the numerical
quadrature while sharing the same exponential order of accuracy achieved by
Elgindy and Smith-Miles (2013). The bulk of the work includes three numerical
test examples to assess the efficiency and accuracy of the numerical scheme.
The present method provides a strong addition to the arsenal of numerical
pseudospectral methods, and can be extended to solve a wide range of problems
arising in numerous applications.


title:
Zeta Functions and Complex Dimensions of Relative Fractal Drums: Theory,
  Examples and Applications

abstract:
  In 2009, the first author introduced a new class of zeta functions, called
`distance zeta functions', associated with arbitrary compact fractal subsets of
Euclidean spaces of arbitrary dimension. It represents a natural, but
nontrivial extension of the theory of `geometric zeta functions' of bounded
fractal strings. In this memoir, we introduce the class of `relative fractal
drums' (or RFDs), which contains the classes of bounded fractal strings and of
compact fractal subsets of Euclidean spaces as special cases. Furthermore, the
associated (relative) distance zeta functions of RFDs, extend (in a suitable
sense) the aforementioned classes of fractal zeta functions. This notion is
very general and flexible, enabling us to view practically all of the
previously studied aspects of the theory of fractal zeta functions from a
unified perspective as well as to go well beyond the previous theory. The
abscissa of (absolute) convergence of any relative fractal drum is equal to the
relative box dimension of the RFD. We pay particular attention to the question
of constructing meromorphic extensions of the distance zeta functions of RFDs,
as well as to the construction of transcendentally $\infty$-quasiperiodic RFDs
(i.e., roughly, RFDs with infinitely many quasiperiods, all of which are
algebraically independent). We also describe a class of RFDs (and, in
particular, a new class of bounded sets), called {\em maximal hyperfractals},
such that the critical line of (absolute) convergence consists solely of
nonremovable singularities of the associated relative distance zeta functions.
Finally, we also describe a class of Minkowski measurable RFDs which possess an
infinite sequence of complex dimensions of arbitrary multiplicity $m\ge1$, and
even an infinite sequence of essential singularities along the critical line.


title: X-ray properties of the Youngest Radio Sources and their Environments

abstract:
  We present the results of the first X-ray study of a sample of 16 young radio
sources classified as Compact Symmetric Objects (CSOs). We observed six of them
for the first time in X-rays using {\it Chandra}, re-observed four with the
previous {\it XMM-Newton} or {\it Beppo-SAX} data, and included six other with
the archival data. All the sources are nearby, $z<1$ with the age of their
radio structures ($<3000$~years) derived from the hotspots advance velocity.
Our results show heterogeneous nature of the CSOs indicating a complex
environment associated with young radio sources. The sample covers a range in
X-ray luminosity, $L_{2-10\,\rm keV} \sim 10^{41}$-$10^{45}$\,erg\,s$^{-1}$,
and intrinsic absorbing column density of $N_H \simeq
10^{21}$--10$^{22}$\,cm$^{-2}$. In particular, we detected extended X-ray
emission in 1718$-$649; a hard photon index of $\Gamma \simeq 1$ in 2021$+$614
and 1511$+$0518 consistent with either a Compton thick absorber or non-thermal
emission from compact radio lobes, and in 0710$+$439 an ionized iron emission
line at $E_{rest}=(6.62\pm0.04)$\,keV and EW $\sim 0.15-$1.4\,keV, and a
decrease by an order of magnitude in the 2-10 keV flux since the 2008 {\it
XMM-Newton} observation in 1607$+$26. We conclude that our pilot study of CSOs
provides a variety of exceptional diagnostics and highlights the importance of
deep X-ray observations of large samples of young sources. This is necessary in
order to constrain theoretical models for the earliest stage of radio source
evolution and study the interactions of young radio sources with the
interstellar environment of their host galaxies.


title:
Globally stable microresonator Turing pattern formation for coherent
  high-power THz radiation on-chip

abstract:
  In nonlinear microresonators driven by continuous-wave (cw) lasers, Turing
patterns have been studied in the formalism of Lugiato-Lefever equation with
emphasis on its high coherence and exceptional robustness against
perturbations. Destabilization of Turing pattern and transition to
spatio-temporal chaos, however, limits the available energy carried in the
Turing rolls and prevents further harvest of their high coherence and
robustness to noise. Here we report a novel scheme to circumvent such
destabilization, by incorporating the effect of local mode hybridizations, and
attain globally stable Turing pattern formation in chip-scale nonlinear
oscillators, achieving a record high power conversion efficiency of 45% and an
elevated peak-to-valley contrast of 100. The stationary Turing pattern is
discretely tunable across 430 GHz on a THz carrier, with a fractional frequency
sideband non-uniformity measured at 7.3x10^-14. We demonstrate the simultaneous
microwave and optical coherence of the Turing rolls at different evolution
stages through ultrafast optical correlation techniques. The free running
Turing roll coherence, 9 kHz in 200 ms and 160 kHz in 20 minutes, is
transferred onto a plasmonic photomixer for one of the highest power THz
coherent generation at room-temperature, with 1.1% optical-to-THz power
conversion. Its long-term stability can be further improved by more than two
orders of magnitude, reaching an Allan deviation of 6x10^-10 at 100 s, with a
simple computer-aided slow feedback control. The demonstrated on-chip coherent
high-power Turing-THz system is promising to find applications in astrophysics,
medical imaging, and wireless communications.


title: $n$-complete algebras and McKay quivers

abstract:
  Let $\Gamma^{n}$ be the cone of an $(n-1)$-complete algebra over an
algebraically closed field $k$. In this paper, we prove that if the bound
quiver $(Q_{n},\rho_{n})$ of $\Gamma^{n}$ is a truncation from the bound McKay
quiver $(Q_{G},\rho_{G})$ of a finite subgroup $G$ of $GL(n,k)$, the bound
quiver $(Q_{n+1}, \rho_{n+1})$ of $\Gamma^{n+1}$, the cone of $\Gamma^{n}$, is
a truncation from the bound McKay quiver
$(Q_{\widetilde{G}},\rho_{\widetilde{G}})$ of $\widetilde{G}$, where
$\widetilde{G}\cong G\times \mathbb{Z}_{m}$ for some $m\in \mathbb{N}$.


title:
The inhabitance paradox: how habitability and inhabitancy are
  inseparable

abstract:
  The dominant paradigm in assigning "habitability"' to terrestrial planets is
to define a circumstellar habitable zone: the locus of orbital radii in which
the planet is neither too hot nor too cold for life as we know it. One
dimensional climate models have identified theoretically impressive boundaries
for this zone: a runaway greenhouse or water loss at the inner edge (Venus),
and low-latitude glaciation followed by formation of CO2 clouds at the outer
edge. A cottage industry now exists to "refine" the definition of these
boundaries each year to the third decimal place of an AU. Using the same class
of climate model, I show that the different climate states can overlap very
substantially and that "snowball Earth", moist temperate climate, hot moist
climate and a post-runaway dry climate can all be stable under the same solar
flux. The radial extent of the temperate climate band is very narrow for pure
water atmospheres, but can be widened with di-nitrogen and carbon dioxide. The
width of the habitable zone is thus determined by the atmospheric inventories
of these gases. Yet Earth teaches us that these abundances are very heavily
influenced (perhaps even controlled) by biology. This is paradoxical: the
habitable zone seeks to define the region a planet should be capable of
harbouring life; yet whether the planet is inhabited will determine whether the
climate may be habitable at any given distance from the star. This matters,
because future life detection missions may use habitable zone boundaries in
mission design.


title: Stochastic Einstein equations with fluctuating volume

abstract:
  We develop a simple model to study classical fields on the background of a
fluctuating spacetime volume. It is applied to formulate the stochastic
Einstein equations with a perfect-fluid source. We investigate the particular
case of a stochastic Friedmann-Lema\^itre-Robertson-Walker cosmology, and show
that the resulting field equations can lead to solutions which avoid the
initial big bang singularity. By interpreting the fluctuations as the result of
the presence of a quantum spacetime, we conclude that classical singularities
can be avoided even within a stochastic model that include quantum effects in a
very simple manner.


title: Sparse model selection in the highly under-sampled regime

abstract:
  We propose a method for recovering the structure of a sparse undirected
graphical model when very few samples are available. The method decides about
the presence or absence of bonds between pairs of variable by considering one
pair at a time and using a closed form formula, analytically derived by
calculating the posterior probability for every possible model explaining a two
body system using Jeffreys prior. The approach does not rely on the
optimisation of any cost functions and consequently is much faster than
existing algorithms. Despite this time and computational advantage, numerical
results show that for several sparse topologies the algorithm is comparable to
the best existing algorithms, and is more accurate in the presence of hidden
variables. We apply this approach to the analysis of US stock market data and
to neural data, in order to show its efficiency in recovering robust
statistical dependencies in real data with non stationary correlations in time
and space.


title: On the representation dimension of smash products

abstract:
  Let $A$ be a finite dimensional $G$-graded algebra with $G$ a finite group,
and $A\# k[G]^{\ast}$ be the smash product of $A$ with the group $G$. Our
results can be stated as follows: (1) If $A$ is a self-injective algebra and
separably graded, then the dimensions of triangulated categories
$\underline{\rm mod}A$ and $\underline{\rm mod}A\# k[G]^{\ast}$ are equal. In
particular, we obtain that the representation dimension of $A\# k[G]^{\ast}$ is
at least the dimension of triangulated category $\underline{\rm mod}A$ plus 2;
(2) Generally, if $A$ is a $k$-algebra and separably graded, then the Oppermann
dimensions of $A$ and $A\# k[G]^{\ast}$ are equal. In particular, we obtain
that the representation dimension of $A\# k[G]^{\ast}$ is at least the
Oppermann dimension of $A$ plus 2. In the end, we give two examples to
illustrate our results.


title: Training Input-Output Recurrent Neural Networks through Spectral Methods

abstract:
  We consider the problem of training input-output recurrent neural networks
(RNN) for sequence labeling tasks. We propose a novel spectral approach for
learning the network parameters. It is based on decomposition of the
cross-moment tensor between the output and a non-linear transformation of the
input, based on score functions. We guarantee consistent learning with
polynomial sample and computational complexity under transparent conditions
such as non-degeneracy of model parameters, polynomial activations for the
neurons, and a Markovian evolution of the input sequence. We also extend our
results to Bidirectional RNN which uses both previous and future information to
output the label at each time point, and is employed in many NLP tasks such as
POS tagging.


title:
Decentralized State Estimation via a Hybrid of Consensus and Covariance
  intersection

abstract:
  This paper presents a new recursive information consensus filter for
decentralized dynamic-state estimation. No structure is assumed about the
topology of the network and local estimators are assumed to have access only to
local information. The network need not be connected at all times. Consensus
over priors which might become correlated is performed through Covariance
Intersection (CI) and consensus over new information is handled using weights
based on a Metropolis Hastings Markov Chains. We establish bounds for
estimation performance and show that our method produces unbiased conservative
estimates that are better than CI. The performance of the proposed method is
evaluated and compared with competing algorithms on an atmospheric dispersion
problem.


title:
Derivative of the standard $p$-adic $L$-function associated with a
  Siegel form

abstract:
  In this paper we construct a two variables $p$-adic $L$-function for the
standard representation associated with a Hida family of parallel weight genus
$g$ Siegel forms, using a method previously developed by B\"ocherer--Schmidt in
one variable. When a form of weight $g+1$ is Steinberg at $p$, a trivial zero
appears and, using the method of Greenberg--Stevens, we calculate the first
derivative of this $p$-adic $L$-function and show that it has the form
predicted by a conjecture of Greenberg on trivial zeros.


title:
Question Answering on Freebase via Relation Extraction and Textual
  Evidence

abstract:
  Existing knowledge-based question answering systems often rely on small
annotated training data. While shallow methods like relation extraction are
robust to data scarcity, they are less expressive than the deep meaning
representation methods like semantic parsing, thereby failing at answering
questions involving multiple constraints. Here we alleviate this problem by
empowering a relation extraction method with additional evidence from
Wikipedia. We first present a neural network based relation extractor to
retrieve the candidate answers from Freebase, and then infer over Wikipedia to
validate these answers. Experiments on the WebQuestions question answering
dataset show that our method achieves an F_1 of 53.3%, a substantial
improvement over the state-of-the-art.


title:
Tus-Ter-lock immuno-PCR assays for the sensitive detection of
  tropomyosin-specific IgE antibodies

abstract:
  Background: The increasing prevalence of food allergies requires development
of specific and sensitive tests capable of identifying the allergen responsible
for the disease. The development of serologic tests that can detect specific
IgE antibodies to allergenic proteins would therefore be highly received.
Results: Here we present two new quantitative immuno-PCR assays for the
sensitive detection of antibodies specific to the shrimp allergen tropomyosin.
Both assays are based on the self-assembling Tus-Ter-lock protein-DNA
conjugation system. Significantly elevated levels of tropomyosin-specific IgE
were detected in sera from patients allergic to shrimp. Conclusions: This is
the first time an allergenic protein has been fused with Tus to enable specific
IgE antibody detection in human sera by quantitative immuno-PCR.


title:
Exploring group theory and topology for analyzing the structure of
  biology

abstract:
  The concepts of population and species play a fundamental role in biology.
The existence and precise definition of higher-order hierarchies, such as
division into species, is open to debate among biologists. First, we seek to
show a fractal structure of species. We are able to define a species as a
$p$-Sylow subgroup of a particular community in a single niche, confirmed by
topological analysis. We named this model the patch with zeta dominance (PzDom)
model. Next, the topological nature of the system is carefully examined and for
testing purposes, species density data are used in conjunction with data
derived from liquid-chromatography mass spectrometry of proteins. We confirm
the induction of hierarchy and time through a one-dimensional probability space
with certain topologies. For further clarification of induced fractals
including the relation to renormalization in physics, a theoretical development
is proposed based on a newly identified fact, namely that scaling parameters
for magnetization exactly correspond to imaginary parts of the Riemann zeta
function's nontrivial zeros. A master torus and a Lagrangian/Hamiltonian are
derived expressing fractal structures as a solution for diminishing divergent
terms in renormalization. We will also focus on an application of our developed
model. We extend current PzDom model to the so-called exPzDom model to qualify
population dynamics as a topological matter as a whole, not focusing on
hierarchy. The indicators in the exPzDom model adhere well to the empirical
dynamics of SARS-CoV-2 infected people and align appropriately with actual
policies instituted by the Japanese government. In our patch with zeta
dominance (PzDom) model or its extended version (exPzDom), calculations only
require knowledge of the density of individuals over time.


title:
Cellular Automata Segmentation of the Boundary between the Compacta of
  Vertebral Bodies and Surrounding Structures

abstract:
  Due to the aging population, spinal diseases get more and more common
nowadays; e.g., lifetime risk of osteoporotic fracture is 40% for white women
and 13% for white men in the United States. Thus the numbers of surgical spinal
procedures are also increasing with the aging population and precise diagnosis
plays a vital role in reducing complication and recurrence of symptoms. Spinal
imaging of vertebral column is a tedious process subjected to interpretation
errors. In this contribution, we aim to reduce time and error for vertebral
interpretation by applying and studying the GrowCut-algorithm for boundary
segmentation between vertebral body compacta and surrounding structures.
GrowCut is a competitive region growing algorithm using cellular automata. For
our study, vertebral T2-weighted Magnetic Resonance Imaging (MRI) scans were
first manually outlined by neurosurgeons. Then, the vertebral bodies were
segmented in the medical images by a GrowCut-trained physician using the
semi-automated GrowCut-algorithm. Afterwards, results of both segmentation
processes were compared using the Dice Similarity Coefficient (DSC) and the
Hausdorff Distance (HD) which yielded to a DSC of 82.99+/-5.03% and a HD of
18.91+/-7.2 voxel, respectively. In addition, the times have been measured
during the manual and the GrowCut segmentations, showing that a
GrowCut-segmentation - with an average time of less than six minutes
(5.77+/-0.73) - is significantly shorter than a pure manual outlining.


title:
Interactive and Scale Invariant Segmentation of the Rectum/Sigmoid via
  User-Defined Templates

abstract:
  Among all types of cancer, gynecological malignancies belong to the 4th most
frequent type of cancer among women. Besides chemotherapy and external beam
radiation, brachytherapy is the standard procedure for the treatment of these
malignancies. In the progress of treatment planning, localization of the tumor
as the target volume and adjacent organs of risks by segmentation is crucial to
accomplish an optimal radiation distribution to the tumor while simultaneously
preserving healthy tissue. Segmentation is performed manually and represents a
time-consuming task in clinical daily routine. This study focuses on the
segmentation of the rectum/sigmoid colon as an Organ-At-Risk in gynecological
brachytherapy. The proposed segmentation method uses an interactive,
graph-based segmentation scheme with a user-defined template. The scheme
creates a directed two dimensional graph, followed by the minimal cost closed
set computation on the graph, resulting in an outlining of the rectum. The
graphs outline is dynamically adapted to the last calculated cut. Evaluation
was performed by comparing manual segmentations of the rectum/sigmoid colon to
results achieved with the proposed method. The comparison of the algorithmic to
manual results yielded to a Dice Similarity Coefficient value of 83.85+/-4.08%,
in comparison to 83.97+/-8.08% for the comparison of two manual segmentations
of the same physician. Utilizing the proposed methodology resulted in a median
time of 128 seconds per dataset, compared to 300 seconds needed for pure manual
segmentation.


title: Diphoton and Diboson Probes of Fermiophobic Higgs Bosons at the LHC

abstract:
  Extensions of the Standard Model Higgs sector with electroweak charged
scalars can possess exotic `Higgs' bosons with vanishing or suppressed
couplings to Standard Model fermions. These `fermiophobic' scalars, which
cannot be produced via gluon fusion, are constrained by LHC measurements of the
125 GeV Higgs boson to have a small vacuum expectation value. This implies that
vector boson fusion and associated vector boson production are in general
suppressed rendering conventional Higgs searches insensitive. However,
Drell-Yan Higgs pair production, which is not present in the SM, can be
sizeable even in the limit of vanishing exotic Higgs vacuum expectation value.
We utilize this to show that diphoton searches at 8 TeV LHC already rule out a
large class of neutral fermiophobic Higgs bosons below around 110 GeV. This
includes fermiophobic scalars found in two Higgs doublet as well as Higgs
triplet and Georgi-Machacek type models. Our results extend the only relevant
limit on fermiophobic Higgs bosons obtained by a recent CDF analysis of
$4\gamma + X$ Tevatron data. Furthermore, diphoton limits are independent of
the decay of the second Higgs boson and thus apply even for degenerate masses
in contrast to the CDF search. We also find that if the fermiophobic Higgs has
very enhanced couplings to photons, masses as large as $\sim 150$ GeV can be
ruled out while if these couplings are somehow highly suppressed, masses below
$\sim 90$ GeV can still be ruled out. Finally, we show that $WW$ and $ZZ$
diboson searches may serve as complementary probes for masses above the
diphoton limit up to $\sim 250$ GeV and discuss prospects at 13 TeV LHC.


title: Using Quadrilaterals to Compute the Shortest Path

abstract:
  We introduce a new heuristic for the A* algorithm that references a data
structure significantly smaller than that of ALT. We characterize the behavior
of this new heuristic based on a dual landmark configuration that leverages
quadrilateral inequalities to identify the lower bound for shortest path. Using
this approach, we demonstrate both the utility and detriments of using polygon
inequalities aside from the triangle inequality to establish lower bounds for
shortest path queries. While this new heuristic does not dominate previous
heuristics based on triangle inequalities, the inverse is true, as well.
Further, we demonstrate that an A* heuristic function does not necessarily
outperform another heuristic that it dominates. In comparison to other landmark
methods, the new heuristic maintains a larger average search space while
commonly decreasing the number of computed arithmetic operations. The new
heuristic can significantly outperform previous methods, particularly in graphs
with larger path lengths. The characterization of the use of these inequalities
for bounding offers insight into its applications in other theoretical spaces.


title: Object Manipulation Learning by Imitation

abstract:
  We aim to enable robot to learn object manipulation by imitation. Given
external observations of demonstrations on object manipulations, we believe
that two underlying problems to address in learning by imitation is 1) segment
a given demonstration into skills that can be individually learned and reused,
and 2) formulate the correct RL (Reinforcement Learning) problem that only
considers the relevant aspects of each skill so that the policy for each skill
can be effectively learned. Previous works made certain progress in this
direction, but none has taken private information into account. The public
information is the information that is available in the external observations
of demonstration, and the private information is the information that are only
available to the agent that executes the actions, such as tactile sensations.
Our contribution is that we provide a method for the robot to automatically
segment the demonstration of object manipulations into multiple skills, and
formulate the correct RL problem for each skill, and automatically decide
whether the private information is an important aspect of each skill based on
interaction with the world. Our experiment shows that our robot learns to pick
up a block, and stack it onto another block by imitating an observed
demonstration. The evaluation is based on 1) whether the demonstration is
reasonably segmented, 2) whether the correct RL problems are formulated, 3) and
whether a good policy is learned.


title:
Search for Gamma-ray Emission from Dark Matter Annihilation in the Small
  Magellanic Cloud with the Fermi Large Area Telescope

abstract:
  The Small Magellanic Cloud (SMC) is the second-largest satellite galaxy of
the Milky Way and is only 60 kpc away. As a nearby, massive, and dense object
with relatively low astrophysical backgrounds, it is a natural target for dark
matter indirect detection searches. In this work, we use six years of Pass 8
data from the Fermi Large Area Telescope to search for gamma-ray signals of
dark matter annihilation in the SMC. Using data-driven fits to the gamma-ray
backgrounds, and a combination of N-body simulations and direct measurements of
rotation curves to estimate the SMC DM density profile, we found that the SMC
was well described by standard astrophysical sources, and no signal from dark
matter annihilation was detected. We set conservative upper limits on the dark
matter annihilation cross section. These constraints are in agreement with
stronger constraints set by searches in the Large Magellanic Cloud and approach
the canonical thermal relic cross section at dark matter masses lower than 10
GeV in the $b\bar{b}$ and $\tau^+\tau^-$ channels.


title: Classical and quantum spherical pendulum

abstract:
  This paper extends the Bohr-Sommerfeld quantization of the spherical pendulum
to a full quantum theory. This the first application of geometric quantization
to a classical system with monodromy.


title:
Of Genes and Machines: application of a combination of machine learning
  tools to astronomy datasets

abstract:
  We apply a combination of a Genetic Algorithms (GA) and Support Vector
Machines (SVM) machine learning algorithm to solve two important problems faced
by the astronomical community: star/galaxy separation, and photometric redshift
estimation of galaxies in survey catalogs. We use the GA to select the relevant
features in the first step, followed by optimization of SVM parameters in the
second step to obtain an optimal set of parameters to classify or regress, in
process of which we avoid over-fitting. We apply our method to star/galaxy
separation in Pan-STARRS1 data. We show that our method correctly classifies
98% of objects down to i_P1= 24.5, with a completeness (or true positive rate)
of 99% for galaxies, and 88% for stars. By combining colors with morphology,
our star/classification method yields better results than the new SExtractor
classifier spread_model in particular at the faint end (i_P1>22). We also use
our method to derive photometric redshifts for galaxies in the COSMOS bright
multi-wavelength dataset down to an error in (1+z) of sigma=0.013, which
compares well with estimates from SED fitting on the same data (sigma=0.007)
while making a significantly smaller number of assumptions.


title:
MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for
  Sentence Classification

abstract:
  We introduce a novel, simple convolution neural network (CNN) architecture -
multi-group norm constraint CNN (MGNC-CNN) that capitalizes on multiple sets of
word embeddings for sentence classification. MGNC-CNN extracts features from
input embedding sets independently and then joins these at the penultimate
layer in the network to form a final feature vector. We then adopt a group
regularization strategy that differentially penalizes weights associated with
the subcomponents generated from the respective embedding sets. This model is
much simpler than comparable alternative architectures and requires
substantially less training time. Furthermore, it is flexible in that it does
not require input word embeddings to be of the same dimensionality. We show
that MGNC-CNN consistently outperforms baseline models.


title: Group dualities, T-dualities, and twisted K-theory

abstract:
  This paper explores further the connection between Langlands duality and
T-duality for compact simple Lie groups, which appeared in work of Daenzer-Van
Erp and Bunke-Nikolaus. We show that Langlands duality gives rise to
isomorphisms of twisted K-groups, but that these K-groups are trivial except in
the simplest case of SU(2) and SO(3). Along the way we compute explicitly the
map on $H^3$ induced by a covering of compact simple Lie groups, which is
either 1 or 2 depending in a complicated way on the type of the groups
involved. We also give a new method for computing twisted K-theory using the
Segal spectral sequence, giving simpler computations of certain twisted
K-theory groups of compact Lie groups relevant for D-brane charges in WZW
theories and rank-level dualities. Finally we study a duality for orientifolds
based on complex Lie groups with an involution.


title: Inverted crossover resonance aiding laser cooling of $^{171}$Yb

abstract:
  We observe an inverted crossover resonance in $\pi$-driven four-level
systems, where $F'-F=0,+1$. The signal is observed through saturated absorption
spectroscopy of the $(6s^{2})$ $^{1}S_{0}$ $-$ $(6s6p)$ $^{3}P_{1}$ transition
in $^{171}$Yb, where the nuclear spin $I=1/2$. The enhanced absorption signal
is used to generate a dispersive curve for 556 nm laser frequency stabilisation
and the stabilised light cools $^{171}$Yb atoms in a two-stage magneto-optical
trap, achieving temperatures of 20 $\mu$K. The Doppler-free spectroscopy scheme
is further used to measure isotopic frequency shifts and hyperfine separations
for the intercombination line in ytterbium.


title:
Direct penetration of spin-triplet superconductivity into a ferromagnet
  in Au/SrRuO3/Sr2RuO4 junctions

abstract:
  Efforts have been ongoing to establish superconducting spintronics utilizing
ferromagnet/superconductor heterostructures1. Previously reported devices are
based on spin-singlet superconductors (SSCs), where the spin degree of freedom
is lost. Spin-polarized supercurrent induction in ferromagnetic metals (FMs) is
achieved even with SSCs, but only with the aid of interfacial complex magnetic
structures, which severely affect information imprinted to the electron spin.
Use of spin-triplet superconductors (TSCs) with active spins potentially
overcomes this difficulty and further leads to novel functionalities. Here, we
report spin-triplet superconductivity induction into a FM SrRuO3 from a leading
TSC candidate Sr2RuO4, by fabricating microscopic devices using an epitaxial
SrRuO3/Sr2RuO4 hybrid. The differential conductance, exhibiting
Andreev-reflection features with multiple energy scales up to around half
tesla, indicates the penetration of superconductivity over a considerable
distance of 15 nm across the SrRuO3 layer without help of interfacial complex
magnetism. This demonstrates the first FM/TSC device exhibiting the
spin-triplet proximity effect.


title: Donaldson-Thomas Transformation of Grassmannian

abstract:
  Kontsevich and Soibelman defined the notion of Donaldson-Thomas invariants of
a 3d Calabi-Yau category with a stability condition. A family of examples of
such categories can be constructed from an arbitrary cluster variety. The
corresponding Donaldson-Thomas invariants are encoded by a special formal
automorphism of the cluster variety, known as Donaldson-Thomas transformation.
  Fix two integers $m$ and $n$ with $1<m<m+1<n$. It is known that the
configuration space $\mathrm{Conf}_n(\mathbb{P}^{m-1})$, closely related to
Grassmannian $\mathrm{Gr}_m(n)$, is a cluster Poisson variety. In this paper we
determine the Donaldson-Thomas transformation of
$\mathrm{Conf}_n(\mathbb{P}^{m-1})$ as an explicitly defined birational
automorphism of $\mathrm{Conf}_n(\mathbb{P}^{m-1})$. Its variant acts on the
Grassmannian by a birational automorphism.


title: Tight Analysis of a Multiple-Swap Heuristic for Budgeted Red-Blue Median

abstract:
  Budgeted Red-Blue Median is a generalization of classic $k$-Median in that
there are two sets of facilities, say $\mathcal{R}$ and $\mathcal{B}$, that can
be used to serve clients located in some metric space. The goal is to open
$k_r$ facilities in $\mathcal{R}$ and $k_b$ facilities in $\mathcal{B}$ for
some given bounds $k_r, k_b$ and connect each client to their nearest open
facility in a way that minimizes the total connection cost.
  We extend work by Hajiaghayi, Khandekar, and Kortsarz [2012] and show that a
multiple-swap local search heuristic can be used to obtain a
$(5+\epsilon)$-approximation for Budgeted Red-Blue Median for any constant
$\epsilon > 0$. This is an improvement over their single swap analysis and
beats the previous best approximation guarantee of 8 by Swamy [2014].
  We also present a matching lower bound showing that for every $p \geq 1$,
there are instances of Budgeted Red-Blue Median with local optimum solutions
for the $p$-swap heuristic whose cost is $5 + \Omega\left(\frac{1}{p}\right)$
times the optimum solution cost. Thus, our analysis is tight up to the lower
order terms. In particular, for any $\epsilon > 0$ we show the single-swap
heuristic admits local optima whose cost can be as bad as $7-\epsilon$ times
the optimum solution cost.


title: Regression Analysis for Microbiome Compositional Data

abstract:
  One important problem in microbiome analysis is to identify the bacterial
taxa that are associated with a response, where the microbiome data are
summarized as the composition of the bacterial taxa at different taxonomic
levels. This paper considers regression analysis with such compositional data
as covariates. In order to satisfy the subcompositional coherence of the
results, linear models with a set of linear constraints on the regression
coefficients are introduced. Such models allow regression analysis for
subcompositions and include the log-contrast model for compositional covariates
as a special case. A penalized estimation procedure for estimating the
regression coefficients and for selecting variables under the linear
constraints is developed. A method is also proposed to obtain de-biased
estimates of the regression coefficients that are asymptotically unbiased and
have a joint asymptotic multivariate normal distribution. This provides valid
confidence intervals of the regression coefficients and can be used to obtain
the $p$-values. Simulation results show the validity of the confidence
intervals and smaller variances of the de-biased estimates when the linear
constraints are imposed. The proposed methods are applied to a gut microbiome
data set and identify four bacterial genera that are associated with the body
mass index after adjusting for the total fat and caloric intakes.


title: Formalising Confluence in PVS

abstract:
  Confluence is a critical property of computational systems which is related
with determinism and non ambiguity and thus with other relevant computational
attributes of functional specifications and rewriting system as termination and
completion. Several criteria have been explored that guarantee confluence and
their formalisations provide further interesting information. This work
discusses topics and presents personal positions and views related with the
formalisation of confluence properties in the Prototype Verification System PVS
developed at our research group.


title: Compositional model checking of concurrent systems, with Petri nets

abstract:
  Compositionality and process equivalence are both standard concepts of
process algebra. Compositionality means that the behaviour of a compound system
relies only on the behaviour of its components, i.e. there is no emergent
behaviour. Process equivalence means that the explicit statespace of a system
takes a back seat to its interaction patterns: the information that an
environment can obtain though interaction.
  Petri nets are a classical, yet widely used and understood, model of
concurrency. Nevertheless, they have often been described as a
non-compositional model, and tools tend to deal with monolithic,
globally-specified models.
  This tutorial paper concentrates on Petri Nets with Boundaries (PNB): a
compositional, graphical algebra of 1-safe nets, and its applications to
reachability checking within the tool Penrose. The algorithms feature the use
of compositionality and process equivalence, a powerful combination that can be
harnessed to improve the performance of checking reachability and coverability
in several common examples where Petri nets model realistic concurrent systems.


title: Generation, Ranking and Unranking of Ordered Trees with Degree Bounds

abstract:
  We study the problem of generating, ranking and unranking of unlabeled
ordered trees whose nodes have maximum degree of $\Delta$. This class of trees
represents a generalization of chemical trees. A chemical tree is an unlabeled
tree in which no node has degree greater than 4. By allowing up to $\Delta$
children for each node of chemical tree instead of 4, we will have a
generalization of chemical trees. Here, we introduce a new encoding over an
alphabet of size 4 for representing unlabeled ordered trees with maximum degree
of $\Delta$. We use this encoding for generating these trees in A-order with
constant average time and O(n) worst case time. Due to the given encoding, with
a precomputation of size and time O(n^2) (assuming $\Delta$ is constant), both
ranking and unranking algorithms are also designed taking O(n) and O(nlogn)
time complexities.


title: Finiteness and Computation in Toposes

abstract:
  Some notions in mathematics can be considered relative. Relative is a term
used to denote when the variation in the position of an observer implies
variation in properties or measures on the observed object. We know, from
Skolem theorem, that there are first-order models where the set of real numbers
is countable and some where it is not. This fact depends on the position of the
observer and on the instrument/language the obserevr uses as well, i.e., it
depends on whether he/she is inside the model or not and in this particular
case the use of first-order logic. In this article, we assume that computation
is based on finiteness rather than natural numbers and discuss Turing machines
computable morphisms defined on top of the sole notion finiteness. We explore
the relativity of finiteness in models provided by toposes where the Axiom of
Choice (AC) does not hold, since Tarski proved that if AC holds then all
finiteness notions are equivalent. Our toposes do not have natural numbers
object (NNO) either, since in a topos with a NNO these finiteness notions are
equivalent to Peano finiteness going back to computation on top of Natural
Numbers. The main contribution of this article is to show that although from
inside every topos, with the properties previously stated, the computation
model is standard, from outside some of these toposes, unexpected properties on
the computation arise, e.g., infinitely long programs, finite computations
containing infinitely long ones, infinitely branching computations. We mainly
consider Dedekind and Kuratowski notions of finiteness in this article.


title:
Mean-Field Semantics for a Process Calculus for Spatially-Explicit
  Ecological Models

abstract:
  We define a mean-field semantics for S-PALPS, a process calculus for
spatially-explicit, individual-based modeling of ecological systems. The new
semantics of S-PALPS allows an interpretation of the average behavior of a
system as a set of recurrence equations. Recurrence equations are a useful
approximation when dealing with a large number of individuals, as it is the
case in epidemiological studies. As a case study, we compute a set of
recurrence equations capturing the dynamics of an individual-based model of the
transmission of dengue in Bello (Antioquia), Colombia.


title: Local Map Descriptor for Compressive Change Retrieval

abstract:
  Change detection, i.e., anomaly detection from local maps built by a mobile
robot at multiple different times, is a challenging problem to solve in
practice. Most previous work either cannot be applied to scenarios where the
size of the map collection is large, or simply assumed that the robot
self-location is globally known. In this paper, we tackle the problem of
simultaneous self-localization and change detection, by reformulating the
problem as a map retrieval problem, and propose a local map descriptor with a
compressed bag-of-words (BoW) structure as a scalable solution. We make the
following contributions. (1) To enable a direct comparison of the spatial
layout of visual features between different local maps, the origin of the local
map coordinate (termed "viewpoint") is planned by scene parsing and determined
by our "viewpoint planner" to be invariant against small variations in
self-location and changes, aiming at providing similar viewpoints for similar
scenes (i.e., the relevant map pair). (2) We extend the BoW model to enable the
use of not only the appearance (e.g., polestar) but also the spatial layout
(e.g., spatial pyramid) of visual features with respect to the planned
viewpoint. The key observation is that the planned viewpoint (i.e., the origin
of local map coordinate) acts as a pseudo viewpoint that is usually required by
spatial BoW (e.g., SPM) and also by anomaly detection (e.g., NN-d, LOF). (3)
Experimental results on a challenging "loop-closing" scenario show that the
proposed method outperforms previous BoW methods in self-localization, and
furthermore, that the use of both appearance and pose information in change
detection produces better results than the use of either information alone.


title:
Thermodynamics and Geometrothermodynamics of Charged black holes in
  Massive Gravity

abstract:
  The objective of this paper is to study the thermodynamics and thermodynamic
geometry of charged de-Sitter and charged anti de-Sitter black hole solutions
in massive gravity. We study the effect of curvature parameter as well as the
mass of graviton in the thermodynamics of the black hole system. We further
extend our studies to different topology of the space time and its effects on
phase transition and thermodynamics. In addition, the phase transition
structure of the black hole and its interactions are reproduced using
geometrothermodynamics.


title:
Audio Word2Vec: Unsupervised Learning of Audio Segment Representations
  using Sequence-to-sequence Autoencoder

abstract:
  The vector representations of fixed dimensionality for words (in text)
offered by Word2Vec have been shown to be very useful in many application
scenarios, in particular due to the semantic information they carry. This paper
proposes a parallel version, the Audio Word2Vec. It offers the vector
representations of fixed dimensionality for variable-length audio segments.
These vector representations are shown to describe the sequential phonetic
structures of the audio segments to a good degree, with very attractive real
world applications such as query-by-example Spoken Term Detection (STD). In
this STD application, the proposed approach significantly outperformed the
conventional Dynamic Time Warping (DTW) based approaches at significantly lower
computation requirements. We propose unsupervised learning of Audio Word2Vec
from audio data without human annotation using Sequence-to-sequence Audoencoder
(SA). SA consists of two RNNs equipped with Long Short-Term Memory (LSTM)
units: the first RNN (encoder) maps the input audio sequence into a vector
representation of fixed dimensionality, and the second RNN (decoder) maps the
representation back to the input audio sequence. The two RNNs are jointly
trained by minimizing the reconstruction error. Denoising Sequence-to-sequence
Autoencoder (DSA) is furthered proposed offering more robust learning.


title:
The H$\alpha$ surface brightness $-$ radius plane as a diagnostic tool
  for photoionized nebulae

abstract:
  The H$\alpha$ surface brightness $-$ radius ($S-r$) relation is a robust
distance indicator for planetary nebulae (PNe), further enhanced by different
populations of PNe having distinct loci in $S-r$ space. Other types of
photoionized nebulae also plot in quite distinct regions in the $S-r$ plane,
allowing its use as a diagnostic tool. In particular, the nova shells and
massive star ejecta (MSE) plot on relatively tight loci illustrating their
evolutionary sequences. For the MSE, there is potential to develop a distance
indicator for these objects, based on their trend in $S-r$ space. As
high-resolution, narrowband surveys of the nearest galaxies become more
commonplace, the $S-r$ plane is a potentially useful diagnostic tool to help
identify the various ionized nebulae in these systems.


title:
David vs Goliath (You against the Markets), A Dynamic Programming
  Approach to Separate the Impact and Timing of Trading Costs

abstract:
  We develop a fundamentally different stochastic dynamic programming model of
trading costs. Built on a strong theoretical foundation, our model provides
insights to market participants by splitting the overall move of the security
price during the duration of an order into the Market Impact (price move caused
by their actions) and Market Timing (price move caused by everyone else)
components. We derive formulations of this model under different laws of motion
of the security prices, starting with a simple benchmark scenario and extending
this to include multiple sources of uncertainty, liquidity constraints due to
volume curve shifts and relating trading costs to the spread. We develop a
numerical framework that can be used to obtain optimal executions under any law
of motion of prices and demonstrate the tremendous practical applicability of
our theoretical methodology including the powerful numerical techniques to
implement them. Our decomposition of trading costs into Market Impact and
Market Timing allows us to deduce the zero sum game nature of trading costs. It
holds numerous lessons for dealing with complex systems, wherein reducing the
complexity by splitting the many sources of uncertainty can lead to better
insights in the decision process.


title: Theory of diffusive light scattering cancellation cloaking

abstract:
  We report on a new concept of cloaking objects in diffusive light regime
using the paradigm of the scattering cancellation and mantle cloaking
techniques. We show numerically that an object can be made completely invisible
to diffusive photon density waves, by tailoring the diffusivity constant of the
spherical shell enclosing the object. This means that photons' flow outside the
object and the cloak made of these spherical shells behaves as if the object
were not present. Diffusive light invisibility may open new vistas in hiding
hot spots in infrared thermography or tissue imaging.


title:
Local solution to the $G_{2}-$monopole equation with prescribed tangent
  cone and $G_{2}-$structure

abstract:
  For any locally defined $G_{2}-$structure and Hermitian-Yang-Mills connection
on $S^{6}$, the $G_{2}-$monopole equation always admits a local solution that
is asymptotic to the HYM-connection.


title: Securities Lending Strategies: Exclusive Valuations and Auction Bids

abstract:
  We derive valuations of a portfolio of financial instruments from a
securities lending perspective, under different assumptions, and show a
weighting scheme that converges to the true valuation. We illustrate conditions
under which our alternative weighting scheme converges faster to the true
valuation when compared to the minimum variance weighting. This weighting
scheme is applicable in any situation where multiple forecasts are made and we
need a methodology to combine them. Our valuations can be useful either to
derive a bidding strategy for an exclusive auction or to design an appropriate
auction mechanism, depending on which side of the fence a participant sits
(whether the interest is to procure the rights to use a portfolio for making
stock loans such as for a lending desk, or, to obtain additional revenue from a
portfolio such as from the point of view of a long only asset management firm).
Lastly, we run simulations to establish numerical examples for the set of
valuations and for various bidding strategies corresponding to different
auction settings.


title: Learning Functions: When Is Deep Better Than Shallow

abstract:
  While the universal approximation property holds both for hierarchical and
shallow networks, we prove that deep (hierarchical) networks can approximate
the class of compositional functions with the same accuracy as shallow networks
but with exponentially lower number of training parameters as well as
VC-dimension. This theorem settles an old conjecture by Bengio on the role of
depth in networks. We then define a general class of scalable, shift-invariant
algorithms to show a simple and natural set of requirements that justify deep
convolutional networks.


title: Hadron Interactions from lattice QCD

abstract:
  We review our strategy to study hadron interactions from lattice QCD using
newly proposed potential method. We first explain our strategy in the case of
nuclear potentials and its application to nuclear physics. We then discuss the
origin of the repulsive core, by adding strange quarks to the system. We also
explore a possibility for H-dibaryon to exist in flavor SU(3) limit of lattice
QCD. We conclude the paper with an application of our strategy to investigate
the maximum mass of neutron stars.


title:
Energy identity for approximate harmonic maps from surface to general
  targets

abstract:
  Let $u_n$ be a sequence of mappings from a closed Riemannian surface $M$ to a
general Riemannian manifold $N$. If $u_n$ satisfies \beno \sup_{n}\big(\|\nabla
u_n\|_{L^2(M)}+\|\tau(u_n)\|_{L^{p}(M)}\big)\leq \Lambda\quad \text{for
some}\,\,p>1, \eeno where $\tau(u_n)$ is the tension field of $u_n$, then there
hold the so called energy identity and neckless property during blowing up.
This result is sharp by Parker's example, where the tension fields of the
mappings from Riemannian surface are bounded in $L^1(M)$ but the energy
identity fails.


title: Financial Services, Economic Growth and Well-Being: A Four-Pronged Study

abstract:
  A four-pronged approach to dealing with Social Science Phenomenon is
outlined. This methodology is applied to Financial Services, Economic Growth
and Well-Being. The four prongs are like the four directions for an army
general looking for victory. Just like the four directions, we need to be aware
that there is a degree of interconnectedness in the below four prongs.
-Uncertainty Principle of the Social Sciences -Responsibilities of Fiscal
Janitors -Need for Smaller Organizations -Redirecting Growth that Generates
Garbage The importance of gaining a more profound comprehension of welfare and
delineating its components into those that result from an increase in goods and
services, and hence can be attributed to economic growth, and into those that
are not related to economic growth but lead to a better quality of life, is
highlighted. The reasoning being that economic growth alone is an inadequate
indicator of well-being. Hand in hand with a better understanding of the
characteristics of welfare, comes the need to consider the metrics we currently
have that gauge economic growth and supplement those with measures that capture
well-being more holistically.


title:
Multidimensionally-constrained relativistic mean-field study of
  spontaneous fission: coupling between shape and pairing degrees of freedom

abstract:
  Studies of fission dynamics, based on nuclear energy density functionals,
have shown that the coupling between shape and pairing degrees of freedom has a
pronounced effect on the nonperturbative collective inertia and, therefore, on
dynamic (least-action) spontaneous fission paths and half-lives.
  Collective potentials and nonperturbative cranking collective inertia tensors
are calculated using the multidimensionally-constrained relativistic mean-field
(MDC-RMF) model. Pairing correlations are treated in the BCS approximation
using a separable pairing force of finite range. Pairing fluctuations are
included as a collective variable using a constraint on particle-number
dispersion. Fission paths are determined with the dynamic programming method by
minimizing the action in multidimensional collective spaces.
  The dynamics of spontaneous fission of $^{264}$Fm and $^{250}$Fm are
explored. Fission paths, action integrals and corresponding half-lives computed
in the three-dimensional collective space of shape and pairing coordinates,
using the relativistic functional DD-PC1 and a separable pairing force of
finite range, are compared with results obtained without pairing fluctuations.
Results for $^{264}$Fm are also discussed in relation with those recently
obtained using the HFB model.
  The inclusion of pairing correlations in the space of collective coordinates
favors axially symmetric shapes along the dynamic path of the fissioning
system, amplifies pairing as the path traverses the fission barriers,
significantly reduces the action integral and shortens the corresponding SF
half-life.


title: Self-localization from Images with Small Overlap

abstract:
  With the recent success of visual features from deep convolutional neural
networks (DCNN) in visual robot self-localization, it has become important and
practical to address more general self-localization scenarios. In this paper,
we address the scenario of self-localization from images with small overlap. We
explicitly introduce a localization difficulty index as a decreasing function
of view overlap between query and relevant database images and investigate
performance versus difficulty for challenging cross-view self-localization
tasks. We then reformulate the self-localization as a scalable
bag-of-visual-features (BoVF) scene retrieval and present an efficient solution
called PCA-NBNN, aiming to facilitate fast and yet discriminative
correspondence between partially overlapping images. The proposed approach
adopts recent findings in discriminativity preserving encoding of DCNN features
using principal component analysis (PCA) and cross-domain scene matching using
naive Bayes nearest neighbor distance metric (NBNN). We experimentally
demonstrate that the proposed PCA-NBNN framework frequently achieves comparable
results to previous DCNN features and that the BoVF model is significantly more
efficient. We further address an important alternative scenario of
"self-localization from images with NO overlap" and report the result.


title:
Pseudogap evidenced by Cu EPR in the normal state of Ortho-III
  YBa2Cu3O7-x

abstract:
  The temperature dependences of g factors of underdoped YBa2Cu3O7-x (Tc
approximates 86.5K) indicate that the pseudogap onset temperature T*(
approximates 190 K) coincides with the phase boundary established by
resistivity, Nernst effect, neutron diffraction and ultrasound measurements in
YBCO phase diagram. The obtained empirical relationship between g factors and
pseudogap is appropriate for the entire charactering temperature range of
Ortho-III YBCO. The EPR signals are ascribed to the localized Cu2+(1) sites
based on the quantitative calculations of the g factors by involving the local
structures of the paramagnetic copper (1) sites. The present work provides
another potential spectroscopic probe for the pseudogap in underdoped high Tc
superconductors and the origin of EPR and related mechanisms in YBCO which are
still controversial.


title: Parameterizing Stellar Spectra Using Deep Neural Networks

abstract:
  This work investigates the spectrum parameterization problem using deep
neural networks (DNNs). The proposed scheme consists of the following
procedures: first, the configuration of a DNN is initialized using a series of
autoencoder neural networks; second, the DNN is fine-tuned using a gradient
descent scheme; third, stellar parameters ($T_{eff}$, log$~g$, and [Fe/H]) are
estimated using the obtained DNN. This scheme was evaluated on both real
spectra from SDSS/SEGUE and synthetic spectra calculated from Kurucz's new
opacity distribution function models. Test consistencies between our estimates
and those provided by the spectroscopic parameter pipeline of SDSS show that
the mean absolute errors (MAEs) are 0.0048, 0.1477, and 0.1129 dex for
log$~T_{eff}$, log$~g$, and [Fe/H] (64.85 K for $T_{eff}$), respectively. For
the synthetic spectra, the MAE test accuracies are 0.0011, 0.0182, and 0.0112
dex for log$~T_{eff}$, log$~g$, and [Fe/H] (14.90 K for $T_{eff}$),
respectively.


title: Cooperative single-photon subradiant states

abstract:
  We propose a set of subradiant states which can be prepared and detected in a
one-dimensional optical lattice. We find that the decay rates are highly
dependent on the spatial phases imprinted on the atomic chain, which gives
systematic investigations of the subradiance in the fluorescence experiments.
The time evolution of these states can have long decay time where up to hundred
milliseconds of lifetime is predicted for one hundred atoms. They can also show
decayed Rabi-like oscillations with a beating frequency determined by the
difference of cooperative Lamb shift in the subspace. Experimental requirements
are also discussed for practical implementation of the subradiant states. Our
proposal provides a novel scheme for quantum storage of photons in arrays of
two-level atoms through the preparation and detection of subradiant states,
which offer opportunities for quantum many-body state preparation and quantum
information processing in optical lattices.


title:
Axial U(1) symmetry in the chiral symmetric phase of 2-flavor QCD at
  finite temperature

abstract:
  We discuss the fate of the axial U(1) symmetry in 2-flavor QCD at finite
temperature, where the non-singlet chiral symmetry is restored. We first
summarize the previous theoretical investigation on the relation between the
eigenvalue density of the Dirac operator and the axial U(1) symmetry. We show
that the eigenvalue density near the origin behaves as $\lambda^\gamma$ with
$\gamma > 2$ in the chirally symmetric phase, where $\lambda$ is an eigenvalue.
This implies that the axial U(1) symmetry is partially restored, so that the
low energy symmetry of the theory becomes SU(2)$\otimes$ SU(2)$\otimes$ Z$_4$.
Secondly, we report recent numerical investigations on this issue by lattice
QCD simulations with lattice chiral fermions such as Overlap or improved
domain-wall fermions. Our preliminary results indicate that the eigenvalue
density seems to have a gap at the origin just above $T_c$, the temperature of
the chiral symmetry restoration, which implies the axial U(1) symmetry is
effectively restored at high temperature. We also point out an importance of
the exact lattice chiral symmetry to obtain correct results on this issue.


title: The Likely Fermi detection of the supernova remnant SN 1006

abstract:
  We report the likely detection of gamma-ray emission from the northeast shell
region of the historical supernova remnant (SNR) SN 1006. Having analyzed 7
years of Fermi LAT Pass 8 data for the region of SN 1006, we found a GeV
gamma-ray source detected with 4 sigma significance. Both the position and
spectrum of the source match those of HESS J1504-418 respectively, which is TeV
emission from SN 1006. Considering the source as the GeV gamma-ray counterpart
to SN~1006, the broadband spectral energy distribution is found to be
approximately consistent with the leptonic scenario that has been proposed for
the TeV emission from the SNR. Our result has likely confirmed the previous
study of the SNRs with TeV shell-like morphology: SN 1006 is one of them
sharing very similar peak luminosity and spectral shape.


title:
High-temperature superconductivity in single-unit-cell FeSe films on
  anatase TiO2(001)

abstract:
  We report on the observation of high-temperature ($T_\textrm{c}$)
superconductivity and magnetic vortices in single-unit-cell FeSe films on
anatase TiO$_2$(001) substrate by using scanning tunneling microscopy. A
systematic study and engineering of interfacial properties has clarified the
essential roles of substrate in realizing the high-$T_\textrm{c}$
superconductivity, probably via interface-induced electron-phonon coupling
enhancement and charge transfer. By visualizing and tuning the oxygen vacancies
at the interface, we find their very limited effect on the superconductivity,
which excludes interfacial oxygen vacancies as the primary source for charge
transfer between the substrate and FeSe films. Our findings have placed severe
constraints on any microscopic model for the high-$T_\textrm{c}$
superconductivity in FeSe-related heterostructures.


title: Cloaking the magnons

abstract:
  We propose two approaches to cloak the spin waves (magnons) by investigating
magnetization dynamics. One approach is based on a spatially inhomogeneous
anisotropic magnetic moment tensor. The other mechanism is using a spatially
inhomogeneous anisotropic gyromagnetic factor tensor and an inhomogeneous
external magnetic field. For both approaches, the damping tensor is also
inhomogeneous and anisotropic. The magnetic characteristic functions of the
magnetic materials have been theoretically derived for both mechanisms. A
non-magnetic core, which prevents magnons from entering and consequently
distorts the spin wave propagation, can be cloaked by a structured magnetic
shell to redirect the spin wave around the core using the above design
mechanisms. We discuss the feasibility of the proposed mechanisms in an
ensemble of quantum dot molecules and magnetic semiconductors. The proposed
approaches shed light on transformation magnonics, and can be utilized for
future spin-wave lenses, concentrators, low back-scattering waveguides, and
ultimately quantum computing.


title:
Improvement in medium-long term frequency stability of integrating
  sphere cold atom clock

abstract:
  The medium-long term frequency stability of the integrating sphere cold atom
clock was improved.During the clock operation, Rb atoms were cooled and
manipulated using cooling light diffusely reflected by the inner surface of a
microwave cavity in the clock. This light heated the cavity and caused a
frequency drift from the resonant frequency of the cavity. Power fluctuations
of the cooling light led to atomic density variations in the cavity's central
area, which increased the clock frequency instability through a cavity pulling
effect. We overcame these limitations with appropriate solutions. A frequency
stability of 3.5E-15 was achieved when the integrating time ? increased to 2E4
s.


title: Power counting for nuclear forces in chiral effective field theory

abstract:
  The present note summarizes the discourse on power counting issues of chiral
nuclear forces, with an emphasis on renormalization-group invariance. Given its
introductory nature, I will lean toward narrating a coherent point of view on
the concepts, rather than covering comprehensively the development of chiral
nuclear forces in different approaches.


title:
A review of 20 years of naive tests of significance for high-dimensional
  mean vectors and covariance matrices

abstract:
  In this paper, we will introduce the so called naive tests and give a brief
review on the newly development. Naive testing methods are easy to understand
and performs robust especially when the dimension is large. In this paper, we
mainly focus on reviewing some naive testing methods for the mean vectors and
covariance matrices of high dimensional populations and believe this naive test
idea can be wildly used in many other testing problems.


title: Weighted Uncertainty Relations

abstract:
  Recently, Maccone and Pati have given two stronger uncertainty relations
based on the sum of variances and one of them is nontrivial when the quantum
state is not an eigenstate of the sum of the observables. We derive a family of
weighted uncertainty relations to provide an optimal lower bound for all
situations and remove the restriction on the quantum state. Generalization to
multi-observable cases is also given and an optimal lower bound for the
weighted sum of the variances is obtained in general quantum situation.


title: MV-algebras, infinite dimensional polyhedra, and natural dualities

abstract:
  We connect the dual adjunction between MV-algebras and Tychonoff spaces with
the general theory of natural dualities, and provide a number of applications.
In doing so, we simplify the aforementioned construction by observing that
there is no need of using presentations of MV-algebras in order to obtain the
adjunction. We also provide a description of the dual maps that is
intrinsically geometric, and thus avoids the syntactic notion of definable map.
Finally, we apply these results to better explain the relation between
semisimple tensor products and coproducts of MV-algebras, and we extend beyond
the finitely generated case the characterisations of strongly semisimple and
polyhedral MV-algebras.


title: Automatic learning of gait signatures for people identification

abstract:
  This work targets people identification in video based on the way they walk
(i.e. gait). While classical methods typically derive gait signatures from
sequences of binary silhouettes, in this work we explore the use of
convolutional neural networks (CNN) for learning high-level descriptors from
low-level motion features (i.e. optical flow components). We carry out a
thorough experimental evaluation of the proposed CNN architecture on the
challenging TUM-GAID dataset. The experimental results indicate that using
spatio-temporal cuboids of optical flow as input data for CNN allows to obtain
state-of-the-art results on the gait task with an image resolution eight times
lower than the previously reported results (i.e. 80x60 pixels).


title:
The Minkowski dimension of interior singular points in the
  incompressible Navier--Stokes equations

abstract:
  We study the possible interior singular points of suitable weak solutions to
the three dimensional incompressible Navier--Stokes equations. We present an
improved parabolic upper Minkowski dimension of the possible singular set. It
is bounded by $95/63$. The result also continue to hold for the three
dimensional incompressible magnetohydrodynamic equations without any
difficulty.


title: Deformation of K-theoretic cycles

abstract:
  By using higher K-theory, we study deformation theory of K-theoretic cycles.
As an application, we answer two questions posed by Mark Green and Philip
Griffiths: (1). How to define tangent spaces to cycle class groups in general?
(2). Obstruction issues. The highlight is the appearance of negative K-groups
which detects the obstructions to deforming cycles.


title:
Analysis of terrestrial planet formation by the Grand Tack model: System
  architecture and tack location

abstract:
  The Grand Tack model of terrestrial planet formation has emerged in recent
years as the premier scenario used to account for several observed features of
the inner solar system. It relies on early migration of the giant planets to
gravitationally sculpt and mix the planetesimal disc down to ~1 AU, after which
the terrestrial planets accrete from material left in a narrow circum-solar
annulus. Here we have investigated how the model fares under a range of initial
conditions and migration course-change (`tack') locations. We have run a large
number of N-body simulations with a tack location of 1.5 AU and 2 AU and tested
initial conditions using equal mass planetary embryos and a semi-analytical
approach to oligarchic growth. We make use of a recent model of the protosolar
disc that takes account of viscous heating, include the full effect of type 1
migration, and employ a realistic mass-radius relation for the growing
terrestrial planets. Results show that the canonical tack location of Jupiter
at 1.5 AU is inconsistent with the most massive planet residing at 1 AU at
greater than 95% confidence. This favours a tack farther out at 2 AU for the
disc model and parameters employed. Of the different initial conditions, we
find that the oligarchic case is capable of statistically reproducing the
orbital architecture and mass distribution of the terrestrial planets, while
the equal mass embryo case is not.


title:
Derived noncommutative Zariski immersion and an equivalent reformulation
  of Friedlander-Milnor conjecture

abstract:
  WeintroducethenotionofderivedformalnoncommutativeZariski immersion for
differential graded algebra with examples from topology. We il- lustrate the
importance of such notion by reformulating the Friedlander-Milnor conjecture in
terms of formal noncommutative Zariski immersions. This paper is based on the
language developed by Dwyer, Greenless and Iyendar.


title:
Observation of Quantum Griffiths Singularity and Ferromagnetism at
  Superconducting LaAlO3/SrTiO3(110) Interface

abstract:
  Diverse phenomena emerge at the interface between band insulators LaAlO3 and
SrTiO3, such as superconductivity and ferromagnetism, showing an opportunity
for potential applications as well as bringing fundamental research interests.
Particularly, the two-dimensional electron gas formed at LaAlO3/SrTiO3
interface offers an appealing platform for quantum phase transition from a
superconductor to a weakly localized metal. Here we report the
superconductor-metal transition in superconducting two-dimensional electron gas
formed at LaAlO3/SrTiO3(110) interface driven by a perpendicular magnetic
field. Interestingly, when approaching the quantum critical point, the dynamic
critical exponent is not a constant but a diverging value, which is a direct
evidence of quantum Griffiths singularity raised from quenched disorder at
ultralow temperatures. Furthermore, the hysteretic property of
magnetoresistance was firstly observed at LaAlO3/SrTiO3(110) interfaces, which
suggests potential coexistence of superconductivity and ferromagnetism.


title: Uniform Entanglement Frames

abstract:
  We present several criteria for genuine multipartite entanglement from
universal uncertainty relations based on majorization theory. Under
non-negative Schur-concave functions, the vector-type uncertainty relation
generates a family of infinitely many detectors to check genuine multipartite
entanglement. We also introduce the concept of $k$-separable circles via
geometric distance for probability vectors, which include at most
$(k-1)$-separable states. The entanglement witness is also generalized to a
universal entanglement witness which is able to detect the $k$-separable states
more accurately.


title:
On triple zeta values of even weight and their connections with period
  polynomials

abstract:
  We study triple zeta values of even weight and show various connections with
period polynomials. As a result, an (expected) upper bound of the dimension of
the vector space spanned by certain triple zeta values is obtained.


title: Commissioning of the vacuum system of the KATRIN Main Spectrometer

abstract:
  The KATRIN experiment will probe the neutrino mass by measuring the
beta-electron energy spectrum near the endpoint of tritium beta-decay. An
integral energy analysis will be performed by an electro-static spectrometer
(Main Spectrometer), an ultra-high vacuum vessel with a length of 23.2 m, a
volume of 1240 m^3, and a complex inner electrode system with about 120000
individual parts. The strong magnetic field that guides the beta-electrons is
provided by super-conducting solenoids at both ends of the spectrometer. Its
influence on turbo-molecular pumps and vacuum gauges had to be considered. A
system consisting of 6 turbo-molecular pumps and 3 km of non-evaporable getter
strips has been deployed and was tested during the commissioning of the
spectrometer. In this paper the configuration, the commissioning with bake-out
at 300{\deg}C, and the performance of this system are presented in detail. The
vacuum system has to maintain a pressure in the 10^{-11} mbar range. It is
demonstrated that the performance of the system is already close to these
stringent functional requirements for the KATRIN experiment, which will start
at the end of 2016.


title:
Phase boundary between Na-Si clathrates of structures I and II at high
  pressures and high temperatures

abstract:
  Understanding the covalent clathrate formation is a crucial point for the
design of new superhard materials with intrinsic coupling of superhardness and
metallic conductivity. Silicon clathrates have the archetype structures that
can serve an existant model compounds for superhard clathrate frameworks
"Si-B", "Si-C", "B-C" and "C" with intercalated atoms (e.g. alkali metals or
even halogenes) that can assure the metalic properties. Here we report the in
situ and ex situ studies of high-pressure formation and stability of clathrates
Na8Si46 (structure I) and Na24+xSi136 (structure II). Experiments have been
performed using standard Paris-Edinburgh cells (opposite anvils) up to 6 GPa
and 1500 K. We have established that chemical interactions in Na-Si system and
transition between two structures of clathrates occur at temperatures below
silicon melting. The strong sensitivity of crystallization products to the
sodium concentration have been observed. A tentative diagram of clathrate
transformations has been proposed. At least up to ~6 GPa, Na24+xSi136
(structure II) is stable at lower temperatures as compared to Na8Si46
(structure I).


title: Nonlinear functions and difference sets on group actions

abstract:
  Let $G$, $H$ be finite groups and let $X$ be a finite $G$-set. $G$-perfect
nonlinear functions from $X$ to $H$ have been studied in several papers. They
have more interesting properties than perfect nonlinear functions from $G$
itself to $H$. By introducing the concept of a $(G, H)$-related difference
family of $X$, we obtain a characterization of $G$-perfect nonlinear functions
on $X$. When $G$ is abelian, we characterize a $G$-difference set of $X$ by the
Fourier transform on a normalized $G$-dual set $\widehat X$. We will also
investigate the existence and constructions of $G$-perfect nonlinear functions
and $G$-bent functions. Several known results in [2,6,10,17] are direct
consequences of our results.


title:
The SDSS spectroscopic catalogue of white dwarf-main sequence binaries:
  new identifications from DR9-12

abstract:
  We present an updated version of the spectroscopic catalogue of white
dwarf-main sequence (WDMS) binaries from the Sloan Digital Sky Survey (SDSS).
We identify 939 WDMS binaries within the data releases (DR) 9-12 of SDSS plus
40 objects from DR 1-8 that we missed in our previous works, 646 of which are
new. The total number of spectroscopic SDSS WDMS binaries increases to 3294.
This is by far the largest and most homogeneous sample of compact binaries
currently available. We use a decomposition/fitting routine to derive the
stellar parameters of all systems identified here (white dwarf effective
temperatures, surface gravities and masses, and secondary star spectral types).
The analysis of the corresponding stellar parameter distributions shows that
the SDSS WDMS binary population is seriously affected by selection effects. We
also measure the NaI 8183.27, 8194.81 absorption doublet and Halpha emission
radial velocities (RV) from all SDSS WDMS binary spectra identified in this
work. 98 objects are found to display RV variations, 62 of which are new. The
RV data are sufficient enough to estimate the orbital periods of three close
binaries.


title: On the typical values of the cross-correlation measure

abstract:
  Gyarmati, Mauduit and S\'ark\"ozy introduced the \textit{cross-correlation
measure} $\Phi_k(\mathcal{F})$ to measure the randomness of families of binary
sequences $\mathcal{F} \subset \{-1,1\}^N$.
  In this paper we study the order of magnitude of the cross-correlation
measure $\Phi_k(\mathcal{F})$ for typical families. We prove that, for most
families $\mathcal{F} \subset \{-1,1\}^N$ of size $2\leq
|\mathcal{F}|<2^{N/12}$, $\Phi_k(\mathcal{F})$ is of order $\sqrt{N\log
\binom{N}{k}+k\log |\mathcal{F}|}$ for any given $2\leq k \leq N/(6\log_2
|\mathcal{F}|)$.


abstract:
  Isotope shifts of the 2$p_{3/2}$-2$p_{1/2}$ transition in B-like ions are
evaluated for a wide range of the nuclear charge number: Z=8-92. The
calculations of the relativistic nuclear recoil and nuclear size effects are
performed using a large scale configuration-interaction Dirac-Fock-Sturm
method. The corresponding QED corrections are also taken into account. The
results of the calculations are compared with the theoretical values obtained
with other methods. The accuracy of the isotope shifts of the
2$p_{3/2}$-2$p_{1/2}$ transition in B-like ions is significantly improved.