  We compute the I=2 pi-pi scattering length at pion masses of m_pi ~ 294, 348
and 484 MeV in fully-dynamical lattice QCD using Luscher's finite-volume
method. The calculation is performed with domain-wall valence-quark propagators
on asqtad-improved MILC configurations with staggered sea quarks at a single
lattice spacing, b ~ 0.125 fm. Chiral perturbation theory is used to perform
the extrapolation of the scattering length from lattice quark masses down to
the physical value, and we find m_pi a_2 = -0.0426 +- 0.0006 +- 0.0003 +-
0.0018, in good agreement with experiment. The I=2 pi-pi scattering phase shift
is calculated to be delta = -43 +- 10 +- 5 degrees at |p| ~ 544 MeV for m_pi ~
484 MeV.


  An analytical study on crease formations in a swelling gel layer is
conducted. By exploring the smallness of the layer thickness and using a method
of coupled series-asymptotic expansions, the original nonlinear eigenvalue
problem of partial differential equations is reduced to one of ordinary
differential equations. The latter problem is then solved analytically to
obtain closed-form solutions for all the post-bifurcation branches. With the
available analytical results, a number of deep insights on crease formations
are provided, including the unveiling of three pathways to crease (depending on
the layer thickness), determination of the bifurcation type, establishment of a
lower bound for mode numbers and two scaling laws. Also, a number of
experimental results are captured, which are then nicely interpreted based on
the analytical solutions. In particular, it is shown that some critical
physical quantities are invariant with respect to the thickness at the moment
of crease formation. It appears that the present work offers a comprehensive
understanding on crease formation, a widely-spread phenomenon.


  We describe rational period functions on the Hecke groups and characterize
the ones whose poles satisfy a certain symmetry. This generalizes part of the
characterization of rational period functions on the modular group, which is
one of the Hecke groups.


  This chapter discusses the existing and future use of robotics and
intelligent sensing technology in mental health care. While the use of this
technology is nascent in mental health care, it represents a potentially useful
tool in the practitioner's toolbox. The goal of this chapter is to provide a
brief overview of the field, discuss the recent use of robotics technology in
mental health care practice, explore some of the design issues and ethical
issues of using robots in this space, and finally to explore the potential of
emerging technology.


  We propose a two-stage cycle for an optimized linear-irreversible heat engine
that operates, in a finite time, between a hot (cold) reservoir and a finite
auxiliary system acting as a sink (source) in the first (second) stage. Under
the tight-coupling condition, the engine shows the low-dissipation behavior in
each stage, i.e. the entropy generated depends inversely on the duration of the
process. The phenomenological dissipation constants are determined within the
theory itself in terms of the heat transfer coefficients and the heat capacity
of the auxiliary system. We study the efficiency at maximum power and highlight
a class of efficiencies in the symmetric case that show universality up to
second order in Carnot efficiency, while Curzon-Ahlborn efficiency is obtained
as the lower bound for this class.


  We introduce and study the notion of contact dual pair adopting a line bundle
approach to contact and Jacobi geometry. A contact dual pair is a pair of
Jacobi morphisms defined on the same contact manifold and satisfying a certain
orthogonality condition. Contact groupoids and contact reduction are the main
sources of examples. Among other properties, we prove the Characteristic Leaf
Correspondence Theorem for contact dual pairs which parallels the analogous
result of Weinstein for symplectic dual pairs.


  Motivated by applications to the study of ultracold atomic gases near the
unitarity limit, we investigate the structure of the operator product expansion
(OPE) in non-relativistic conformal field theories (NRCFTs). The main tool used
in our analysis is the representation theory of charged (i.e. non-zero particle
number) operators in the NRCFT, in particular the mapping between operators and
states in a non-relativistic "radial quantization" Hilbert space. Our results
include: a determination of the OPE coefficients of descendant operators in
terms of those of the underlying primary state, a demonstration of convergence
of the (imaginary time) OPE in certain kinematic limits, and an estimate of the
decay rate of the OPE tail inside matrix elements which, as in relativistic
CFTs, depends exponentially on operator dimensions. To illustrate our results
we consider several examples, including a strongly interacting field theory of
bosons tuned to the unitarity limit, as well as a class of holographic models.
Given the similarity with known statements about the OPE in SO(2,d) invariant
field theories, our results suggest the existence of a bootstrap approach to
constraining NRCFTs, with applications to bound state spectra and interactions.
We briefly comment on a possible implementation of this non-relativistic
conformal bootstrap program.


  The paper deals with the asymptotic laws of functional of standard random
variables. These classes of statistics are closely related to estimators of the
extreme value index when the underlying distribution function is in the Weibull
domain of attraction. We use techniques based on martingales theory to describe
the non Gaussian asymptotic distribution of the aforementioned statistics. We
provide results of a simulation study as well as statistical tests that may be
of interest with the proposed results.


  We present MalONT2.0 -- an ontology for malware threat intelligence
\cite{rastogi2020malont}. New classes (attack patterns, infrastructural
resources to enable attacks, malware analysis to incorporate static analysis,
and dynamic analysis of binaries) and relations have been added following a
broadened scope of core competency questions. MalONT2.0 allows researchers to
extensively capture all requisite classes and relations that gather semantic
and syntactic characteristics of an android malware attack. This ontology forms
the basis for the malware threat intelligence knowledge graph, MalKG, which we
exemplify using three different, non-overlapping demonstrations. Malware
features have been extracted from CTI reports on android threat intelligence
shared on the Internet and written in the form of unstructured text. Some of
these sources are blogs, threat intelligence reports, tweets, and news
articles. The smallest unit of information that captures malware features is
written as triples comprising head and tail entities, each connected with a
relation. In the poster and demonstration, we discuss MalONT2.0, MalKG, as well
as the dynamically growing knowledge graph, TINKER.


  We study the existence and multiplicity of periodic weak solutions for a
non-local equation involving an odd subcritical nonlinearity which is
asymptotically linear at infinity. We investigate such problem by applying the
the pseudo-index theory developed by Bartolo, Benci and Fortunato \cite{bbf}
after transforming the problem to a degenerate elliptic problem in a
half-cylinder with a Neumann boundary condition, via a Caffarelli-Silvestre
type extension in periodic setting. The periodic nonlocal case, considered
here, presents, respect to the cases studied in literature, some new additional
difficulties and a careful analysis of the fractional spaces involved is
necessary.


  We completely explore the system of ODE's which is equivalent to the
existence of a parallel $Spin(7)$-structure on the cone over a 7-dimensional
3-Sasakian manifold. The one-dimensional family of solutions of this system is
constructed. The solutions of this family correspond to metrics with holonomy
SU(4) which generalize the Calabi metrics.


  We study many properties of level-dependent Hermite subdivision, focusing on
schemes preserving polynomial and exponential data. We specifically consider
interpolatory schemes, which give rise to level-dependent multiresolution
analyses through a prediction-correction approach. A result on the decay of the
associated multiwavelet coefficients, corresponding to a uniformly continuous
and differentiable function, is derived. It makes use of the approximation of
any such function with a generalized Taylor formula expressed in terms of
polynomials and exponentials.


  We investigate an active pure-exploration setting, that includes best-arm
identification, in the context of linear stochastic bandits. While
asymptotically optimal algorithms exist for standard multi-arm bandits, the
existence of such algorithms for the best-arm identification in linear bandits
has been elusive despite several attempts to address it. First, we provide a
thorough comparison and new insight over different notions of optimality in the
linear case, including G-optimality, transductive optimality from optimal
experimental design and asymptotic optimality. Second, we design the first
asymptotically optimal algorithm for fixed-confidence pure exploration in
linear bandits. As a consequence, our algorithm naturally bypasses the pitfall
caused by a simple but difficult instance, that most prior algorithms had to be
engineered to deal with explicitly. Finally, we avoid the need to fully solve
an optimal design problem by providing an approach that entails an efficient
implementation.


  A novel Markovian network evolution model is introduced and analysed by means
of information theory. It will be proved that the model, called Network
Evolution Chain, is a stationary and ergodic stochastic process. Therefore, the
Asymptotic Equipartition Property can be applied to it. The model's entropy
rate and typical sequences are also explored. Extracting particular information
from the network and methods to simulate network evolution in the continuous
time domain are discussed. Additionally, the Erdos-Renyi Network Evolution
Chain is introduced as a subset of our model with the additional property of
its stationary distribution matching the Erdos-Renyi random graph model. The
stationary distributions of nodes and graphs are calculated for this subset
alongside its entropy rate. The simulation results at the end of the paper back
up the proved theorems and calculated values.


  We prove that the Aizenman-Lieb theorem on ferromagnetism in the Hubbard
model holds true even if the electron-phonon interactions and the
electron-photon interactions are taken into account. Our proof is based on path
integral representations of the partition functions.


  Large geographical regions of our planet remain uncovered by terrestrial
network connections. Sparse and dense constellations of near-Earth orbit
satellites can bridge this gap by providing Internet of Things (IoT)
connectivity on a world-wide scale in a flexible and cost-effective manner.
This paper presents a novel space-terrestrial integrated IoT network
architecture spanning direct- and indirect-to-satellite access from IoT assets
on the surface. Framed on the identified requirements, we analyze NB-IoT and
LoRa/LoRaWAN features to put these technologies forward as appealing candidates
for future satellite IoT deployments. Finally, we list and discuss the key open
research challenges to be addressed in order to achieve a successful
space-terrestrial IoT integration.


  In this paper we introduce a modified covariant quantum algebra based in the
so-called Quesne-Tkachuk algebra. By means of a deformation procedure we arrive
at a class of higher derivative models of gravity. The study of the particle
spectra of these models reveals an equivalence with the physical content of the
well-known renormalizable and super-renormalizable higher derivative gravities.
The particle spectrum exhibits the presence of spurious complex ghosts and, in
light of this problem, we suggest an interesting interpretation in the context
of minimal length theories. Also, a discussion regarding the non-relativistic
potential energy is proposed.


  We demonstrate three-dimensional (3-D) nanoimprint lithography using master
samples initially structured by two-photon lithography. Complex geometries like
micro prisms, micro parabolic concentrators, micro lenses and other micrometer
sized objects with nanoscale features are three-dimensionally fabricated using
two-photon lithography. Stamps made out of polydimethylsiloxane are then cast
using the two-photon lithographically structured samples as master samples.
Hereby, expensive serial nano 3-D printing is transformed into scalable
parallel 3-D nanoimprint lithography. Furthermore, the transition from
two-photon lithography to imprint lithography increases the freedom in
substrate and ink choice significantly. We demonstrate printing on textured
surfaces as well as residue-free printing with silver ink using capillary
action.


  We study the problem of computing the rank of a divisor on a finite graph, a
quantity that arises in the Riemann-Roch theory on a finite graph developed by
Baker and Norine (Advances of Mathematics, 215(2): 766-788, 2007). Our work
consists of two parts: the first part is an algorithm whose running time is
polynomial for a multigraph with a fixed number of vertices. More precisely,
our algorithm has running time O(2^{n \log n})poly(size(G)), where n+1 is the
number of vertices of the graph G. The second part consists of a new proof of
the fact that testing if rank of a divisor is non-negative or not is in the
complexity class NP intersection co-NP and motivated by this proof and its
generalisations, we construct a new graph invariant that we call the critical
automorphism group of the graph.


  We present an alternative method to explore the off-shell component structure
of theories that describe half-integer super-helicities Y=s+1/2 (where sis any
positive integer). We use it to derive the component action, component SUSY
transformation laws, and count the component-level degrees of freedom involved.
This counting will give us clues about N=2 representations. The foundation of
the process relies on the superfield equations of motion, generated by
variation of a superspace action expressed in terms of prepotentials. Using
this approach we reproduce the half-integer super-helicity superspace action
using unconstrained superfields.


  Monitoring Wireless Sensor Networks (WSNs) are composed of sensor nodes that
report temperature, relative humidity, and other environmental parameters. The
time between two successive measurements is a critical parameter to set during
the WSN configuration because it can impact the WSN's lifetime, the wireless
medium contention and the quality of the reported data. As trends in monitored
parameters can significantly vary between scenarios and within time,
identifying a sampling interval suitable for several cases is also challenging.
In this work, we propose a dynamic sampling rate adaptation scheme based on
reinforcement learning, able to tune sensors' sampling interval on-the-fly,
according to environmental conditions and application requirements. The primary
goal is to set the sampling interval to the best value possible so as to avoid
oversampling and save energy, while not missing environmental changes that can
be relevant for the application. In simulations, our mechanism could reduce up
to 73% the total number of transmissions compared to a fixed strategy and,
simultaneously, keep the average quality of information provided by the WSN.
The inherent flexibility of the reinforcement learning algorithm facilitates
its use in several scenarios, so as to exploit the broad scope of the Internet
of Things.


  In this short report, we discuss how coordinate-wise descent algorithms can
be used to solve minimum variance portfolio (MVP) problems in which the
portfolio weights are constrained by $l_{q}$ norms, where $1\leq q \leq 2$. A
portfolio which weights are regularised by such norms is called a sparse
portfolio (Brodie et al.), since these constraints facilitate sparsity (zero
components) of the weight vector. We first consider a case when the portfolio
weights are regularised by a weighted $l_{1}$ and squared $l_{2}$ norm. Then
two benchmark data sets (Fama and French 48 industries and 100 size and BM
ratio portfolios) are used to examine performances of the sparse portfolios.
When the sample size is not relatively large to the number of assets, sparse
portfolios tend to have lower out-of-sample portfolio variances, turnover
rates, active assets, short-sale positions, but higher Sharpe ratios than the
unregularised MVP. We then show some possible extensions; particularly we
derive an efficient algorithm for solving an MVP problem in which assets are
allowed to be chosen grouply.


  We review the parity anomaly and a duality web in 2+1 dimensions. An odd
dimensional non-interacting Dirac fermion theory is not parity invariant at
quantum level. We demonstrate the parity anomaly in a three dimensional
non-interacting Dirac fermion theory and a one dimensional non-interacting
Dirac fermion theory. These theories can generate non-gauge invariant Abelian
Chern-Simons terms at a finite temperature through an effective action. The
parity anomaly also leads us to study the duality web in 2+1 dimensions, in
which the 2+1 dimensional duality web begins from the conjecture of a duality
between a three dimensional Dirac fermion theory and a three dimensional
interacting scalar field theory at the Wilson-Fisher fixed point. We first
review the duality web for the flat background, then we discuss its extension
to the spin$_c$ manifold to avoid inconsistency from the spin structure. This
also leads a global effect. We discuss that the composite fermions approach of
the quantum Hall system also suffers from the same issue of the global
description. Finally, we use perspective of the electric-magnetic duality of
the Abelian gauge theory in 3+1 dimensions to study the 2+1 dimensional duality
web.


  Gang affiliates have joined the masses who use social media to share thoughts
and actions publicly. Interestingly, they use this public medium to express
recent illegal actions, to intimidate others, and to share outrageous images
and statements. Agencies able to unearth these profiles may thus be able to
anticipate, stop, or hasten the investigation of gang-related crimes. This
paper investigates the use of word embeddings to help identify gang members on
Twitter. Building on our previous work, we generate word embeddings that
translate what Twitter users post in their profile descriptions, tweets,
profile images, and linked YouTube content to a real vector format amenable for
machine learning classification. Our experimental results show that pre-trained
word embeddings can boost the accuracy of supervised learning algorithms
trained over gang members social media posts.


  It is proposed that light neutrinos form a triplet in a global SU(3) symmetry
in mass eigenstate basis. Assuming that the SU(3)symmetry is broken in the
direction (-alambda_{3}+frac{b}/{sqrt{3}}lambda_{8}), and after going to the
flavor basis we predict atmospheric mixing angle, sin ^{2}theta_{23}=0.5 and
sin theta_{13}=0 if nu_{mu}-nu_{tau} symmetry is assumed. In the flavor basis
the diagonal part of matrix coefficient of b (dominant part) is found to
transform like (lambda_{3}+frac{1}/{sqrt{3}}lambda_{8}). Imposing the same on
matrix coefficient of $a$ fixes solar mixing angle,sin ^{2}theta
_{12}=frac{1}{3}. Implications for neutrinoless double beta-decay are
discussed.


  We consider a class of continuous generalized antiferromagnetic models
previously studied in \cite{Goldman-Runa} and \cite{Daneri-Runa}, and in the
discrete by \cite{Giuliani-Lebowitz-Lieb-Seiringer}. The functional consists of
an anisotropic perimeter term and a repulsive nonlocal term with a power law
kernel. In certain regimes the two terms enter in competition and symmetry
breaking with formation of periodic striped patterns is expected to occur. In
this paper we extend the results of \cite{Daneri-Runa} to power law kernels
within a range of exponents smaller than $d+2$, being $d$ the dimension of the
underlying space. In particular, we prove that in a suitable regime minimizers
are periodic unions of stripes with a given optimal period. Notice that the
exponent $d+1$ corresponds to an anisotropic version of the model for pattern
formation in thin magnetic films.


  This paper provides a comprehensive discussion of neutralino dark matter
within classes of extended supersymmetric models referred to as the USSM
containing one additional SM singlet Higgs plus an extra $Z'$, together with
their superpartners the singlino and bino'. These extra states of the USSM can
significantly modify the nature and properties of neutralino dark matter
relative to that of the minimal (or even next-to-minimal) supersymmetric
standard models. We derive the Feynman rules for the USSM and calculate the
dark matter relic abundance and direct detection rates for elastic scattering
in the USSM for interesting regions of parameter space where the largest
differences are expected.


  In Scott (2002) and Congdon (2006), a new method is advanced to compute
posterior probabilities of models under consideration. It is based solely on
MCMC outputs restricted to single models, i.e., it is bypassing reversible jump
and other model exploration techniques. While it is indeed possible to
approximate posterior probabilities based solely on MCMC outputs from single
models, as demonstrated by Gelfand and Dey (1994) and Bartolucci et al. (2006),
we show that the proposals of Scott (2002) and Congdon (2006) are biased and
advance several arguments towards this thesis, the primary one being the
confusion between model-based posteriors and joint pseudo-posteriors. From a
practical point of view, the bias in Scott's (2002) approximation appears to be
much more severe than the one in Congdon's (2006), the later being often of the
same magnitude as the posterior probability it approximates, although we also
exhibit an example where the divergence from the true posterior probability is
extreme.


  We consider a multidimensional search problem that is motivated by questions
in contextual decision-making, such as dynamic pricing and personalized
medicine. Nature selects a state from a $d$-dimensional unit ball and then
generates a sequence of $d$-dimensional directions. We are given access to the
directions, but not access to the state. After receiving a direction, we have
to guess the value of the dot product between the state and the direction. Our
goal is to minimize the number of times when our guess is more than $\epsilon$
away from the true answer. We construct a polynomial time algorithm that we
call Projected Volume achieving regret $O(d\log(d/\epsilon))$, which is optimal
up to a $\log d$ factor. The algorithm combines a volume cutting strategy with
a new geometric technique that we call cylindrification.


  Some identities of Chebyshev polynomials are deduced from Waring's formula on
symmetric functions. In particular, these formulae generalize some recent
results of Grabner and Prodinger.


  This paper proposes improving the solve time of a bootstrap AMG designed
previously by the authors. This is achieved by incorporating the information,
set of algebraically smooth vectors, generated by the bootstrap algorithm, in a
single hierarchy by using sufficiently large aggregates, and these aggregates
are compositions of aggregates already built throughout the bootstrap
algorithm. The modified AMG method has good convergence properties and shows
significant reduction in both, memory and solve time. These savings with
respect to the original bootstrap AMG are illustrated on some difficult (for
standard AMG) linear systems arising from discretization of scalar and vector
function elliptic partial differential equations (PDEs) in both 2d and 3d.


  We give a simple classical algorithm which provably achieves the performance
in the title. The algorithm is a simple modification of the Gaussian wave
process.


  Spin is a welcome complication in the study of partonic structure that has
led to new insights, even if theoretically and experimentally not all dust has
settled, in particular on quark flavor dependence and gluon spin. At the same
time it opened new questions on angular momentum and effects of transverse
structure. In this talk the focus is on the role of the transverse momenta of
partons. Like for collinear parton distribution functions (PDFs), we are also
in the case of transverse momentum dependent (TMD) PDFs, talking about forward
matrix elements. TMD PDFs (or in short TMDs) extend collinear PDFs with only
spin-spin correlations to PDFs that include spin-momentum correlations,
including also time-reversal-odd (T-odd) correlations, relevant for the
description of single spin asymmetries. In this way TMDs open up new ways of
studying the spin structure. Their operator structure within QCD, however, is
more complex leading to various ways of breaking of universality.


  Classical mechanics is based upon a mechanical picture of nature that is
fundamentally incorrect. It has been replaced at the basic level by a radically
different theory: quantum mechanics. This change entails an enormous shift in
our basic conception of nature, one that can profoundly alter the scientific
image of man himself. Self-image is the foundation of values, and the
replacement of the mechanistic self-image derived from classical mechanics by
one concordant with quantum mechanics may provide the foundation of a moral
order better suited to our times, a self-image that endows human life with
meaning, responsibility, and a deeper linkage to nature as a whole.


  We show that for local alternatives which are not square integrable the
intermediate (or Kallenberg) efficiency of the Neyman-Pearson test for
uniformity with respect to the classical Kolmogorov-Smirnov test is equal to
infinity. Contrary to this, for local square integrable alternatives the
intermediate efficiency is finite and can be explicitly calculated.


  Subdiffusive transport in tilted washboard potentials is studied within the
fractional Fokker-Planck equation approach, using the associated continuous
time random walk (CTRW) framework. The scaled subvelocity is shown to obey a
universal law, assuming the form of a stationary Levy-stable distribution. The
latter is defined by the index of subdiffusion alpha and the mean subvelocity
only, but interestingly depends neither on the bias strength nor on the
specific form of the potential. These scaled, universal subvelocity
fluctuations emerge due to the weak ergodicity breaking and are vanishing in
the limit of normal diffusion. The results of the analytical heuristic theory
are corroborated by Monte Carlo simulations of the underlying CTRW.


  Based on SU(3) flavor symmetry, many of the quark-graph amplitudes in
two-body nonleptonic decays of charmed mesons can be extracted from experiment,
which enable us to see the relevance and importance of weak annihilation
topologies and to determine the complex parameters $a_1$ and $a_2$ to test the
factorization approach. It is found that $a_2$ in $D\to \bar K^*\pi$ and $D\to
\bar K\rho$ can be different by a factor of 2, indicating that nonfactorizable
corrections to the latter are far more important than the former. The relative
phase between $a_1$ and $a_2$ is about $150^\circ$. Weak annihilation
topologies induced by nearby resonances via final-state rescattering can be
described in a model-independent manner. Although the W-exchange contribution
in $D\to PP$ decays is dominated by resonant final-state interactions (FSIs),
its amplitude in VP decays (V: vector meson, P: pseudoscalar meson) receives
little contributions from FSIs in the quark-antiquark resonance formation. As a
consequence, the sign flip of the W-exchange amplitude in $D\to\bar K^*\pi$ and
$\bar K\rho$ decays, which is needed to explain the relatively real decay
amplitudes of $D\to \bar K\rho$, remains unexplained. SU(3) symmetry is badly
broken in some Cabibbo-suppressed modes and it can be accounted for by the
accumulation of some modest SU(3) violation in individual quark-graph
amplitudes.


  A novel federated learning training framework for heterogeneous environments
is presented, taking into account the diverse network speeds of clients in
realistic settings. This framework integrates asynchronous learning algorithms
and pruning techniques, effectively addressing the inefficiencies of
traditional federated learning algorithms in scenarios involving heterogeneous
devices, as well as tackling the staleness issue and inadequate training of
certain clients in asynchronous algorithms. Through the incremental restoration
of model size during training, the framework expedites model training while
preserving model accuracy. Furthermore, enhancements to the federated learning
aggregation process are introduced, incorporating a buffering mechanism to
enable asynchronous federated learning to operate akin to synchronous learning.
Additionally, optimizations in the process of the server transmitting the
global model to clients reduce communication overhead. Our experiments across
various datasets demonstrate that: (i) significant reductions in training time
and improvements in convergence accuracy are achieved compared to conventional
asynchronous FL and HeteroFL; (ii) the advantages of our approach are more
pronounced in scenarios with heterogeneous clients and non-IID client data.


  The Sturm-Liouville eigenvalue method is employed to analytically investigate
the properties of holographic superconductors in higher dimensions in the
framework of Born-Infeld electrodynamics incorporating the effects of
noncommutative spacetime. In the background of pure Einstein gravity in
noncommutative spacetime, we obtain the relation between the critical
temperature and the charge density. We also obtain the value of the
condensation operator and the critical exponent. Our findings suggest that
higher the value of noncommutative parameter and Born-Infeld parameter make the
condensate harder to form. We also observe that the critical temperature
depends on the mass of the black hole and higher value of black hole mass is
favourable for the formation of the condensate.


  We present a study of the stellar parameters and iron abundances of 18 giant
stars in 6 open clusters. The analysis was based on high-resolution and
high-S/N spectra obtained with the UVES spectrograph (VLT-UT2). The results
complement our previous study where 13 clusters were already analyzed. The
total sample of 18 clusters is part of a program to search for planets around
giant stars. The results show that the 18 clusters cover a metallicity range
between -0.23 and +0.23 dex. Together with the derivation of the stellar
masses, these metallicities will allow the metallicity and mass effects to be
disentangled when analyzing the frequency of planets as a function of these
stellar parameters.


  In a recent paper published in this journal, Almeida and collaborators [Phys.
Rev. D \textbf{79}, 125022 (2009)] analyze the issue of fermion localization of
fermions on a brane constructed from two scalar fields coupled with gravity
(Bloch brane model). In this meritorious research the simplest Yukawa coupling
$\eta\bar{\Psi}\phi\chi\Psi$ was considered. In that work does not analyze the
zero mode in details. In this paper, the localization of fermions on two-field
thick branes is reinvestigated. It is found that the simplest Yukawa coupling
does not support the localization of fermions on the brane. In addition, the
problem of fermion localization for some other Yukawa couplings are analyzed.
It is shown that the zero mode for left-handed and right-handed fermions can be
localized on the brane depending on the values for the coupling constant $\eta$
and the Bloch brane's parameter $a$.


  This is the second in a series of papers on standard monomial theory and
invariant theory of arc spaces. For any algebraically closed field $K$, we
construct a standard monomial basis for the arc space of the Pfaffian variety
over $K$. As an application, we prove the arc space analogue of the first and
second fundamental theorems of invariant theory for the symplectic group.


  In novel Co and CoNi based superalloys, the creep resistance is limited at
high temperatures due to low lattice misfit and solvus temperature. In this
study, we combined the advantages of Co-Ti (high lattice misfit and solvus
temperature) and Co-Al based superalloys (cuboidal precipitates) by using Ti to
substitute Al in alloys of Co-30Ni-(12.5-x)Al-xTi-2.5Mo-2.5W (at.%)
composition. With high Ti content, the alloys obtained extreme high lattice
misfit (bigger than 1.3 %) and solvus temperature (bigger than 1150 degree).
During aging at 900 degree, alloys with high Ti/Al ratio exhibited a lower
gamma prime precipitate coarsening rate resulting from their lower gamma prime
and gamma interfacial energy and higher lattice misfit. In addition, high Ti/Al
ratio brought higher gamma prime volume fraction and excellent mechanical
properties, such as higher yield stress and better creep resistance. However,
at high temperature of 1100 degree, the cubic gamma prime phase was decomposed
into deleterious Eta phase with D024 structure if the Ti/Al ratio exceeded 1.
Based on this, we outreached new alloys design with a high content of Cr and Ta
and appropriate Ti/Al ratio, i.e., Ti/Al ratio is smaller than 1. The newly
designed alloys still have high solvus temperature (bigger than 1200 degree)
and exhibit high lattice misfit (bigger than 1.2 %) as Co-12Ti (at.%)
superalloys but more regular cubic gamma prime precipitates and significantly
better creep resistance than superalloys Co-9Al-9W and Co-9Al-9W-2Ti at 850 and
950 degree. Nevertheless, compared with creep resistance of Ni based
superalloys, our newly designed alloys still need to be further improved,
especially in the 1000 and 1050 degree range.


  First data on inclusive particle production measured in proton-proton
collisions at the Large Hadron Collider (LHC) are compared to predictions of
various hadron-interaction Monte Carlos (QGSJET, EPOS and SIBYLL) used commonly
in high-energy cosmic-ray physics. While reasonable overall agreement is found
for some of the models, none of them reproduces consistently the sqrt(s)
evolution of all the measured observables. We discuss the implications of the
new LHC data for the modeling of the non-perturbative and semihard parton
dynamics in hadron-hadron and cosmic-rays interactions at the highest energies
studied today.


  It is shown that a disformally coupled theory in which the gravitational
sector has the Einstein-Hilbert form is equivalent to a quartic DBI Galileon
Lagrangian, possessing non-linear higher derivative interactions, and hence
allowing for the Vainshtein effect. This Einstein Frame description
considerably simplifies the dynamical equations and highlights the role of the
different terms. The study of highly dense, non-relativistic environments
within this description unravels the existence of a disformal screening
mechanism, while the study of static vacuum configurations reveals the
existence of a Vainshtein radius, at which the asymptotic solution breaks down.
Disformal couplings to matter also allow the construction of Dark Energy
models, which behave differently than conformally coupled ones and introduce
new effects on the growth of Large Scale Structure over cosmological scales, on
which the scalar force is not screened. We consider a simple Disformally
Coupled Dark Matter model in detail, in which standard model particles follow
geodesics of the gravitational metric and only Dark Matter is affected by the
disformal scalar field. This particular model is not compatible with
observations in the linearly perturbed regime. Nonetheless, disformally coupled
theories offer enough freedom to construct realistic cosmological scenarios,
which can be distinguished from the standard model through characteristic
signatures.


  We present a consistent theoretical approach for the study of nonequilibrium
effects in chiral fluid dynamics within the framework of the linear sigma model
with constituent quarks. Treating the quarks as an equilibrated heat bath we
use the influence functional formalism to obtain a Langevin equation for the
sigma field. This allows us to calculate the explicit form of the damping
coefficient and the noise correlators. For a selfconsistent derivation of both
the dynamics of the sigma field and the quark fluid we have to employ the 2PI
(two-particle irreducible) effective action formalism. The energy dissipation
from the field to the fluid is treated in the exact formalism of the 2PI
effective action where a conserved energy-momentum tensor can be constructed.
We derive its form and comment on approximations generating additional terms in
the energy-momentum balance of the entire system.


  We have generalized the BOUND and MOLSCAT packages to allow calculations in
basis sets where the monomer Hamiltonians are off-diagonal and used the new
capability to carry out bound-state and scattering calculations on 3He-NH and
4He-NH as a function of magnetic field. Following the bound-state energies to
the point where they cross thresholds gives very precise predictions of the
magnetic fields at which zero-energy Feshbach resonances occur. We have used
this to locate and characterize two very narrow Feshbach resonances in 3He-NH.
Such resonances can be used to tune elastic and inelastic collision cross
sections, and sweeping the magnetic field across them will allow a form of
quantum control in which separated atoms and molecules are associated to form
complexes. For the first resonance, where only elastic scattering is possible,
the scattering length shows a pole as a function of magnetic field and there is
a very large peak in the elastic cross section. For the second resonance,
however, inelastic scattering is also possible. In this case the pole in the
scattering length is dramatically suppressed and the cross sections show
relatively small peaks. The peak suppression is expected to be even larger in
systems with stronger inelasticity. The results suggest that calculations on
ultracold molecular inelastic collisions may be much less sensitive to details
of the potential energy surface than has been believed.


  Virtual Observatories (VOs) are online hubs of scientific knowledge. They
encompass a collection of platforms dedicated to the storage and dissemination
of astronomical data, from simple data archives to e-research platforms
offering advanced tools for data exploration and analysis. Whilst the more
mature platforms within VOs primarily serve the observational community, there
are also services fulfilling a similar role for theoretical data. Scientific
visualization can be an effective tool for analysis and exploration of datasets
made accessible through web platforms for theoretical data, which often contain
spatial dimensions and properties inherently suitable for visualization via
e.g. mock imaging in 2d or volume rendering in 3d. We analyze the current state
of 3d visualization for big theoretical astronomical datasets through
scientific web portals and virtual observatory services. We discuss some of the
challenges for interactive 3d visualization and how it can augment the workflow
of users in a virtual observatory context. Finally we showcase a lightweight
client-server visualization tool for particle-based datasets allowing
quantitative visualization via data filtering, highlighting two example use
cases within the Theoretical Astrophysical Observatory.


  We study thermal effects on pinning and creep in type-II superconductors
where vortices interact with a low density $n_p$ of strong point-like defects
with pinning energy $e_p$ and extension $\xi$, the vortex core size. Defects
are classified as strong if the interaction between a single pin and an
individual vortex leads to the appearance of bistable solutions describing
pinned and free vortex configurations. Extending the strong pinning theory to
account for thermal fluctuations, we provide a quantitative analysis of vortex
depinning and creep. We determine the thermally activated transitions between
bistable states using Kramer's rate theory and find the non-equilibrium
steady-state occupation of vortex states. The latter depends on the temperature
$T$ and vortex velocity $v$ and determines the current--voltage (or
force--velocity) characteristic of the superconductor at finite temperatures.
We find that the $T=0$ linear excess-current characteristic $v \propto (j-j_c)
\, \Theta(j-j_c)$ with its sharp transition at the critical current density
$j_c$, keeps its overall shape but is modified in three ways due to thermal
creep: a downward renormalization of $j_c$ to the thermal depinning current
density $j_\mathrm{dp}(T) < j_c$, a smooth rounding of the characteristic
around $j_\mathrm{dp}(T)$, and the appearance of thermally assisted flux flow
(TAFF) ${v \propto j \exp(-U_0/k_{\rm \scriptscriptstyle B} T)}$ at small drive
$j \ll j_c$, with the activation barrier $U_0$ defined through the energy
landscape at the intersection of free and pinned branches. This characteristic
emphasizes the persistence of pinning of creep at current densities beyond
critical.


  A central result of Sturm-Liouville theory (also called the Sturm-Hurwitz
Theorem) states that if $\phi_k$ is a sequence of eigenfunctions of a second
order differential operator on the interval $I \subset \mathbb{R}$, then any
linear combination satisfies a uniform bound on the roots $$ \# \left\{x \in
I:\sum_{k \geq n}{ a_k \phi_k(x)} = 0 \right\} \geq n-1.$$ We provide a sharp
(up to logarithmic factors) generalization to two dimensions: let $(M,g)$ be a
compact two-dimensional manifold (with or without boundary), let $(\phi_k)$
denote the sequence of eigenfunctions of a uniformly elliptic operator
$-\mbox{div}(a(\cdot) \nabla)$ (with Dirichlet or Neumann boundary conditions).
Then, for any linear combination of eigenfunctions above a certain index $n$,
$$ f = \sum_{k \geq n}{a_k \phi_k} ~ \mbox{we have} \quad \mathcal{H}^1 \left\{
x: f(x) = 0\right\} \gtrsim_{} \frac{\sqrt{n}}{\sqrt{\log{n}}} \log \left(n
\frac{\|f\|_{L^2(M)}}{\|f\|_{L^1(M)}} \right)^{-1/2} \frac{\|f\|_{L^1(M)}}{\| f
\|_{L^{\infty}(M)}} .$$ Examples on $M=\mathbb{T}^2$ and $M=\mathbb{S}^2$ shows
that this is optimal up to the logarithmic factors. The proof is using optimal
transport and a new inequality for the Wasserstein metric $W_p$: if $f(x)dx$
and $g(x)dx$ are two absolutely continuous measures on a two-dimensional domain
$M$ with continuous densities and the same total mass, then, for all $1 \leq p
<\infty$, $$ W_p(f(x)dx, g(x) dx) \cdot \mathcal{H}^1 \left\{x \in M: f(x) =
g(x) \right\} \gtrsim_{M,p}
\frac{\|f-g\|_{L^1(M)}^{1+1/p}}{\|f-g\|_{L^{\infty}(M)}}.$$


  We show that the random matrix theory with non-integer "symmetry parameter"
beta describes the statistics of transport parameters of strongly disordered
two dimensional systems.


  Can the popular shortest remaining processing time (SRPT) algorithm achieve a
constant competitive ratio on multiple servers when server speeds are
adjustable (speed scaling) with respect to the flow time plus energy
consumption metric? This question has remained open for a while, where a
negative result in the absence of speed scaling is well known. The main result
of this paper is to show that multi-server SRPT can be constant competitive,
with a competitive ratio that only depends on the power-usage function of the
servers, but not on the number of jobs/servers or the job sizes (unlike when
speed scaling is not allowed). When all job sizes are unity, we show that
round-robin routing is optimal and can achieve the same competitive ratio as
the best known algorithm for the single server problem. Finally, we show that a
class of greedy dispatch policies, including policies that route to the least
loaded or the shortest queue, do not admit a constant competitive ratio. When
job arrivals are stochastic, with Poisson arrivals and i.i.d. job sizes, we
show that random routing and a simple gated-static speed scaling algorithm
achieves a constant competitive ratio.


  Pairs of pseudoscalar neutral mesons from decays of vector resonances are
studied as bipartite systems in the framework of density operator.
Time-dependent quantum entanglement is quantified in terms of the entanglement
entropy and these dependences are demonstrated on data on correlated pairs of K
and B mesons, as measured by the KLOE and Belle experiments . Another
interesting characteristics of such bipartite systems are moments of the CP
distributions. These moments are directly measurable and they appear to be very
sensitive to the initial degree of entanglement of a pair.


  We study a novel optical setup which is able to select a specific Fock
component from a generic input state. The device allows to synthesize number
states and superpositions of few number states, and to measure the photon
distribution and the density matrix of a generic input signal.


  We report the results of radio flux-monitoring and high resolution
observations at 3.6 cm with the VLA, of the central condensation in G10.0-0.3,
the radio nebula surrounding the soft gamma ray repeater (SGR) 1806-20. The
quiescent X-ray source AX1805.7-2025 is coincident with the radio core
suggesting that G10.0-0.3 is a plerionic supernova remnant. The monitoring
experiment was performed in 10 epochs spread over five months, starting just
before the latest reactivation of SGR 1806-20 in gamma-rays. There is no
apparent increase in the radio flux density from the central region of
G10.0-0.3 on timescales of days to months following the gamma-ray bursts. At a
resolution of 1 arcsec the peak region of G10.0-0.3 is seen to consist of a
compact source with diffuse, one-sided emission, reminiscent of core-jet
geometry seen in AGNs and some accreting Galactic binaries. By analogy with
these latter sources, we argue that the SGR 1806-20 is coincident with the core
component. If so, this is the first arcsecond localization of a high energy
transient. The lack of radio variability and the low brightness temperature of
the central component distinguish SGR 1806-20 from other accreting binaries.
The structure of the high resolution radio image also does not particularly
resemble that seen in the vicinity of young pulsars. Thus there is no
compelling observational evidence for either of the two models discussed for
SGRs, the pulsar model or the accreting binary model.


  By introducing a density-dependent contact term, M3Y-type interactions
applicable to the Hartree-Fock calculations are developed. In order to view
basic characters of the interactions, we carry out calculations on the uniform
nuclear matter as well as on several doubly magic nuclei. It is shown that a
parameter-set called M3Y-P2 describes various properties similarly well to the
Skyrme SLy5 and/or the Gogny D1S interactions. A remarkable difference from the
SLy5 and the D1S interactions is found in the spin-isospin properties in the
nuclear matter, to which the one-pion-exchange potential gives a significant
contribution. Affecting the single-particle energies, this difference may play
a certain role in the new magic numbers in unstable nuclei.


  This paper presents a physical interface for collaborative mobile
manipulators in industrial manufacturing and logistics applications. The
proposed work builds on our earlier MOCA-MAN interface, through which an
operator could be physically coupled to a mobile manipulator to be assisted in
performing daily activities. The previous interface was based on a magnetic
clamp attached to one arm of the user for the coupling stage, and a bracelet
based on EMG sensors on the other arm for human-robot communication via
gestures. The new interface instead presents the following additions: i) An
industrial-like design that allows the worker to couple/decouple easily and to
operate mobile manipulators locally; ii) A simplistic communication channel via
a simple buttons board that allows controlling the robot with one hand only;
iii) The interface offers enhanced loco-manipulation capabilities that do not
compromise the worker mobility. In addition, an experimental evaluation with
six human subjects is carried out to analyze the enhanced locomotion and
flexibility of the proposed interface in terms of mobility constraint,
usability, and physical load reduction.


  We propose a framework for building graphical causal model that is based on
the concept of causal mechanisms. Causal models are intuitive for human users
and, more importantly, support the prediction of the effect of manipulation. We
describe an implementation of the proposed framework as an interactive model
construction module, ImaGeNIe, in SMILE (Structural Modeling, Inference, and
Learning Engine) and in GeNIe (SMILE's Windows user interface).


  We consider the problem of enumerating permutations with exactly r
occurrences of the pattern 1324 and derive functional equations for this
general case as well as for the pattern avoidance (r=0) case. The functional
equations lead to a new algorithm for enumerating length n permutations that
avoid 1324. This approach is used to enumerate the 1324-avoiders up to n=31. We
also extend those functional equations to account for the number of inversions
and derive analogous algorithms.


  An injection of energy into the early Universe on a given characteristic
length scale will result in turbulent motions of the primordial plasma. We
calculate the stochastic background of gravitational radiation arising from a
period of cosmological turbulence, using a simple model of isotropic
Kolmogoroff turbulence produced in a cosmological phase transition. We also
derive the gravitational radiation generated by magnetic fields arising from a
dynamo operating during the period of turbulence. The resulting gravitational
radiation background has a maximum amplitude comparable to the radiation
background from the collision of bubbles in a first-order phase transition, but
at a lower frequency, while the radiation from the induced magnetic fields is
always subdominant to that from the turbulence itself. We briefly discuss the
detectability of such a signal.


  Factorial designs are widely used due to their ability to accommodate
multiple factors simultaneously. The factor-based regression with main effects
and some interactions is the dominant strategy for downstream data analysis,
delivering point estimators and standard errors via one single regression.
Justification of these convenient estimators from the design-based perspective
requires quantifying their sampling properties under the assignment mechanism
conditioning on the potential outcomes. To this end, we derive the sampling
properties of the factor-based regression estimators from both saturated and
unsaturated models, and demonstrate the appropriateness of the robust standard
errors for the Wald-type inference. We then quantify the bias-variance
trade-off between the saturated and unsaturated models from the design-based
perspective, and establish a novel design-based Gauss--Markov theorem that
ensures the latter's gain in efficiency when the nuisance effects omitted
indeed do not exist. As a byproduct of the process, we unify the definitions of
factorial effects in various literatures and propose a location-shift strategy
for their direct estimation from factor-based regressions. Our theory and
simulation suggest using factor-based inference for general factorial effects,
preferably with parsimonious specifications in accordance with the prior
knowledge of zero nuisance effects.


  The main achievement of this paper is a geometric characterisation of certain
subvarieties of the Cartan variety (the standard projective variety associated
to the split exceptional group of Lie type E_6) over an arbitrary field K. The
characterised varieties arise as Veronese representations of certain ring
projective planes over quadratic subalgebras of the split octonions over K
(among which the sextonions, a 6-dimensional non-associative algebra). We
describe how these varieties are linked to the Freudenthal-Tits magic square,
and discuss how they would even fit in, when also allowing the sextonions and
other "degenerate composition algebras" as the algebras used to construct the
square.


  Rotating black holes in the brany universe of the Randall-Sundrum type are
described by the Kerr geometry with a tidal charge b representing the
interaction of the brany black hole and the bulk spacetime. For b<0 rotating
black holes with dimensionless spin a>1 are allowed. We investigate the role of
the tidal charge b in the orbital resonance model of QPOs in black hole
systems. The orbital Keplerian, the radial and vertical epicyclic frequencies
of the equatorial, quasicircular geodetical motion are given and their radial
profiles are discussed. The resonant conditions are given in three
astrophysically relevant situations: for direct (parametric) resonances, for
the relativistic precession model, and for some trapped oscillations of the
warped discs, with resonant combinational frequencies. It is shown, how b could
influence matching of the observational data indicating the 3:2 frequency ratio
observed in GRS 1915+105 microquasar with prediction of the orbital resonance
model; limits on allowed range of the black hole parameters a and b are
established. The "magic" dimensionless black hole spin enabling presence of
strong resonant phenomena at the radius where \nu_K:\nu_{\theta}:\nu_r=3:2:1 is
determined in dependence on b. Such strong resonances could be relevant even in
sources with highly scattered resonant frequencies, as those expected in Sgr
A*. The specific values of a and b are given also for existence of specific
radius where \nu_K:\nu_{\theta}:\nu_r=s:t:u with 5>=s>t>u being small natural
numbers. It is shown that for some ratios such situation is impossible in the
field of black holes. We can conclude that analysing the microquasars
high-frequency QPOs in the framework of orbital resonance models, we can put
relevant limits on the tidal charge of brany Kerr black holes.


  We consider the storage and transmission of a Gaussian distributed set of
coherent states of continuous variable systems. We prove a limit on the average
fidelity achievable when the states are transmitted or stored by a classical
channel, i.e., a measure and repreparation scheme which sends or stores
classical information only. The obtained bound is tight and serves as a
benchmark which has to be surpassed by quantum channels in order to outperform
any classical strategy. The success in experimental demonstrations of quantum
memories as well as quantum teleportation has to be judged on this footing.


  In many studies, dimension reduction methods are used to profile participant
characteristics. For example, nutrition epidemiologists often use latent class
models to characterize dietary patterns. One challenge with such approaches is
understanding subtle variations in patterns across subpopulations. Robust
Profile Clustering (RPC) provides a dual flexible clustering model, where
participants may cluster at two levels: (1) globally, where participants are
clustered according to behaviors shared across an overall population, and (2)
locally, where individual behaviors can deviate and cluster in subpopulations.
We link clusters to a health outcome using a joint model. This model is used to
derive dietary patterns in the United States and evaluate case proportion of
orofacial clefts. Using dietary consumption data from the 1997-2009 National
Birth Defects Prevention Study, a population-based case-control study, we
determine how maternal dietary profiles are associated with an orofacial cleft
among offspring. Results indicated that mothers who consumed a high proportion
of fruits and vegetables compared to meats, such as chicken and beef, had lower
odds delivering a child with an orofacial cleft defect.


  Round fold maps are smooth maps on closed manifolds which are locally
represented as the product maps of Morse functions and identity maps on open
disks and whose singularity is realized as concentrically embedded spheres. The
author previously introduced such maps. Our paper presents round fold maps on
some $7$-dimensional simply-connected manifolds whose cohomology rings are
isomorphic to that of the product of the $2$-dimensional complex projective
space and a $3$-dimensional sphere. Such manifolds have been studied precisely
by Wang and round fold maps on spin manifolds in these manifolds have been
previously studied by the author. These manifolds form explicit classes of
higehr dimensional closed and simply-connected manifolds, which are central
objects in classical algeberic topology and differential topology.
Understanding these manifolds in geometric and constructive ways is still
attractive, which we think as pioneers.
  Fold maps are defined as smooth maps which are locally represented as the
product maps of Morse functions and identity maps on open disks. They are
fundamental and strong tools in generalizations of theory of Morse functions
and applications to geometry of manifolds. Explicit construction of fold maps
are difficult even on elementary or well-known manifolds whereas we can know
the (non-)existence from Eliashberg's celebrating theory in the 1970s and
related one in considerable cases.


  With the time-varying renewable energy generation and power demand,
microgrids (MGs) exchange energy in smart grids to reduce their dependence on
power plants. In this paper, we formulate an MG energy trading game, in which
each MG trades energy according to the predicted renewable energy generation
and local energy demand, the current battery level, and the energy trading
history. The Nash quilibrium (NE) of the game is provided, revealing the
conditions under which the local energy generation satisfies the energy demand
of the MG and providing the performance bound of the energy trading scheme. We
propose a reinforcement learning based MG energy trading scheme that applies
the deep Q-network (DQN) to improve the utility of the MG for the case with a
large number of the connected MGs. Simulations are performed for the MGs with
wind generation that are aware of the electricity prices and the historic
energy trading, showing that this scheme significantly reduces the average
power plant schedules and improves the utility of the MG compared with the
benchmark strategy.


  Students of visualization come to formal education with an abundance of
personal experience. However, one's exposure to graphics through media and
education may not be sufficiently diverse to appreciate the nuance and
complexity required to design and evaluate effective representations. While
many introductory courses in visualization address best practices for visual
encoding of data based on perceptual characteristics, as cognitive scientists,
we place equal value on representational decisions based on communicative
context: how the representation is intended to be used. In this pedagogical
activity, we aim to surface learners' preconceived notions about what makes a
visualization effective. Here we describe the structure and context of an
introductory-level visualization activity, how it might be conducted in
individual or group settings, our experience with the common misconceptions the
activity can reveal, and conclude with recommendations on how they might be
addressed.


  We investigate an $L_{q}(L_{p})$-regularity ($1<p,q<\infty$) theory for
space-time nonlocal equations of the type $\partial^{\alpha}_{t}u =
\mathcal{L}u +f$. Here, $\partial^{\alpha}_{t}$ is the Caputo fractional
derivative of order $\alpha\in(0,1)$ and $\mathcal{L}$ is an
integro-differential operator $$ \mathcal{L}u(x) = \int_{\mathbb{R}^{d}} \left(
u(x)-u(x+y) -\nabla u (x) \cdot y \mathbf{1}_{|y|\leq 1} \right) j_{d}(|y|)dy
$$ which is the infinitesimal generator of an isotropic unimodal L\'evy
process. We assume that the jump kernel $j_{d}(r)$ is comparable to $r^{-d}
\ell(r^{-1})$, where $\ell$ is a continuous function satisfying $$
C_{1}\left(\frac{R}{r}\right)^{\delta_{1}} \leq \frac{\ell(R)}{\ell(r)} \leq
C_{2} \left( \frac{R}{r} \right)^{\delta_{2}} \quad \text{for}\;\; \,1\leq
r\leq R<\infty, $$ where $0\leq \delta_{1}\leq \delta_{2}<2$. Hence, $\ell$ can
be slowly varying at infinity. Our result covers $\mathcal{L}$ whose Fourier
multiplier $\Psi(\xi)$ satisfies $\Psi(\xi)\asymp -\log{(1+|\xi|^{\beta})}$ for
$\beta \in (0,2]$ and $\Psi(\xi) \asymp-(\log(1+|\xi|^{\beta/4}))^{2}$ for
$\beta\in(0,2)$ by taking $\ell(r) \asymp 1$ and $\ell(r) \asymp
\log{(1+r^{\beta})}$ for $r\geq1$ respectively. In this article, we use the
Calder\'on-Zygmund approach and function space theory for operators having
slowly varying symbols.


  Many dense granular systems are non-monodisperse, consisting of particles of
different sizes, and will segregate based on size during flow. This phenomenon
is an important aspect of many industrial and geophysical processes,
necessitating predictive continuum models. This paper systematically studies a
key aspect of the three-dimensional nature of segregation and diffusion in
flowing, dense, bidisperse granular mixtures -- namely, segregation and
diffusion acting along the direction perpendicular to the plane of shearing,
which we refer to as the anti-plane modes of segregation and diffusion. To this
end, we consider discrete-element method (DEM) simulations of flows of dense,
bidisperse mixtures of frictional spheres in an idealized configuration that
isolates anti-plane segregation and diffusion. We find that
previously-developed constitutive equations, calibrated to DEM simulation
results from flows in which both the segregation and diffusion processes occur
within the plane of shearing, do not capture aspects of the anti-plane
segregation dynamics. Accordingly, we utilize DEM simulation results to inform
and calibrate constitutive equations for the segregation and diffusion fluxes
in their anti-plane modes. Predictions of the resulting continuum model for the
anti-plane segregation dynamics are tested against additional DEM simulation
results across different cases, while parameters such as the shear strain rate
and mixture composition are varied, and we find that the calibrated model
predictions match well with the DEM simulation results. Finally, we suggest a
strategy for generalizing the constitutive forms for the segregation and
diffusion fluxes to obtain three-dimensional constitutive equations that
account for both the in-plane and anti-plane modes of the segregation and
diffusion processes.


  A double magma is a nonempty set with two binary operations satisfying the
interchange law. We call a double magma proper if the two operations are
distinct and commutative if the operations are commutative. A double semigroup
is a double magma for which both operations are associative. Given a group G we
define a double magma (G,*,#) with the commutator operations x * y = [x,y] (=
x^-1y^-1xy) and x # y = [y,x]. We show that (G,*,#) is a double magma if and
only if G satisfies the commutator laws [x,y;x,z]=1 and [w,x;y,z]^2 = 1. Note
that the first law defines the variety of 3-metabelian groups. If both these
laws hold in G, (G,*,#) is proper if and only if G contains a commutator whose
square is nontrivial. B.H. Neumann has given an example of such a group which
is not metabelian; thus the associated double magma is proper and produces an
example with some complexity. The double magma (G,*,#) is a double semigroup if
and only if G is nilpotent of class 2. In this case, (G,*,#) is a proper double
semigroup if and only if G contains a commutator whose square is nontrivial. We
construct a specific example letting G be the dihedral group of order 16. In
addition we comment on a similar construction for rings using Lie commutators.


  By means of the concept of factorial moment the charge transfer rates in DNA
segments with fractal structures are investigated. An analytical form for the
electron transfer rate is obtained.


  Dialgebras are generalizations of associative algebras which give rise to
Leibniz algebras instead of Lie algebras. In this paper we study super
dialgebras and Leibniz superalgebras, which are $\z_2$-graded dialgebras and
Leibniz algebras. We also study universal central extesions of Leibniz
superalgebras and obtain some results as in the case of Lie superalgebras. We
determine universal central extensions of basic classical Lie superalgebras in
the category of Leibniz superalgebras. They play a key role in studying Leibniz
superalgebras graded by finite root systems.


  Domain adaptation for semantic image segmentation is very necessary since
manually labeling large datasets with pixel-level labels is expensive and time
consuming. Existing domain adaptation techniques either work on limited
datasets, or yield not so good performance compared with supervised learning.
In this paper, we propose a novel bidirectional learning framework for domain
adaptation of segmentation. Using the bidirectional learning, the image
translation model and the segmentation adaptation model can be learned
alternatively and promote to each other. Furthermore, we propose a
self-supervised learning algorithm to learn a better segmentation adaptation
model and in return improve the image translation model. Experiments show that
our method is superior to the state-of-the-art methods in domain adaptation of
segmentation with a big margin. The source code is available at
https://github.com/liyunsheng13/BDL.


  The CL-SciSumm Shared Task is the first medium-scale shared task on
scientific document summarization in the computational linguistics~(CL) domain.
In 2019, it comprised three tasks: (1A) identifying relationships between
citing documents and the referred document, (1B) classifying the discourse
facets, and (2) generating the abstractive summary. The dataset comprised 40
annotated sets of citing and reference papers of the CL-SciSumm 2018 corpus and
1000 more from the SciSummNet dataset. All papers are from the open access
research papers in the CL domain. This overview describes the participation and
the official results of the CL-SciSumm 2019 Shared Task, organized as a part of
the 42nd Annual Conference of the Special Interest Group in Information
Retrieval (SIGIR), held in Paris, France in July 2019. We compare the
participating systems in terms of two evaluation metrics and discuss the use of
ROUGE as an evaluation metric. The annotated dataset used for this shared task
and the scripts used for evaluation can be accessed and used by the community
at: https://github.com/WING-NUS/scisumm-corpus.


  Heider's Balance Theory in signed networks, which consists of friendship or
enmity relationships, is a model that relates the type of relationship between
two people to the third person. In this model, there is an assumption of the
independence of triadic relations, which means that the balance or imbalance of
one triangle does not affect another and the energy only depends on the number
of each type of triangle. There is evidence that in real network data, in
addition to third-order interactions (Heider Balance), higher-order
interactions also play a role. One step beyond the Heider Balance, the effect
of Quartic Balance has been studied by removing the assumption of triangular
independence. Application of quartic balance results in the influence of the
balanced or imbalanced state of neighboring triangles on each specific one.
Here, a question arises that how the Heider Balance is affected by the
existence of Quartic Balance (fourth-order). The phase diagram obtained from
the mean-field method shows there is a threshold for higher-order interaction
strength, below which a third-order interaction dominates and there are no
imbalance triangles in the network, and above this threshold, squares
effectively determine the balance state in which the imbalance triangles can
survive. The solution of the mean-field indicates that we have a first-order
phase transition in terms of random behavior of agents (temperature) which is
in accordance with the Monte Carlo simulation results.


  In this commentary article to 'The Puzzle of Ideography' by Morin, we put
forth a new cognitive account of the puzzle of ideography, that complements the
standardization account of Morin. Efficient standardization of spoken language
is phenomenologically attributed to a modality effect coupled with chunking of
cognitive representations, further aided by multi-sensory integration and the
serialized nature of attention. These cognitive mechanisms are crucial for
explaining why languages dominate graphic codes for general-purpose human
communication.


  This paper investigates a fully unsupervised statistical method for edge
preserving image restoration and compression using a spatial decomposition
scheme. Smoothed maximum likelihood is used for local estimation of edge pixels
from mixture parametric models of local templates. For the complementary smooth
part the traditional L2-variational problem is solved in the Fourier domain
with Thin Plate Spline (TPS) regularization. It is well known that naive
Fourier compression of the whole image fails to restore a piece-wise smooth
noisy image satisfactorily due to Gibbs phenomenon. Images are interpreted as
relative frequency histograms of samples from bi-variate densities where the
sample sizes might be unknown. The set of discontinuities is assumed to be
completely unsupervised Lebesgue-null, compact subset of the plane in the
continuous formulation of the problem. Proposed spatial decomposition uses a
widely used topological concept, partition of unity. The decision on edge pixel
neighborhoods are made based on the multiple testing procedure of Holms.
Statistical summary of the final output is decomposed into two layers of
information extraction, one for the subset of edge pixels and the other for the
smooth region. Robustness is also demonstrated by applying the technique on
noisy degradation of clean images.


  Motivated by some variational problems from a nonlocal model of mechanics,
this work presents a set of sufficient conditions that guarantee a compact
inclusion in the function space of $L^{p}$ vector fields defined on a domain
$\Omega$ that is either a bounded domain in $\mathbb{R}^{d}$ or
$\mathbb{R}^{d}$ itself. The criteria are nonlocal and are given with respect
to nonlocal interaction kernels that may not be necessarily radially symmetric.
Moreover, these criteria for vector fields are also different from those given
for scalar fields in that the conditions are based on nonlocal interactions
involving only parts of the components of the vector fields. The $L^{p}$
compactness criteria are utilized in demonstrating the convergence of
minimizers of parametrized nonlocal energy functionals.


  In the field of Computer Science and Information Technology Internet of
Things (IoT) is one of the emerging technologies. In IoT environment several
devices are interconnected and transmit data among them. There may be some
security vulnerability arise within the IoT environment. Till date, IoT has not
been widely accepted due to its security flaws. Hence to keep the IoT
environment most robust, we propose a stable security framework of IoT with
Elliptic Curve Cryptography (ECC) using DNA Encoding. The ECC is most
lightweight cryptography technique among other well known public key
cryptography techniques. To increase encryption complexity, DNA encoding
mechanism of DNA computing with ECC is preceded.


  Combating bias in NLP requires bias measurement. Bias measurement is almost
always achieved by using lexicons of seed terms, i.e. sets of words specifying
stereotypes or dimensions of interest. This reproducibility study focuses on
the original authors' main claim that the rationale for the construction of
these lexicons needs thorough checking before usage, as the seeds used for bias
measurement can themselves exhibit biases. The study aims to evaluate the
reproducibility of the quantitative and qualitative results presented in the
paper and the conclusions drawn thereof. We reproduce most of the results
supporting the original authors' general claim: seed sets often suffer from
biases that affect their performance as a baseline for bias metrics. Generally,
our results mirror the original paper's. They are slightly different on select
occasions, but not in ways that undermine the paper's general intent to show
the fragility of seed sets.


  Deforming the domain of integration after complexification of the field
variables is an intriguing idea to tackle the sign problem. In thimble
regularization the domain of integration is deformed into an union of manifolds
called Lefschetz thimbles. On each thimble the imaginary part of the action
stays constant and the sign problem disappears. A long standing issue of this
approach is how to determine the relative weight to assign to each thimble
contribution in the (multi)-thimble decomposition. Yet this is an issue one has
to face, as previous work has shown that different theories exist for which the
contributions coming from thimbles other than the dominant one cannot be
neglected. Historically, one of the first examples of such theories is the
one-dimensional Thirring model. Here we discuss how Taylor expansions can be
used to by-pass the need for multi-thimble simulations. If multiple, disjoint
regions can be found in the parameters space of the theory where only one
thimble gives a relevant contribution, multiple Taylor expansions can be
carried out in those regions to reach other regions by single thimble
simulations. Better yet, these Taylor expansions can be bridged by Pad\'e
interpolants. Not only does this improve the convergence properties of the
series, but it also gives access to information about the analytical structure
of the observables. The true singularities of the observables can be recovered.
We show that this program can be applied to the one-dimensional Thirring model
and to a (simple) version of HDQCD. But the general idea behind our strategy
can be helpful beyond thimble regularization itself, i.e. it could be valuable
in studying the singularities of QCD in the complex $\mu_B$ plane. Indeed this
is a program that is currently being carried out by the Bielefeld-Parma
collaboration.


  We consider the problem of learning a coefficient vector x_0\in R^N from
noisy linear observation y=Ax_0+w \in R^n. In many contexts (ranging from model
selection to image processing) it is desirable to construct a sparse estimator
x'. In this case, a popular approach consists in solving an L1-penalized least
squares problem known as the LASSO or Basis Pursuit DeNoising (BPDN).
  For sequences of matrices A of increasing dimensions, with independent
gaussian entries, we prove that the normalized risk of the LASSO converges to a
limit, and we obtain an explicit expression for this limit. Our result is the
first rigorous derivation of an explicit formula for the asymptotic mean square
error of the LASSO for random instances. The proof technique is based on the
analysis of AMP, a recently developed efficient algorithm, that is inspired
from graphical models ideas.
  Simulations on real data matrices suggest that our results can be relevant in
a broad array of practical applications.


  Recent advancements in Large Language Models (LLMs) and Prompt Engineering
have made chatbot customization more accessible, significantly reducing
barriers to tasks that previously required programming skills. However, prompt
evaluation, especially at the dataset scale, remains complex due to the need to
assess prompts across thousands of test instances within a dataset. Our study,
based on a comprehensive literature review and pilot study, summarized five
critical challenges in prompt evaluation. In response, we introduce a
feature-oriented workflow for systematic prompt evaluation. In the context of
text summarization, our workflow advocates evaluation with summary
characteristics (feature metrics) such as complexity, formality, or
naturalness, instead of using traditional quality metrics like ROUGE. This
design choice enables a more user-friendly evaluation of prompts, as it guides
users in sorting through the ambiguity inherent in natural language. To support
this workflow, we introduce Awesum, a visual analytics system that facilitates
identifying optimal prompt refinements for text summarization through
interactive visualizations, featuring a novel Prompt Comparator design that
employs a BubbleSet-inspired design enhanced by dimensionality reduction
techniques. We evaluate the effectiveness and general applicability of the
system with practitioners from various domains and found that (1) our design
helps overcome the learning curve for non-technical people to conduct a
systematic evaluation of summarization prompts, and (2) our feature-oriented
workflow has the potential to generalize to other NLG and image-generation
tasks. For future works, we advocate moving towards feature-oriented evaluation
of LLM prompts and discuss unsolved challenges in terms of human-agent
interaction.


  Boron abundances in A- and B-type stars may be a successful way to track
evolutionary effects in these hot stars. The light elements -- Li, Be, and B --
are tracers of exposure to temperatures more moderate than those in which the
H-burning CN-cycle operates. Thus, any exposure of surface stellar layers to
deeper layers will affect these light element abundances. Li and Be are used in
this role in investigations of evolutionary processes in cool stars, but are
not observable in hotter stars. An investigation of boron, however, is possible
through the B II 1362=C5 resonance line.
  We have gathered high resolution spectra from the IUE database of A- and
B-type stars near 10~M$_\odot$ for which nitrogen abundances have been
determined (by Gies & Lambert, 1992, and Venn 1995). The B II 1362=C5 line is
blended throughout the temperature range of this program, requiring spectrum
syntheses to recover the boron abundances. For no star could we synthesize the
1362=C5 region using the meteoritic/solar boron abundance of log(B) =3D 2.88
(Anders & Grevesse 1989); a lower boron abundance was necessary which may
reflect evolutionary effects (e.g., mass loss or mixing near the
main-sequence), the natal composition of the star forming regions, or a
systematic error in the analyses (e.g., non-LTE effects). Regardless of the
initial boron abundance, and despite the possibility of non-LTE effects, it
seems clear that boron is severely depleted in some stars. It may be that the
nitrogen and boron abundances are anticorrelated, as would be expected from
mixing between the H-burning and outer stellar layers. If, as we suspect, a
residue of boron is present in the A-type supergiants, we may exclude a
scenario in which mixing occurs continuously between the surface and the deep


  Unrolled deep neural networks have attracted significant attention for their
success in various practical applications. In this paper, we explore an
application of deep unrolling in the direction of arrival (DoA) estimation
problem when coarse quantization is applied to the measurements. We present a
compressed sensing formulation for DoA estimation from one-bit data in which
estimating target DoAs requires recovering a sparse signal from a limited
number of severely quantized linear measurements. In particular, we exploit
covariance recovery from one-bit dither samples. To recover the covariance of
transmitted signal, the learned iterative shrinkage and thresholding algorithm
(LISTA) is employed fed by one-bit data. We demonstrate that the upper bound of
estimation performance is governed by the recovery error of the transmitted
signal covariance matrix. Through numerical experiments, we demonstrate the
proposed LISTA-based algorithm's capability in estimating target locations. The
code employed in this study is available online.


  Regional rainfall-runoff modeling is an old but still mostly out-standing
problem in Hydrological Sciences. The problem currently is that traditional
hydrological models degrade significantly in performance when calibrated for
multiple basins together instead of for a single basin alone. In this paper, we
propose a novel, data-driven approach using Long Short-Term Memory networks
(LSTMs), and demonstrate that under a 'big data' paradigm, this is not
necessarily the case. By training a single LSTM model on 531 basins from the
CAMELS data set using meteorological time series data and static catchment
attributes, we were able to significantly improve performance compared to a set
of several different hydrological benchmark models. Our proposed approach not
only significantly outperforms hydrological models that were calibrated
regionally but also achieves better performance than hydrological models that
were calibrated for each basin individually. Furthermore, we propose an
adaption to the standard LSTM architecture, which we call an Entity-Aware-LSTM
(EA-LSTM), that allows for learning, and embedding as a feature layer in a deep
learning model, catchment similarities. We show that this learned catchment
similarity corresponds well with what we would expect from prior hydrological
understanding.


  Since their introduction by Thurston, measured geodesic laminations on
hyperbolic surfaces occur in many contexts. In this survey, we give a
generalization of geodesic laminations on surfaces endowed with a
half-translation structure, called flat laminations, and we define transverse
measures on flat laminations similar to transverse measures on hyperbolic
laminations, taking into account that the images of the leaves of a flat
lamination are in general not pairwise disjoint. One aim is to construct a tool
that could allow a fine description of the space of degenerations of
half-translation structures on a surface. We define a topology on the set of
measured flat laminations and a natural continuous projection of the space of
measured flat laminations onto the space of measured hyperbolic laminations,
for any arbitrary half-translation structure and hyperbolic metric on a
surface. We prove in particular that the space of measured flat laminations is
projectively compact. The main result of this survey is a classification
theorem of (measured) flat laminations on a compact surface endowed with a
half-translation structure. We also give an exposition of that every finite
metric fat graph, outside four homeomorphisms classes, is the support of
uncountably many measured flat laminations with uncountably many leaves none of
which is eventually periodic, and that the space of measured flat laminations
is separable and projectively compact.


  The phase-integral method (PIM) is an asymptotic method of the geometrical
optics or semi-classical type for solving approximately, but in many cases very
accurately, a wide class of differential equations in physics. Unlike the
related (J)WKB method, the higher-order corrections in the PIM can be generated
from a generic, unspecified base function, providing added symmetry and
flexibility. However, with the conventional approach of using the
next-to-lowest (third) order correction to the integrand in the phase integral
as a platform for calculating higher (fifth, seventh, ninth,...) order
corrections, the higher-order calculations very often become quite complicated.
  We therefore introduce a new platform function, which considerably simplifies
the calculation of the third-order contribution for a wide range of problems.
We also present directly integrable conditions for the phase integral, which so
far seem to have gone unnoticed.
  For a large number of observables, our analysis makes a clearer distinction
between physical and, in a sense, unphysical contributions.


  A brief overview is given of X-ray observations of old clusters. Most X-ray
sources in old open clusters are interacting binaries, formed via evolution of
a primordial binary, and emitting X-rays because of magnetic activity; however,
a sizable fraction of the cluster sources is not well understood, including
some of the most luminous ones. Globular clusters appear to contain fewer
magnetically active X-ray sources than expected if one scales from old open
clusters by mass.


  We present a method for generating higher-order finite volume discretizations
for Poisson's equation on Cartesian cut cell grids in two and three dimensions.
The discretization is in flux-divergence form, and stencils for the flux are
computed by solving small weighted least-squares linear systems. Weights are
the key in generating a stable discretization. We apply the method to solve
Poisson's equation on a variety of geometries, and we demonstrate that the
method can achieve second and fourth order accuracy in both truncation and
solution error for these examples. We also show that the Laplacian operator has
only stable eigenvalues for each of these examples.


  For any prime p we consider the density of elements in the multiplicative
group of the finite field F_p having order, respectively index, congruent to
a(mod d). We compute these densities on average, where the average is taken
over all finite fields of prime order. Some connections between the two
densities are established. It is also shown how to compute these densities with
high numerical accuracy.


  The prediction of pancreatic ductal adenocarcinoma therapy response is a
clinically challenging and important task in this high-mortality tumour entity.
The training of neural networks able to tackle this challenge is impeded by a
lack of large datasets and the difficult anatomical localisation of the
pancreas. Here, we propose a hybrid deep neural network pipeline to predict
tumour response to initial chemotherapy which is based on the Response
Evaluation Criteria in Solid Tumors (RECIST) score, a standardised method for
cancer response evaluation by clinicians as well as tumour markers, and
clinical evaluation of the patients. We leverage a combination of
representation transfer from segmentation to classification, as well as
localisation and representation learning. Our approach yields a remarkably
data-efficient method able to predict treatment response with a ROC-AUC of
63.7% using only 477 datasets in total.


  We compare two techniques for following the cooling of gas and its
condensation into galaxies within high resolution simulations of cosmologically
representative regions. Both techniques treat the dark matter using N-body
methods. One follows the gas using smoothed particle hydrodynamics (SPH) while
the other uses simplified recipes from semi-analytic (SA) models. We compare
the masses and locations predicted for dense knots of cold gas (the `galaxies')
when the two techniques are applied to evolution from the same initial
conditions and when the additional complications of star formation and feedback
are ignored. We find that above the effective resolution limit of the two
techniques, they give very similar results both for global quantities such as
the total amount of cooled gas and for the properties of individual `galaxies'.
The SA technique has systematic uncertainties arising from the simplified
cooling model adopted, while details of the SPH implementation can produce
substantial systematic variations in the galaxy masses it predicts.
Nevertheless, for the best current SPH methods and the standard assumptions of
the SA model, systematic differences between the two techniques are remarkably
small. The SA technique gives adequate predictions for the condensation of gas
into `galaxies' at less than one percent of the computational cost of obtaining
similar results at comparable resolution using SPH.


  This paper is devoted to characterizing complex projective structures defined
on Riemann surface orbifolds and giving rise to injective developing maps
defined on the monodromy covering of the surface (orbifold) in question. The
relevance of these structures stems from several problems involving vector
fields with uniform solutions as well as from problems about "simultaneous
uniformization" for leaves of foliations by Riemann surfaces. In this paper, we
first describe the local structure of the mentioned projective structures
showing, in particular, that they are locally bounded. In the case of Riemann
surface orbifolds of finite type, the previous result will then allow us to
provide a detailed global picture of these projective structures by exploiting
their connection with the class of "bounded covering projective structures".


  Gravitational-wave detectors are sensitive not only to astrophysical
gravitational waves, but also to the fluctuating Newtonian gravitational forces
of moving masses in the ground and air around the detector. This paper studies
the gravitational effects of density perturbations in the atmosphere, and from
massive airborne objects near the detector. These effects were previously
considered by Saulson; in this paper I revisit these phenomena, considering
transient atmospheric shocks, and the effects of sound waves or objects
colliding with the ground or buildings around the test masses. I also consider
temperature perturbations advected past the detector as a source of
gravitational noise. I find that the gravitational noise background is below
the expected noise floor even of advanced interferometric detectors, although
only by an order of magnitude for temperature perturbations carried along
turbulent streamlines. I also find that transient shockwaves in the atmosphere
could potentially produce large spurious signals, with signal-to-noise ratios
in the hundreds in an advanced interferometric detector. These signals could be
vetoed by means of acoustic sensors outside of the buildings. Massive
wind-borne objects such as tumbleweeds could also produce gravitational signals
with signal-to-noise ratios in the hundreds if they collide with the
interferometer buildings, so it may be necessary to build fences preventing
such objects from approaching within about 30m of the test masses.


  In previous work we constructed new boson star solutions consisting of a
family of massive complex scalar fields minimally coupled to gravity in which
the individual fields have angular momentum, yet the configuration as a whole
is static and spherically symmetric. In the present article we study the linear
stability of these $\ell$-boson stars with respect to time-dependent, radial
perturbations. The pulsation equations, governing the dynamics of such
perturbations are derived, generalizing previous work initiated by M. Gleiser,
and shown to give rise to a two-channel Schr\"odinger operator. Using standard
tools from the literature, we show that for each fixed value $\ell$ of the
angular momentum number, there exists a family of $\ell$-boson stars which are
linearly stable with respect to radial fluctuations; in this case the
perturbations oscillate in time with given characteristic frequencies which are
computed and compared with the results from a nonlinear numerical simulation.
Further, there is also a family of $\ell$-boson stars which are linearly
unstable. The two families are separated by the configuration with maximum
mass. These results are qualitatively similar to the corresponding stability
results of the standard boson stars with $\ell=0$, and they imply the existence
of new stable configurations that are more massive and compact than usual boson
stars.


  Let $X = \left\{x_1, \dots, x_N\right\} \subset \mathbb{T}^d \cong [0,1]^d$
be a set of $N$ points in the $d-$dimensional torus that we want to arrange as
regularly possible. The purpose of this paper is to introduce a curious energy
functional $$ E(X) = \sum_{1 \leq m,n \leq N \atop m \neq n} \prod_{k=1}^{d}{
(1 - \log{\left(2 \sin{ \left( \pi |x_{m,k} - y_{m,k} |\right)} \right)})}$$
and to suggest that moving a set $X$ into the direction $-\nabla E(X)$ may have
the effect of increasing regularity of the set in the sense of decreasing
discrepancy. We numerically demonstrate the effect for Halton, Hammersley,
Kronecker, Niederreiter and Sobol sets. Lattices in $d=2$ are critical points
of the energy functional, some (possibly all) are strict local minima.


  We perform charge self-consistent LDA+DMFT (density functional theory
combined with dynamical mean field theory) calculations to study correlation
effects on the Fermi surfaces of the iron pnictide superconductors LaFePO and
LiFeP. We find a distinctive change in the topology of the Fermi surface in
both compounds where a hole pocket with Fe dz^2 orbital character changes its
geometry from a closed shape in LDA to an open shape upon inclusion of
correlations.


  We study homogeneous Besov and Triebel--Lizorkin spaces defined on doubling
metric measure spaces in terms of a self-adjoint operator whose heat kernel
satisfies Gaussian estimates together with its derivatives. When the measure
space is a smooth manifold and such operator is a sum of squares of smooth
vector fields, we prove that their intersection with $L^\infty$ is an algebra
for pointwise multiplication. Our results apply to nilpotent Lie groups and
Grushin settings.


  Recently, new topological properties that an operator acting on a topological
vector space can have were introduced: strong hypercyclicity and hypermixing.
We introduce a new property called ultra hypercyclicity, and we compare it to
the other common topological properties, including the new ones. For the family
of weighted backward shifts on $c_0$ and $\ell^p$, we characterize ultra
hypercyclicity in terms of the weight sequence, and frame the open question of
whether or not there exists a strongly hypercyclic weighted backward shift
which is not ultra hypercyclic in terms of properties that the weight sequence
has.


  Neural machine translation (NMT) has achieved notable success in recent
times, however it is also widely recognized that this approach has limitations
with handling infrequent words and word pairs. This paper presents a novel
memory-augmented NMT (M-NMT) architecture, which stores knowledge about how
words (usually infrequently encountered ones) should be translated in a memory
and then utilizes them to assist the neural model. We use this memory mechanism
to combine the knowledge learned from a conventional statistical machine
translation system and the rules learned by an NMT system, and also propose a
solution for out-of-vocabulary (OOV) words based on this framework. Our
experiments on two Chinese-English translation tasks demonstrated that the
M-NMT architecture outperformed the NMT baseline by $9.0$ and $2.7$ BLEU points
on the two tasks, respectively. Additionally, we found this architecture
resulted in a much more effective OOV treatment compared to competitive
methods.


  We have studied the rapid X-ray time variability in 99 pointed observations
with the Rossi X-ray Timing Explorer (RXTE)'s Proportional Counter Array of the
low-mass X-ray binary 1E~1724--3045 which includes, for the first time,
observations of this source in its island and banana states, confirming the
atoll nature of this source. We report the discovery of kilohertz
quasi-periodic oscillations (kHz QPOs). Although we have 5 detections of the
lower kHz QPO and one detection of the upper kHz QPO, in none of the
observations we detect both QPOs simultaneously. By comparing the dependence of
the rms amplitude with energy of kHz QPOs in different atoll sources, we
conclude that this information cannot be use to unambiguously identify the
kilohertz QPOs as was previously thought. We find that Terzan~2 in its
different states shows timing behavior similar to that seen in other
neutron-star low mass X-ray binaries (LMXBs). We studied the flux transitions
observed between February 2004 and October 2005 and conclude that they are due
to changes in the accretion rate.


  According to the recently discovered 'Law of Urination', mammals, ranging in
size from mice to elephants, take, on the average, 21s to urinate. We attempt
to gain insights into the physical processes responsible for this uniformity
using simple dimensional analysis. We assume that the biological apparatus for
urination in mammals simply scales with linear size, and consider the scenarios
where the driving force is gravity or elasticity, and where the response is
dominated by inertia or viscosity. We ask how the time required for urination
depends on the length scale, and find that for the time to be independent of
body size, the dominant driving force must be elasticity, and the dominant
response viscosity. Our note demonstrates that dimensional analysis can indeed
readily give insights into complex physical and biological processes.


  The high-density electron gas in a strong magnetic field B and at zero
temperature is investigated. The quantum strong-field limit is considered in
which only the lowest Landau level is occupied. It is shown that the
perturbation series of the ground-state energy can be represented in analogy to
the Gell-Mann Brueckner expression of the ground-state energy of the field-free
electron gas. The role of the expansion parameter is taken by r_B= (2/3 \pi^2)
(B/m^2) (\hbar r_s /e)^3 instead of the field-free Gell-Mann Brueckner
parameter r_s. The perturbation series is given exactly up to o(r_B) for the
case of a small filling factor for the lowest Landau level.


  Hexagonally arranged Au nano particles (NPs) exhibiting a broad size
distribution ranging from 30 nm to 80 nm with a Gaussian shape were deposited
on Si substrates and irradiated with Ar+ and Ga+ ions with various energies
from 20 to 350 keV and 1 to 30 keV, respectively. The size and energy
dependence of the sputter yield were measured using high resolution scanning
electron microscopy image analysis. These results were compared to simulation
results obtained by iradina, a Monte Carlo (MC) code, which takes the specifics
of the nano geometry into account. The experimental obtained sputter yields are
significantly higher compared to the calculated simulation results for both
bulk and the nano geometry. The difference can be clearly attributed to
thermally driven effects, which significantly influence the measured sputter
yields.


  In this paper, AdS black brane solution of Einstein-Hilbert gravity with
non-abelian exponential guage theory of Yang-Mills type is introduced. DC
conductivity and the ratio of shear viscosity to entropy density as two
important transport coefficients are calculated by using of Kubo formula in the
context of AdS/CFT duality. Our results recover the Yang-Mills model in $q\to
\infty$ limit.