  Non-axisymmetries in the Galactic potential (spiral arms and bar) induce
kinematic groups such as the Hercules stream. Assuming that Hercules is caused
by the effects of the Outer Lindblad Resonance of the Galactic bar, we model
analytically its properties as a function of position in the Galaxy and its
dependence on the bar's pattern speed and orientation. Using data from the RAVE
survey we find that the azimuthal velocity of the Hercules structure decreases
as a function of Galactocentric radius, in a manner consistent with our
analytical model. This allows us to obtain new estimates of the parameters of
the Milky Way's bar. The combined likelihood function of the bar's pattern
speed and angle has its maximum for a pattern speed of $\Omega_b=(1.89 \pm
0.08) \times \Omega_0$ where $\Omega_0$ is the local circular frequency.
Assuming a Solar radius of 8.05 kpc and a local circular velocity of 238 km/s,
this corresponds to $\Omega_b=56\pm 2$ km/s/kpc. On the other hand, the bar's
orientation $\phi_b$ cannot be constrained with the available data. In fact,
the likelihood function shows that a tight correlation exists between the
pattern speed and the orientation, implying that a better description of our
best fit results is given by the linear relation $\Omega_b/\Omega_0=1.91 +
0.0044[\phi_b(\deg)-48]$, with standard deviation of 0.02. For example, for an
angle of $\phi_b=30\deg$ the pattern speed is $54.0\pm0.5$ km/s/kpc. These
results are not very sensitive to the other Galactic parameters such as the
circular velocity curve or the peculiar motion of the Sun, and are robust to
biases in distance.


  A Cayley-Sudoku table of a finite group G is a Cayley table for G subdivided
into uniformly sized rectangular blocks, in such a way that each group element
appears once in each block. They were introduced by J. Carmichael, K.
Schloeman, and M. B. Ward [CSW], who also gave three ways to construct them.
This paper has four aims. First, we review Constructions 1 and 2 of [CSW] and
uncover their unexpected heritage in the work of R. Baer and J. Denes. Next we
turn to some new instances of Construction 2 inspired by Baer, which answer an
open question in [CSW]. Third, we provide a very brief outline of recent
reinventions of special cases of Construction 1 in the literature. We conclude
with an invitation to seek out the heritage of Construction 3. Portions of this
paper appear in: Kady Hossner Boden and Michael B. Ward (2019) A New Class of
Cayley-Sudoku Tables, Mathematics Magazine, 92:4, 243-251, DOI:
10.1080/0025570X.2019.1613949


  The properties of randomly evolving special trees having defined and analyzed
already in two earlier papers (arXiv:cond-mat/0205650 and
arXiv:cond-mat/0211092) have been investigated in the case when the continuous
time parameter converges to infinity. Equations for generating functions of the
number of nodes and end-nodes in a stationary (i.e. infinitely old) tree have
been derived. In order to solve exactly these equations we have chosen three
simple distributions for the number of new nodes produced by one dying node. By
using appropriate method we have calculated step-by-step the probabilities of
finding n=1,2,... nodes as well as end-nodes in a stationary random tree. The
conclusion to be correct that in the evolution process the formation of a
rod-like stationary tree is much more probable than the formation of a tree
with many branches.


  In feature-based simultaneous localization and mapping (SLAM), line features
complement the sparsity of point features, making it possible to map the
surrounding environment structure. Existing approaches utilizing line features
have primarily employed a measurement model that uses line re-projection.
However, the direction vectors used in the 3D line mapping process cannot be
corrected because the line measurement model employs only the lines' normal
vectors in the Pl\"{u}cker coordinate. As a result, problems like degeneracy
that occur during the 3D line mapping process cannot be solved. To tackle the
problem, this paper presents a UV-SLAM, which is an unconstrained line-based
SLAM using vanishing points for structural mapping. This paper focuses on using
structural regularities without any constraints, such as the Manhattan world
assumption. For this, we use the vanishing points that can be obtained from the
line features. The difference between the vanishing point observation
calculated through line features in the image and the vanishing point
estimation calculated through the direction vector is defined as a residual and
added to the cost function of optimization-based SLAM. Furthermore, through
Fisher information matrix rank analysis, we prove that vanishing point
measurements guarantee a unique mapping solution. Finally, we demonstrate that
the localization accuracy and mapping quality are improved compared to the
state-of-the-art algorithms using public datasets.


  A crucial problem in genome assembly is the discovery and correction of
misassembly errors in draft genomes. We develop a method that will enhance the
quality of draft genomes by identifying and removing misassembly errors using
paired short read sequence data and optical mapping data. We apply our method
to various assemblies of the loblolly pine and Francisella tularensis genomes.
Our results demonstrate that we detect more than 54% of extensively
misassembled contigs and more than 60% of locally misassembed contigs in an
assembly of Francisella tularensis, and between 31% and 100% of extensively
misassembled contigs and between 57% and 73% of locally misassembed contigs in
the assemblies of loblolly pine. MISSEQUEL can be downloaded at
http://www.cs.colostate.edu/seq/.


  Functors from (co)operads to bialgebras relate Hopf algebras that occur in
renormalisation to operads, which simplifies the proof of the Hopf algebra
axioms, and induces a characterisation of the corresponding group of characters
and Lie algebra of primitives of the dual in terms of the operad. In addition,
it is shown that the Wick rotation formula leads to canonical algebras for one
of these operads.


  In fluids and plasmas with zonal flow reversed shear, a peculiar kind of
transport barrier appears in the shearless region, one that is associated with
a proper route of transition to chaos. Using a symplectic nontwist maps, which
model such zonal flows, we investigate these barriers. In particular, the
standard nontwist map, a paradigm of nontwist systems, is used to analyze the
parameter dependence of the transport through a broken shearless barrier.
Varying a proper control parameter, we identify the onset of structures with
high stickiness that give rise to an effective barrier near the broken
shearless curve. Several diagnostics are used: stickiness is measured by escape
time and transmissivity plots, while barriers that separate different regions
of stickiness are identified by employing two indicators in the phase space,
the finite-time rotation number and the finite-time Lyapunov exponent.


  In recent work, we examined how different modes in the ringdown phase of a
binary coalescence are excited as a function of the final plunge geometry. At
least in the large mass ratio limit, we found a clean mapping between angles
describing the plunge and the amplitude of different quasi-normal modes (QNMs)
which constitute the ringdown. In this study, we use that mapping to construct
a waveform model expressed as a sum of QNMs where the mode amplitudes and
phases are determined by the source plunge parameters. We first generate a
large number of calibration waveforms and interpolate between fits of each mode
amplitude and phase up to $\ell \leq 8$ and $\ell - |m| \leq 4$. The density of
our calibration data allows us to resolve important features such as phase
transition discontinuities at large misalignments. Using our ringdown waveform
model, we then perform Bayesian parameter estimation with added white Gaussian
noise to demonstrate that, in principle, the mode amplitudes can be measured
and used to constrain the plunge geometry. We find that inferences are
substantially improved by incorporating prior information constraining mode
excitation, which motivates work to understand and characterize how the QNM
excitation depends on the coalescence geometry. These results are part of a
broader effort to map the mode excitation from arbitrary masses and spins,
which will be useful for characterizing ringdown waves in upcoming
gravitational-wave measurements.


  Diverse disciplines are interested in how the coordination of interacting
agents' movements, emotions, and physiology over time impacts social behavior.
Here, we describe a new multivariate procedure for automating the investigation
of this kind of behaviorally-relevant "interactional synchrony", and introduce
a novel interactional synchrony measure based on features of dynamic time
warping (DTW) paths. We demonstrate that our DTW path-based measure of
interactional synchrony between facial action units of two people interacting
freely in a natural social interaction can be used to predict how much trust
they will display in a subsequent Trust Game. We also show that our approach
outperforms univariate head movement models, models that consider participants'
facial action units independently, and models that use previously proposed
synchrony or similarity measures. The insights of this work can be applied to
any research question that aims to quantify the temporal coordination of
multiple signals over time, but has immediate applications in psychology,
medicine, and robotics.


  We propose a simple model for an optically thick radiative torus in local
thermodynamic equilibrium around a Kerr black hole. The hydrodynamics
structure, which is not affected by the radiation field, is the same as for the
so--called polish doughnuts. Under the assumption of isentropic fluid and
polytropic equation of state, a simple stationary and axisymmetric solution to
the relativistic radiation hydrodynamics equations is possible, for which the
temperature of the torus scales like the specific enthalpy. The astrophysical
relevance of the model is briefly discussed.


  We propose a complete, d=6 covariant and kappa-symmetric, action for an
M-theory five-brane propagating in D=11 supergravity background.


  The KiDS Strongly lensed QUAsar Detection project (KiDS-SQuaD) aims at
finding as many previously undiscovered gravitational lensed quasars as
possible in the Kilo Degree Survey. This is the second paper of this series
where we present a new, automatic object classification method based on machine
learning technique. The main goal of this paper is to build a catalogue of
bright extragalactic objects (galaxies and quasars), from the KiDS Data Release
4, with a minimum stellar contamination, preserving the completeness as much as
possible, to then apply morphological methods to select reliable
gravitationally lensed (GL) quasar candidates. After testing some of the most
used machine learning algorithms, decision trees based classifiers, we decided
to use CatBoost, that was specifically trained with the aim of creating a
sample of extragalactic sources as clean as possible from stars. We discuss the
input data, define the training sample for the classifier, give quantitative
estimates of its performances, and finally describe the validation results with
Gaia DR2, AllWISE, and GAMA catalogues. We have built and make available to the
scientific community the KiDS Bright EXtraGalactic Objects catalogue
(KiDS-BEXGO), specifically created to find gravitational lenses. This is made
of $\approx6$ millions of sources classified as quasars ($\approx 200\,000$)
and galaxies ($\approx 5.7$M), up to $r<22^m$. From this catalog we selected
'Multiplets': close pairs of quasars or galaxies surrounded by at least one
quasar, presenting the 12 most reliable gravitationally lensed quasar
candidates, to demonstrate the potential of the catalogue, which will be
further explored in a forthcoming paper. We compared our search to the previous
one, presented in the first paper from this series, showing that employing a
machine learning method decreases the stars-contaminators within the GL
candidates.


  Text-to-SQL semantic parsing has made significant progress in recent years,
with various models demonstrating impressive performance on the challenging
Spider benchmark. However, it has also been shown that these models often
struggle to generalize even when faced with small perturbations of previously
(accurately) parsed expressions. This is mainly due to the linguistic form of
questions in Spider which are overly specific, unnatural, and display limited
variation. In this work, we use data augmentation to enhance the robustness of
text-to-SQL parsers against natural language variations. Existing approaches
generate question reformulations either via models trained on Spider or only
introduce local changes. In contrast, we leverage the capabilities of large
language models to generate more realistic and diverse questions. Using only a
few prompts, we achieve a two-fold increase in the number of questions in
Spider. Training on this augmented dataset yields substantial improvements on a
range of evaluation sets, including robustness benchmarks and out-of-domain
data.


  These lectures give an introduction to the structure of the nucleon as seen
with the electromagnetic probe. Particular emphasis is put on the form factors,
the strangeness content, Compton scattering and polarizabilities, pion photo-
and electroproduction, the spin structure and sum rules. The existing data are
compared to predictions obtained from chiral perturbation theory, dispersion
theory and effective Lagrangians.


  Vacuum polarization of massive scalar fields in a thermal state at arbitrary
temperature is studied near the horizon of a Reissner-Nordstr\"{o}m black hole.
We derived an analytic form of $<\phi^2>$ approximately in the large mass limit
near the black hole horizon. We uses the zeroth order WKB approximation and
power series expansion near the horizon for the Euclideanized mode function.
Our formula for the vacuum polarization shows regular behavior on the horizon
if the temperature of the scalar field is equal to the Hawking temperature of
the black hole. The finite part of the vacuum polarization agrees with the
result of the DeWitt-Schwinger approximation up to $O(m^{-4})$ which is the
next leading order of the expansion.


  We propose a new formulation of manifestly Lorentz-covariant spinor
wave-packet basis. The conventional definition of the spinor wave packet is
problematic in the sense that it suffers from mixing with other wave packets
under Lorentz transformations. Our formulation evades this difficulty of
mixing. This wave packet forms a complete set that can expand a free spinor
field in a Lorentz covariant manner. In addition, we present a
Lorentz-invariant expression of zero-point energy.


  Wiring diagrams usually serve as a tool in the study of arrangements of lines
and pseudolines. In this paper we go in the opposite direction, using known
properties of line arrangements to motivate certain equivalence relations and
actions on sets of wiring diagrams, which preserve the incidence lattice and
the fundamental groups of the affine and projective complements of the
diagrams. These actions are used in [GTV] to classify real arrangements of up
to 8 lines and show that in this case, the incidence lattice determines both
the affine and the projective fundamental groups.


  This paper studies the stabilization and safety problems of nonlinear
time-delay systems, where time delays exist in system state and affect the
controller design. Following the Razumikhin approach, we propose a novel
control Lyapunov-Razumikhin function to facilitate the controller design and to
achieve the stabilization objective. To ensure the safety objective, we propose
a Razumikhin-type control barrier function for time-delay systems for the first
time. Furthermore, the proposed Razumikhin-type control Lyapunov and barrier
functions are merged such that the stabilization and safety control design can
be combined to address the stabilization and safety simultaneously, which
further extends the control design from the delay-free case into the time-delay
case. Finally, the proposed approach is illustrated via a numerical example.


  We report experimental generation of a noisy entangled four-photon state that
exhibits a separation between the secure key contents and distillable
entanglement, a hallmark feature of the recently established quantum theory of
private states. The privacy analysis, based on the full tomographic
reconstruction of the prepared state, is utilized in a proof-of-principle key
generation. The inferiority of distillation-based strategies to extract the key
is exposed by an implementation of an entanglement distillation protocol for
the produced state.


  In swarm robotics, a set of robots has to perform a given task with specified
internal capabilities (model) and under a given adversarial scheduler. Relation
between a model $M_1$ under scheduler $S_1$, and that of a model $M_2$ under
scheduler $S_2$ can be of four different types: not less powerful, more
powerful, equivalent and orthogonal. In literature there are four main models
of robots with lights: $\mathcal{LUMI}$, where robots have the power of
observing the lights of all the robots, $\mathcal{FSTA}$ , where each robot can
see only its own light, $\mathcal{FCOM}$, where each robot can observe the
light of all other robots except its own and $\mathcal{OBLOT}$, where the
robots do not have any light. In this paper, we investigate the computational
power of $\mathcal{FSTA}$ and $\mathcal{FCOM}$ model under asynchronous
scheduler by comparing it with other model and scheduler combinations. Our main
focus is to understand and compare the power of persistent memory and explicit
communication in robots under asynchronous scheduler.


  If the Galaxy is axisymmetric and in dynamical equilibrium, we expect
negligible fluctuations in the residual line-of-sight velocity field. Recent
results using the \apg{} survey find significant fluctuations in velocity for
stars in the midplane ($|z|<$0.25 kpc) out to 5 kpc, suggesting that the
dynamical influence of non-axisymmetric features i.e., the Milky Way's bar,
spiral arms and merger events extends out to the Solar neighborhood. Their
measured power spectrum has a characteristic amplitude of 11 \kms{} on a scale
of 2.5 kpc. The existence of such large-scale streaming motions has important
implications for determining the Sun's motion about the Galactic Centre. Using
Red Clump stars from \glh{} and \apg{}, we map the line-of-sight velocities
around the Sun (d$<$5 kpc), and $|z|<$1.25 kpc from the midplane. By
subtracting a smooth axisymmetric model for the velocity field, we study the
residual fluctuations and compare our findings with mock survey generated by
\glx{}. We find negligible large-scale fluctuations away from the plane. In the
mid-plane, we reproduce the earlier \apg{} power spectrum but with 20\% smaller
amplitude (9.3 \kms{}) after taking into account a few systematics (e.g.,
volume completeness). Using a flexible axisymmetric model the power-amplitude
is further reduced to 6.3 \kms{}. Additionally, our simulations show that, in
the plane, distances are underestimated for high-mass Red Clump stars which can
lead to spurious power-amplitude of about 5.2 \kms{}. Taking this into account,
we estimate the amplitude of real fluctuations to be $<$4.6 \kms{}, about a
factor of three less than the \apg{} result.


  Chest radiographs are among the most frequently acquired images in radiology
and are often the subject of computer vision research. However, most of the
models used to classify chest radiographs are derived from openly available
deep neural networks, trained on large image-datasets. These datasets routinely
differ from chest radiographs in that they are mostly color images and contain
several possible image classes, while radiographs are greyscale images and
often only contain fewer image classes. Therefore, very deep neural networks,
which can represent more complex relationships in image-features, might not be
required for the comparatively simpler task of classifying grayscale chest
radiographs. We compared fifteen different architectures of artificial neural
networks regarding training-time and performance on the openly available
CheXpert dataset to identify the most suitable models for deep learning tasks
on chest radiographs. We could show, that smaller networks such as ResNet-34,
AlexNet or VGG-16 have the potential to classify chest radiographs as precisely
as deeper neural networks such as DenseNet-201 or ResNet-151, while being less
computationally demanding.


  Given that Sr2RuO4 is a two-component p-wave superconductor, there exists the
possibility of well defined collective modes corresponding to fluctuations of
the relative phase and spin-orientation of the two components of the order
parameter. We demonstrate that at temperatures much below Tc, these modes have
energies small compared to the pairing gap scale if the superconductivity
arises primarily from the quasi 1D (dxz and dyz) bands, while it is known that
their energies become comparable to the pairing gap scale if there is a
substantial involvement of the quasi 2D (dxy) band. Therefore, the orbital
origin of the superconductivity can be determined by measuring the energies of
these collective modes.


  Bent functions are of great importance in both mathematics and information
science. The $\mathcal{P}\mathcal{S}$ class of bent functions was introduced by
Dillon in 1974, but functions belonging to this class that can be explicitly
represented are only the $\mathcal{P}\mathcal{S}_{\text{ap}}$ functions, which
were also constructed by Dillon after his introduction of the
$\mathcal{P}\mathcal{S}$ class. In this paper, a technique of using finite
pre-quasifield spread from finite geometry to construct
$\mathcal{P}\mathcal{S}$ bent functions is proposed. The constructed functions
are in similar styles with the $\mathcal{P}\mathcal{S}_{\text{ap}}$ functions.
To explicitly represent them in bivariate forms, the main task is to compute
compositional inverses of certain parametric permutation polynomials over
finite fields of characteristic 2. Concentrated on the Dempwolff-M\"uller
pre-quasifield, the Knuth pre-semifield and the Kantor pre-semifield, three new
subclasses of the $\mathcal{P}\mathcal{S}$ class are obtained. They are the
only sub-classes that can be explicitly constructed more than 30 years after
the $\mathcal{P}\mathcal{S}_{\text{ap}}$ subclass was introduced.


  We discuss the possibility of using experiments timing the propagation of
neutrino beams over large distances to help determine the absolute masses of
the three neutrinos.


  We report for the first time a method-independent geometrical expression for
the angular resolution of an arbitrary network of interferometric gravitational
wave (GW) detectors when the arrival-time of a GW is unknown. We discuss the
implications of our results on how to improve angular resolutions of a GW
network and on improvements of localization methods. An example of an
improvement to the null-stream localization method for GWs of unknown waveforms
is demonstrated.


  The established thermodynamic formalism of chaotic dynamics, valid at
statistical equilibrium, is here generalized to systems out of equilibrium,
that have yet to relax to a steady state. A relation between information,
escape rate, and the phase-space average of an integrated observable (e.g.
Lyapunov exponent, diffusion coefficient) is obtained for finite time. Most
notably, the thermodynamic treatment may predict the phase-space profile of any
finite-time integrated observable from the leading and subleading
eigenfunctions of the Perron-Frobenius/Koopman transfer operator. Examples of
that equivalence are shown, and the theory is tested analytically on the
Bernoulli map, while numerically on the perturbed cat map, the H\'enon map, and
the Ikeda map, all paradigms of chaos.


  Vision transformers have demonstrated the potential to outperform CNNs in a
variety of vision tasks. But the computational and memory requirements of these
models prohibit their use in many applications, especially those that depend on
high-resolution images, such as medical image classification. Efforts to train
ViTs more efficiently are overly complicated, necessitating architectural
changes or intricate training schemes. In this work, we show that standard ViT
models can be efficiently trained at high resolution by randomly dropping input
image patches. This simple approach, PatchDropout, reduces FLOPs and memory by
at least 50% in standard natural image datasets such as ImageNet, and those
savings only increase with image size. On CSAW, a high-resolution medical
dataset, we observe a 5 times savings in computation and memory using
PatchDropout, along with a boost in performance. For practitioners with a fixed
computational or memory budget, PatchDropout makes it possible to choose image
resolution, hyperparameters, or model size to get the most performance out of
their model.


  Deep-sea archives all over the world show an enhanced concentration of the
radionuclide $^{60}$Fe, isolated in layers dating from about 2.2 Myr ago. Since
this comparatively long-lived isotope is not naturally produced on Earth, such
an enhancement can only be attributed to extraterrestrial sources, particularly
one or several nearby supernovae in the recent past. It has been speculated
that these supernovae might have been involved in the formation of the Local
Superbubble, our Galactic habitat. Here, we summarize our efforts in giving a
quantitative evidence for this scenario. Besides analytical calculations, we
present results from high-resolution hydrodynamical simulations of the Local
Superbubble and its presumptive neighbor Loop I in different environments,
including a self-consistently evolved supernova-driven interstellar medium. For
the superbubble modeling, the time sequence and locations of the generating
core-collapse supernova explosions are taken into account, which are derived
from the mass spectrum of the perished members of certain, carefully
preselected stellar moving groups. The release and turbulent mixing of
$^{60}$Fe is followed via passive scalars, where the yields of the decaying
radioisotope were adjusted according to recent stellar evolution calculations.
The models are able to reproduce both the timing and the intensity of the
$^{60}$Fe excess observed with rather high precision. We close with a
discussion of recent developments and give future perspectives.


  We present the first installment of a massive spectroscopic survey of
Galactic O stars, based on new, high signal-to-noise ratio, R~2500 digital
observations from both hemispheres selected from the Galactic O-Star Catalog of
Ma\'iz Apell\'aniz et al. (2004) and Sota et al. (2008). The spectral
classification system is rediscussed and a new atlas is presented, which
supersedes previous versions. Extensive sequences of exceptional objects are
given, including types Ofc, ON/OC, Onfp, Of?p, Oe, and double-lined
spectroscopic binaries. The remaining normal spectra bring this first sample to
184 stars, which is close to complete to B=8 and north of delta = -20 and
includes all of the northern objects in Ma\'iz Apell\'aniz et al. (2004) that
are still classified as O stars. The systematic and random accuracies of these
classifications are substantially higher than previously attainable, because of
the quality, quantity, and homogeneity of the data and analysis procedures.
These results will enhance subsequent investigations in Galactic astronomy and
stellar astrophysics. In the future we will publish the rest of the survey,
beginning with a second paper that will include most of the southern stars in
Ma\'iz Apell\'aniz et al. (2004).


  It is proved that a ring $A$ is a right or left Noetherian, right
distributive centrally essential ring if and only if $A=A_1\times\cdots\times
A_n$, where each of the rings $A_i$ is either a commutative Dedekind domain or
a uniserial Artinian centrally essential (not necessarily commutative) ring.
  V.T.Markov is supported by the Russian Foundation for Basic Research, project
17-01-00895-A. A.A.Tuganbaev is supported by Russian Scientific Foundation,
project 16-11-10013.


  In real-world and online social networks, individuals receive and transmit
information in real time. Cascading information transmissions (e.g. phone
calls, text messages, social media posts) may be understood as a realization of
a diffusion process operating on the network, and its branching path can be
represented by a directed tree. The process only traverses and thus reveals a
limited portion of the edges. The network reconstruction/inference problem is
to infer the unrevealed connections. Most existing approaches derive a
likelihood and attempt to find the network topology maximizing the likelihood,
a problem that is highly intractable. In this paper, we focus on the network
reconstruction problem for a broad class of real-world diffusion processes,
exemplified by a network diffusion scheme called respondent-driven sampling
(RDS). We prove that under realistic and general models of network diffusion,
the posterior distribution of an observed RDS realization is a Bayesian
log-submodular model.We then propose VINE (Variational Inference for Network
rEconstruction), a novel, accurate, and computationally efficient variational
inference algorithm, for the network reconstruction problem under this model.
Crucially, we do not assume any particular probabilistic model for the
underlying network. VINE recovers any connected graph with high accuracy as
shown by our experimental results on real-life networks.


  If a new high-mass resonance is discovered at the Large Hadron Collider,
model-independent techniques to identify the production mechanism will be
crucial to understand its nature and effective couplings to Standard Model
particles. We present a powerful and model-independent method to infer the
initial state in the production of any high-mass color-singlet system by using
a tight veto on accompanying hadronic jets to divide the data into two mutually
exclusive event samples (jet bins). For a resonance of several hundred GeV, the
jet binning cut needed to discriminate quark and gluon initial states is in the
experimentally accessible range of several tens of GeV. It also yields
comparable cross sections for both bins, making this method viable already with
the small event samples available shortly after a discovery. Theoretically, the
method is made feasible by utilizing an effective field theory setup to compute
the jet cut dependence precisely and model independently and to systematically
control all sources of theoretical uncertainties in the jet binning, as well as
their correlations. We use a 750 GeV scalar resonance as an example to
demonstrate the viability of our method.


  We present the Green's functions that are the solutions of the massive
Klein-Gordon equation for a scalar field with non-minimal coupling to
gravitation for several static and expanding cosmological models. An important
feature of such functions is that they can be used to study the appearence of a
Casimir energy in models of the universe with compact spatial sections.


  We investigate recursive relations for the Grothendieck classes of the affine
graph hypersurface complements of melonic graphs. We compute these classes
explicitly for several families of melonic graphs, focusing on the case of
graphs with valence-$4$ internal vertices, relevant to CTKT tensor models. The
results hint at a complex and interesting structure, in terms of divisibility
relations or nontrivial relations between classes of graphs in different
families. Using the recursive relations we prove that the Grothendieck classes
of all melonic graphs are positive as polynomials in the class of the moduli
space $\mathcal M_{0,4}$. We also conjecture that the corresponding polynomials
are log-concave, on the basis of hundreds of explicit computations.


  Let $X$ be a Peano continuum having a free arc and let $C^0(X)$ be the
semigroup of continuous self-maps of $X$. A subsemigroup $F\subset C^0(X)$ is
said to be sensitive, if there is some constant $c>0$ such that for any
nonempty open set $U\subset X$, there is some $f\in F$ such that the diameter
${\rm diam}(f(U))>c$. We show that if $X$ admits a sensitive commutative
subsemigroup $F$ of $C^0(X)$ consisting of continuous open maps, then either
$X$ is an arc, or $X$ is a circle.


  The correlation of the fractionally represented hypercharge group with the
isospin and colour group in the standard model determines as faithfully
represented internal group the quotient group
${\U(1)\x\SU(2)\x\SU(3)\over\Z_2\x\Z_3}$. The discrete cyclic central
abelian-nonabelian internal correlation involved is considered with respect to
its consequences for the representations by the standard model fields, the
electroweak mixing angle and the symmetry breakdown. There exists a further
discrete $\Z_2$-correlation between chirality and Lorentz properties and also a
continuous $\U(1)$-external-internal one between hyperisospin and chirality.


  The $\vec{k}.\vec{p}$ perturbation theory in semiconductor modifies some spin
related parameters of the semi-conducting system. Furthermore, renormalization
of the Kane model parameters occurs when temperature appears in the scenario.
In this paper, we have analysed the consequences of this renormalized Kane
parameters on some spin transport issues. It is noteworthy to study that the
temperature corrected scenario, explained here can open up a new direction
towards the spin calorimetric applications in semiconductors.


  We report on the systematic characterization of conductive micro-channels
fabricated in single-crystal diamond with direct ion microbeam writing. Focused
high-energy (~MeV) helium ions are employed to selectively convert diamond with
micrometric spatial accuracy to a stable graphitic phase upon thermal
annealing, due to the induced structural damage occurring at the end-of-range.
A variable-thickness mask allows the accurate modulation of the depth at which
the microchannels are formed, from several {\mu}m deep up to the very surface
of the sample. By means of cross-sectional transmission electron microscopy
(TEM) we demonstrate that the technique allows the direct writing of amorphous
(and graphitic, upon suitable thermal annealing) microstructures extending
within the insulating diamond matrix in the three spatial directions, and in
particular that buried channels embedded in a highly insulating matrix emerge
and electrically connect to the sample surface at specific locations. Moreover,
by means of electrical characterization both at room temperature and variable
temperature, we investigate the conductivity and the charge-transport
mechanisms of microchannels obtained by implantation at different ion fluences
and after subsequent thermal processes, demonstrating that upon
high-temperature annealing, the channels implanted above a critical damage
density convert to a stable graphitic phase. These structures have significant
impact for different applications, such as compact ionizing radiation
detectors, dosimeters, bio-sensors and more generally diamond-based devices
with buried three-dimensional all-carbon electrodes.


  By means of the recently proposed algorithm based on the tensor product
states, the magnetization process of the spin-1/2 anti-ferromagnetic XXZ model
on a square lattice is investigated. In the large spin-anisotropy limit, clear
evidence of a first-order spin-flip transition is observed as an external
magnetic field is increased. Our findings of the critical field and the
discrete jumps in various local order parameters are in good agreement with the
quantum Monte Carlo data in the literature. Our results imply that this
algorithm can be an accurate and efficient numerical approach in studying
first-order quantum phase transitions in two dimensions.


  Carefully-designed schemas describing how to collect and annotate dialog
corpora are a prerequisite towards building task-oriented dialog systems. In
practical applications, manually designing schemas can be error-prone,
laborious, iterative, and slow, especially when the schema is complicated. To
alleviate this expensive and time consuming process, we propose an unsupervised
approach for slot schema induction from unlabeled dialog corpora. Leveraging
in-domain language models and unsupervised parsing structures, our data-driven
approach extracts candidate slots without constraints, followed by
coarse-to-fine clustering to induce slot types. We compare our method against
several strong supervised baselines, and show significant performance
improvement in slot schema induction on MultiWoz and SGD datasets. We also
demonstrate the effectiveness of induced schemas on downstream applications
including dialog state tracking and response generation.


  We describe an extension of the DeepMind Kinetics human action dataset from
600 classes to 700 classes, where for each class there are at least 600 video
clips from different YouTube videos. This paper details the changes introduced
for this new release of the dataset, and includes a comprehensive set of
statistics as well as baseline results using the I3D neural network
architecture.


  During the last years it has become clear that global O(N) defects and U(1)
cosmic strings do not lead to the pronounced first acoustic peak in the power
spectrum of anisotropies of the cosmic microwave background which has recently
been observed to high accuracy. Inflationary models cannot easily accommodate
the low second peak indicated by the data. Here we construct causal scaling
seed models which reproduce the first and second peak. Future, more precise CMB
anisotropy and polarization experiments will however be able to distinguish
them from the ordinary adiabatic models.


  A plethora of applications have recently motivated extensive efforts on the
generation of low noise Kerr solitons and coherent frequency combs in various
platforms ranging from fiber to whispering gallery and integrated microscale
resonators. However, the Kerr (cubic) nonlinearity is inherently weak, and in
contrast, strong quadratic nonlinearity in optical resonators is expected to
provide an alternative means for soliton formation with promising potential.
Here, we demonstrate the formation of a dissipative quadratic soliton via
non-stationary optical parametric amplification in the presence of significant
temporal walk-off between pump and signal leading to half-harmonic generation
accompanied by a substantial pulse compression (exceeding a factor of 40) at
low pump pulse energies ($\sim$ 4 picojoules). The bright quadratic soliton
forms in a low-finesse cavity in both normal and anomalous dispersion regimes,
which is in stark contrast with bright Kerr solitons. We present a route to
significantly improve the performance of the demonstrated quadratic soliton
when extended to an integrated nonlinear platform to realize highly-efficient
extreme pulse compression leading to the formation of few-cycle soliton pulses
starting from ultra-low energy picosecond scale pump pulses that are widely
tunable from ultra-violet to mid-infrared spectral regimes.


  In soft matter structure couples to flow and vice versa. Complementary to
structural investigations, we here are interested in the determination of
particle velocities of charged colloidal suspensions of different structure
under flow. In a combined effort of theory and experiment we determine the
Fourier transform of the super-heterodyne field auto-correlation function
(power spectrum) which in frequency space is found to be well separated from
homodyne contributions and low frequency noise. Under certain conditions the
power spectrum is dominated by incoherently scattered light, originating from
the unavoidable size polydispersity of colloidal particles. A simple
approximate form for the low-wavenumber self-intermediate scattering function
is proposed, reminiscent to the case of non-interacting particles. We
experimentally scrutinize the range of applicability of these simplified
calculations on employing a parabolic electro-osmotic flow profile. Both for
non-interacting and strongly interacting fluid particle systems, the spectra
are well described as diffusion-broadened velocity distributions comprising an
osmotic flow-averaged superposition of Lorentzians at distinct locations. We
discuss the performance and scope of this approach with particular focus on
moderately strong interactions and on multiphase flow. In addition, we point to
some remaining theoretical challenges in connection to the observed linear
increase of the effective diffusion constant and the integrated spectral power
with increasing electric field strength.


  Recent times have seen surge of research activity on systems combining fluid
mechanics and electromagnetic fields. In radiation optics, whenever information
about the distribution of pressure in a dielectric fluid is required, the
contribution from electrostriction becomes important. In the present paper we
calculate how the local pressure varies with position and time when a laser
beam is imposed in a uniform fluid. A Gaussian intensity profile of arbitrary
time dependence is assumed for the beam, and general results are derived in
this case. For demonstration we analyze two different cases: first, that the
beam is imposed suddenly (mathematically in the form of a step function);
secondly, that the beam is switched on in a soft way. In both cases, simple
analytical expressions for the pressure distribution are found.


  Context: Optically luminous quasars are metal rich across all redshifts.
Surprisingly, there is no significant trend in the broad-line region (BLR)
metallicity with different star formation rates (SFR) and the average N V/ C IV
metallicity does not appear to exceed $9.5~Z_\odot$. Combined, these
observations may suggest a metallicity ceiling.
  Aims: Here, we conduct an exploratory study on scenarios relating to the
evolution of embedded stars that may lead to a metallicity ceiling in quasar
disks.
  Methods: We develop a simple model that starts with gas in a ''closed box'',
which is enriched by cycles of stellar evolution until eventually newly formed
stars may undergo significant mass loss before they reach the supernovae stage
and further enrichment is halted. Using the MESA code, we create a grid over a
parameter space of masses ($>8~M_\odot$) and metallicities ($1-10~Z_\odot$),
and locate portions of the parameter space where mass loss via winds occurs on
a timescale shorter than the lifetime of the stars.
  Results: We find that for reasonable assumptions about stellar winds,
sufficiently massive ($8-22~M_\odot$) and metal-rich ($\sim9~Z_\odot$) stars
lose significant mass via winds and may no longer evolve to the supernovae
stage, thereby failing to enrich and increase the metallicity of their
surroundings. This suggests that a metallicity ceiling is the final state of a
closed-box system of gas and stars.


  Energy of elementary excitations and the anomalous nature of small Q phonons
in He-II are studied by using our macro-orbital microscopic theory of a system
of interacting bosons (cond-mat/0606571). It is observed that : (i) the
experimental E(Q) of He-II not only agrees with our theoretical relation $E(Q)
= \hbar^2Q^2/4mS(Q)$ but also supports an important conclusion of Price that
S(0) should have zero value for quantum fluids, and (ii) Feynman's energy of
excitations $E(Q)_{Fyn} = \hbar^2Q^2/2mS(Q)$ equals approximately to
$2E(Q)_{exp}$ even at low Q. Three problems with the Feynman's inference that
$E(Q)_{Fyn}$ has good agreement with $E(Q)_{exp}$ at low Q are identified. It
is argued that the theory can also be used to understand similar spectrum of
the BEC state of a dilute gas reported by O'Dell et al.


  The paper describes experiments with the SND detector at VEPP-2M collider,
carried out during the period from October 1995 until June 1997. The total
integrated luminosity of 6.4 pb^{-1} was collected in the energy range
2E=0.4-1.4 GeV (MHAD97 experiment), corresponding to 4*10^5 mu^+ mu^- pairs
produced. Preliminary results of the 1996 phi-meson experiment (FI96) are
presented. The total number of phi-mesons produced is 4*10^6. New data on rare
decays of phi and eta (550) mesons, in particular
  B(phi -> eta gamma) = (1.30+-0.06+-0.07)%,
  B(phi -> pi^0 pi^0 gamma) = (1.1+-0.2)*10^{-4}, (M_{pi^0 pi^0} > 800 MeV),
  B(phi -> f^0 gamma) = (4.7+-1.0)*10^{-4},
  B(phi -> eta pi^0 gamma) = (1.3+-0.5)*10^{-4},
  B(phi -> eta' gamma) < 1.7*10^{-4},
  B(phi -> 2 pi^0 ) < 6*10^{-4} were obtained.


  The interaction between ultrashort light pulses and non-absorbing materials
is dominated by Impulsive Stimulated Raman Scattering (ISRS). The description
of ISRS in the context of pump\&probe experiments is based on effective
classical models describing the interaction between the phonon and pulsed
electromagnetic fields. Here we report a theoretical description of ISRS where
we do not make any semi-classical approximation and we treat both photonic and
phononic degrees of freedom at the quantum level. The results of the quantum
model are compared with semiclassical results and validated by means of
spectrally resolved pump\&probe measurements on $\alpha$-quartz.


  Given $1\le \ell <k$ and $\delta\ge0$, let $\textbf{PM}(k,\ell,\delta)$ be
the decision problem for the existence of perfect matchings in $n$-vertex
$k$-uniform hypergraphs with minimum $\ell$-degree at least
$\delta\binom{n-\ell}{k-\ell}$. For $k\ge 3$, the decision problem in general
$k$-uniform hypergraphs, equivalently $\textbf{PM}(k,\ell,0)$, is one of Karp's
21 NP-complete problems. Moreover, for $k\ge 3$, a reduction of Szyma\'{n}ska
showed that $\textbf{PM}(k, \ell, \delta)$ is NP-complete for $\delta <
1-(1-1/k)^{k-\ell}$. A breakthrough by Keevash, Knox and Mycroft resolved this
problem for $\ell=k-1$ by showing that $\textbf{PM}(k, k-1, \delta)$ is in P
for $\delta > 1/k$. Based on their result for $\ell=k-1$, Keevash, Knox and
Mycroft conjectured that $\textbf{PM}(k, \ell, \delta)$ is in P for every
$\delta > 1-(1-1/k)^{k-\ell}$.
  In this paper it is shown that this decision problem for perfect matchings
can be reduced to the study of the minimum $\ell$-degree condition forcing the
existence of fractional perfect matchings. That is, we hopefully resolve the
"computational complexity" aspect of the problem by reducing it to a well-known
extremal problem in hypergraph theory. In particular, together with existing
results on fractional perfect matchings, this solves the conjecture of Keevash,
Knox and Mycroft for $\ell\ge 0.4k$. Moreover, we also supply an algorithm that
outputs a perfect matching, provided that one exists.


  Event cameras have the ability to capture asynchronous per-pixel brightness
changes, called "events", offering advantages over traditional frame-based
cameras for computer vision applications. Efficiently coding event data is
critical for transmission and storage, given the significant volume of events.
This paper proposes a novel double deep learning-based architecture for both
event data coding and classification, using a point cloud-based representation
for events. In this context, the conversions from events to point clouds and
back to events are key steps in the proposed solution, and therefore its impact
is evaluated in terms of compression and classification performance.
Experimental results show that it is possible to achieve a classification
performance of compressed events which is similar to one of the original
events, even after applying a lossy point cloud codec, notably the recent
learning-based JPEG Pleno Point Cloud Coding standard, with a clear rate
reduction. Experimental results also demonstrate that events coded using JPEG
PCC achieve better classification performance than those coded using the
conventional lossy MPEG Geometry-based Point Cloud Coding standard.
Furthermore, the adoption of learning-based coding offers high potential for
performing computer vision tasks in the compressed domain, which allows
skipping the decoding stage while mitigating the impact of coding artifacts.


  Responsibility-sensitive safety (RSS) is an approach to the safety of
automated driving systems (ADS). It aims to introduce mathematically formulated
safety rules, compliance with which guarantees collision avoidance as a
mathematical theorem. However, despite the emphasis on mathematical and logical
guarantees, the logical foundations and formalization of RSS are largely an
unexplored topic of study. In this paper, we present an introduction to RSS,
one that we expect will bridge between different research communities and pave
the way to a logical theory of RSS, its mathematical formalization, and
software tools of practical use.


  Let $\mathfrak{g}=\mathfrak{g}_{\bar{0}}+\mathfrak{g}_{\bar{1}}$ be a basic
Lie superalgebra, $\mathcal{W}_0$ (resp.$\mathcal{W}$) be the finite
W-(resp.super-) algebras constructed from a fixed nilpotent element in
$\mathfrak{g}_{\bar{0}}$. Based on a relation between finite W-algebra
$\mathcal{W}_0$ and W-superalgebra $\mathcal{W}$ found recently by the author
and Shu, we study the finite dimensional representations of finite
W-superalgebras in this paper. We first formulate and prove a version of
Premet's conjecture for the finite W-superalgebras from basic simple Lie
superalgebras. As in the W-algebra case, the Premet's conjecture is very close
to give a classification to the finite dimensional simple
$\mathcal{W}$-modules. In the case of $\ggg$ is Lie superalgebras of basic type
\Rmnum{1}, we prove the set of simple $\mathcal{W}$-supermodules is bijective
with that of simple $\mathcal{W}_0$-modules; presenting a triangular
decomposition to the tensor product of $\mathcal{W}$ with a Clifford algebra,
we also give an algorithm to compute the character of the finite dimensional
simple $\mathcal{W}$-supermodules with integral central character.


  Core-collapse supernovae are a useful laboratory to probe the nature of
exotic particles. If axionlike particles (ALPs) are produced in supernovae,
they can affect the transfer of energy and leave traces in observational
signatures. In this work, we present results from two-dimensional supernova
models including the effects of the production and the absorption of ALPs that
couple with photons. It is found that the additional heating induced by ALPs
can enhance the diagnostic energy of explosion, E_diag. For example, for
moderate ALP-photon coupling, we find explosion energies ~0.6*10^51 erg
compared to our reference model without ALPs of ~0.4*10^51 erg in the first
~0.5 s postbounce explored in this work. Our findings indicate that when the
coupling constant is sufficiently high, the neutrino luminosities and mean
energies are decreased because of the additional cooling of the proto-neutron
star via ALPs. The gravitational wave amplitude is also reduced because the
mass accretion on the proto-neutron star is suppressed. Although the ALP-photon
coupling can foster explodability, including enhancing the explosion energy
closer to recent observations, more long-term simulations in spatially
three-dimension are needed to draw robust conclusions


  This paper addresses a new approach to find a spectrum of information
measures for the process of digital circuit synthesis. We consider the problem
from the information engine point of view. The circuit synthesis as a whole and
different steps of the design process (an example of decision diagram is given)
are presented via such measurements as entropy, logical work and information
vitality. We also introduce new information measures to provide better
estimates of synthesis criteria. We show that the basic properties of
information engine, such as the conservation law of information flow and the
equilibrium law of information can be formulated.


  We propose the extension of the complex numbers to be the new domain where
new concepts, like negative and imaginary probabilities, can be defined. The
unit of the new space is defined as the solution of the unsolvable equation in
the complex domain: $|z|^2= z^* z = i$. The existence of the unsolvable
equation in a closed domain as complex's lead to the definition of a new type
of multiplication, for not violate the fundamental theorem of algebra. The
definition of the new space also requests the inclusion of a new mapping
operation, so the absolute value of the new extended number being real and
positive. We study the properties of the vector space like
positive-definiteness, linearity, and conjugated symmetry.


  We define the class of non-decomposable $N$-ary operations in the mixed
tensor algebra $\bigoplus\limits_{i,j=0}^\infty A_i^j$. There are higher
Jacobi-like identities for (binary) deformed matrix commutator and a 3-ary
operation which is non-decomposable into binary ones.


  This work reports an original method for the fabrication of
Metal-Isulator-Semiconductor (MIS) structures with silicon nanocrystals (Si
NCs) based active layers embedded in the insulating SiO 2 oxide, for high
performance solar cell and photodetector applications. The Si NCs are produced
via the in situ solid-state dewetting of ultra-pure amorphous
silicon-oninsulator (a-SOI) grown by solid source molecular beam epitaxy
(SSMBE). The size and density of Si NCs are precisely tuned by varying the
deposited thickness of silicon. The morphological characterization carried out
by using atomic force microscopy (AFM) and scanning electron microscopy (SEM)
shows that the Si NCs have homogeneous size with welldefined spherical shape
and densities up to ~10 12 /cm 2 (inversely proportional to the square of
nominal a-Si thickness). The structural investigations by high resolution
transmission electron microscopy (HR-TEM) show that the ultra-small Si NCs
(with mean diameter ~7 nm) are monocrystalline and free of structural defects.
The electrical measurements performed by current versus voltage (I-V) and
photocurrent spectroscopies on the Si-NCs based MIS structures prove the
efficiency of Si NCs to enhance the electrical conduction in MIS structures and
to increase (x10 times) the photocurrent (i.e. at bias voltage V =-1 V) via the
photogeneration of additional electron-hole pairs in the MIS structures. These
results evidence that the Si NCs obtained by the combination of MBE growth and
solid-state dewetting are perfectly suitable for the development of novel high
performance optoelectronic devices compatible with the CMOS technology.


  In this paper, we will use the interior functions of an hierarchical basis
for high order $BDM_p$ elements to enforce the divergence-free condition of a
magnetic field $B$ approximated by the H(div) $BDM_p$ basis. The resulting
constrained finite element method can be used to solve magnetic induction
equation in MHD equations. The proposed procedure is based on the fact that the
scalar $(p-1)$-th order polynomial space on each element can be decomposed as
an orthogonal sum of the subspace defined by the divergence of the interior
functions of the $p$-th order $BDM_p$ basis and the constant function.
Therefore, the interior functions can be used to remove element-wise all higher
order terms except the constant in the divergence error of the finite element
solution of $B$-field. The constant terms from each element can be then easily
corrected using a first order H(div) basis globally. Numerical results for a
3-D magnetic induction equation show the effectiveness of the proposed method
in enforcing divergence-free condition of the magnetic field.


  Electronic nematicity is often found in unconventional superconductors,
suggesting its relevance for electronic pairing. In the strongly hole-doped
iron-based superconductors, the symmetry channel and strength of the nematic
fluctuations, as well as the possible presence of long-range nematic order,
remain controversial. Here, we address these questions using transport
measurements under elastic strain. By decomposing the strain response into the
appropriate symmetry channels, we demonstrate the emergence of a giant in-plane
symmetric contribution, associated with the growth of both strong electronic
correlations and the sensitivity of these correlations to strain. We find
weakened remnants of the nematic fluctuations that are present at optimal
doping, but no change in the symmetry channel of nematic fluctuations with hole
doping. Furthermore, we find no evidence for a nematic-ordered state in the
AFe$_2$As$_2$(A = K, Rb, Cs) superconductors. These results revise the current
understanding of nematicity in hole-doped iron-based superconductors.


  We construct a scattering theory of weakly nonlinear thermoelectric transport
through sub-micron scale conductors. The theory incorporates the leading
nonlinear contributions in temperature and voltage biases to the charge and
heat currents. Because of the finite capacitances of sub-micron scale
conducting circuits, fundamental conservation laws such as gauge invariance and
current conservation require special care to be preserved. We do this by
extending the approach of Christen and B\"uttiker [Europhys. Lett. 35, 523
(1996)] to coupled charge and heat transport. In this way we write relations
connecting nonlinear transport coefficients in a manner similar to Mott's
relation between the linear thermopower and the linear conductance. We derive
sum rules that nonlinear transport coefficients must satisfy to preserve gauge
invariance and current conservation. We illustrate our theory by calculating
the efficiency of heat engines and the coefficient of performance of
thermoelectric refrigerators based on quantum point contacts and resonant
tunneling barriers. We identify in particular rectification effects that
increase device performance.


  We survey developments, over the last thirty years, in the theory of Shape
Preserving Approximation (SPA) by algebraic polynomials on a finite interval.
In this article, "shape" refers to (finitely many changes of) monotonicity,
convexity, or q-monotonicity of a function (for definition, see Section 4). It
is rather well known that it is possible to approximate a function by algebraic
polynomials that preserve its shape (i.e., the Weierstrass approximation
theorem is valid for SPA). At the same time, the degree of SPA is much worse
than the degree of best unconstrained approximation in some cases, and it is
"about the same" in others. Numerous results quantifying this difference in
degrees of SPA and unconstrained approximation have been obtained in recent
years, and the main purpose of this article is to provide a "bird's-eye view"
on this area, and discuss various approaches used.
  In particular, we present results on the validity and invalidity of uniform
and pointwise estimates in terms of various moduli of smoothness. We compare
various constrained and unconstrained approximation spaces as well as orders of
unconstrained and shape preserving approximation of particular functions, etc.
There are quite a few interesting phenomena and several open questions.


  It is now well established that laser plasma acceleration (LPA) is an
innovative and good candidate in the beam acceleration field. Relativistic
beams are indeed produced up to several GeV but their quality remains to be
demonstrated in the highly demanding case of Free Electron Lasers (FELs).
Several experiments already showed the feasibility of synchrotron radiation
delivery based on a LPA but free electron lasing has still to be achieved.
Since the quality of the LPA beam inside the undulator is the critical issue,
any LPA based FEL experiment requires a refined characterization of the beam
properties along the transport line and of the photon beam at the undulator
exit. This characterization relies on diagnostics which must be adapted to the
LPA specificities. We will review the electron and photon diagnostics already
used on LPAs and required for LPA based FELs, and illustrate the critical
points using recent experiments performed around the world.


  By pursuing the goal to find new variables in the COROT field-of-view we
characterised a sample of stars located in the lower part of the instability
strip. Our sample is composed of stars belonging to the disk population in the
solar neighbourhood. We found that 23% of the stars display multiperiodic light
variability up to few mmag of amplitude. uvbyBeta photometry fixed most of the
variables in the middle of the instability strip and high-resolution
spectroscopy established that they have vsin i>100 km/s. The comparison with
delta Sct stars in the whole Galaxy shows slightly different features, i.e.,
most delta Sct stars have a 0.05-mag redder (b-y)_0 index and lower vsin i
values. Additional investigation in the open cluster NGC 6633 confirms the same
incidence of variability, i.e., around 20%. The wide variety of pulsational
behaviours of delta Sct stars (including unusual objects such as a variable
beyond the blue edge or a rapidly rotating high-amplitude pulsator) makes them
very powerful asteroseismic tools to be used by COROT. Being quite common among
bright stars, delta Sct stars are suitable targets for optical observations
from space.


  Deformable image registration, estimating the spatial transformation between
different images, is an important task in medical imaging. Many previous
studies have used learning-based methods for multi-stage registration to
perform 3D image registration to improve performance. The performance of the
multi-stage approach, however, is limited by the size of the receptive field
where complex motion does not occur at a single spatial scale. We propose a new
registration network combining recursive network architecture and mutual
attention mechanism to overcome these limitations. Compared with the
state-of-the-art deep learning methods, our network based on the recursive
structure achieves the highest accuracy in lung Computed Tomography (CT) data
set (Dice score of 92\% and average surface distance of 3.8mm for lungs) and
one of the most accurate results in abdominal CT data set with 9 organs of
various sizes (Dice score of 55\% and average surface distance of 7.8mm). We
also showed that adding 3 recursive networks is sufficient to achieve the
state-of-the-art results without a significant increase in the inference time.


  This paper presents a comprehensive description of the relative effect of
optical underwater turbulence in combination with absorption and scattering.
Turbulence induced scattering is shown to cause and increase both spatial and
temporal spreading at the receiver plane. It is also demonstrated that the
relative impact of turbulence on a received signal is lower in a highly
scattering channel. Received intensity distributions are presented confirming
that fluctuations in received power from this method follow the commonly used
Log-Normal fading model. The impact of turbulence induced scattering on maximum
achievable data rate in the underwater channel is investigated.


  We examine the speed of inward traveling cooling fronts in accretion disks.
We show that their speed is determined by the rarefaction wave that precedes
them and is approximately $\alpha_F c_{F} (H/r)^q$, where $\alpha_F$ is the
dimensionless viscosity, $c_{F}$ is the sound speed, $r$ is the radial
coordinate, $H$ is the disk thickness, and all quantities are evaluated at the
cooling front. The scaling exponent $q$ lies in the interval $[0,1]$, depending
on the slope of the $(T,\Sigma)$ relation in the hot state. For a Kramer's law
opacity and $\alpha\propto (H/r)^n$, where $n$ is of order unity, we find that
$q\sim 1/2$. This supports the numerical work of Cannizzo, Chen and Livio
(1995) and their conclusion that $n\approx3/2$ is necessary to reproduce the
exponential decay of luminosity in black hole X-ray binary systems. Our results
are insensitive to the structure of the disk outside of the radius where rapid
cooling sets in. In particular, the width of the rapid cooling zone is a
consequence of the cooling front speed rather than its cause. We conclude that
the exponential luminosity decay of cooling disks is probably compatible with
the wave-driven dynamo model. It is not compatible with models with separate,
constant values of $\alpha$ for the hot and cold states.


  Generating videos from text has proven to be a significant challenge for
existing generative models. We tackle this problem by training a conditional
generative model to extract both static and dynamic information from text. This
is manifested in a hybrid framework, employing a Variational Autoencoder (VAE)
and a Generative Adversarial Network (GAN). The static features, called "gist,"
are used to sketch text-conditioned background color and object layout
structure. Dynamic features are considered by transforming input text into an
image filter. To obtain a large amount of data for training the deep-learning
model, we develop a method to automatically create a matched text-video corpus
from publicly available online videos. Experimental results show that the
proposed framework generates plausible and diverse videos, while accurately
reflecting the input text information. It significantly outperforms baseline
models that directly adapt text-to-image generation procedures to produce
videos. Performance is evaluated both visually and by adapting the inception
score used to evaluate image generation in GANs.


  We prove that the statement "there is a $k$ such that for every $f$ there is
a $k$-bounded diagonally non-recursive function relative to $f$" does not imply
weak K\"onig's lemma over $\mathrm{RCA}_0 + \mathrm{B}\Sigma^0_2$. This answers
a question posed by Simpson. A recursion-theoretic consequence is that the
classic fact that every $k$-bounded diagonally non-recursive function computes
a $2$-bounded diagonally non-recursive function may fail in the absence of
$\mathrm{I}\Sigma^0_2$.


  We consider Horndeski cosmological models, with a minisuperspace Lagrangian
linear in the field derivative, that are able to screen any vacuum energy and
material content leading to a spatially flat de Sitter vacuum fixed by the
theory itself. Furthermore, we investigate particular models with a cosmic
evolution independent of the material content and use them to understand the
general characteristics of this framework. We also consider more realistic
models, which we denote the "term-by-term" and "tripod" models, focusing
attention on cases in which the critical point is indeed an attractor solution
and the cosmological history is of particular interest.


  Ring-diagram analysis of acoustic waves observed at the photosphere can
provide a relatively robust determination of the sub-surface flows at a
particular time under a particular region. The depth of penetration of the
waves is related to the size of the region, hence the depth extent of the
measured flows is inversely proportional to the spatial resolution. Most
ring-diagram analysis has focused on regions of extent ~15{\deg} (180 Mm) or
more in order to provide reasonable mode sets for inversions. HMI data analysis
also provides a set of ring fit parameters on a scale three times smaller.
These provide flow estimates for the outer 1% (7 Mm) of the Sun only, with very
limited depth resolution, but with spatial resolution adequate to map
structures potentially associated with the belts and regions of magnetic
activity. There are a number of systematic effects affecting the determination
of flows from local helioseismic analysis of regions over different parts of
the observable disk, not all well understood. In this study we characterize
those systematic effects with higher spatial resolution, so that they may more
effectively be accounted for in mapping temporal and spatial evolution of the
flows. Leaving open the question of the mean structure of the global meridional
circulation and the differential rotation, we describe the near-surface flow
anomalies in time and latitude corresponding to the torsional oscillation
pattern in differential rotation and analogous patterns in the meridional cell
structure as observed by SDO/HMI.


  The inversion of two-dimensional NMR data is an ill-posed problem related to
the numerical computation of the inverse Laplace transform. In this paper we
present the 2DUPEN algorithm that extends the Uniform Penalty (UPEN) algorithm
[Borgia, Brown, Fantazzini, {\em Journal of Magnetic Resonance}, 1998] to
two-dimensional data. The UPEN algorithm, defined for the inversion of
one-dimensional NMR relaxation data, uses Tikhonov-like regularization and
optionally non-negativity constraints in order to implement locally adapted
regularization. In this paper, we analyze the regularization properties of this
approach. Moreover, we extend the one-dimensional UPEN algorithm to the
two-dimensional case and present an efficient implementation based on the
Newton Projection method. Without any a-priori information on the noise norm,
2DUPEN automatically computes the locally adapted regularization parameters and
the distribution of the unknown NMR parameters by using variable smoothing.
Results of numerical experiments on simulated and real data are presented in
order to illustrate the potential of the proposed method in reconstructing
peaks and flat regions with the same accuracy.


  The density of relic neutrinos is expected to be enhanced due to clustering
in our local neighbourhood at Earth. We introduce a novel analytical technique
to calculate the neutrino overdensity, based on kinetic field theory. Kinetic
field theory is a particle-based theory for cosmic structure formation and in
this work we apply it for the first time to massive neutrinos. The
gravitational interaction is expanded in a perturbation series and we take into
account the first-order contribution to the local density of relic neutrinos.
For neutrino masses that are consistent with cosmological neutrino mass bounds,
our results are in excellent agreement with state-of-the-art calculations.


  Approximate Message Passing (AMP) is an efficient iterative
parameter-estimation technique for certain high-dimensional linear systems with
non-Gaussian distributions, such as sparse systems. In AMP, a so-called Onsager
term is added to keep estimation errors approximately Gaussian. Orthogonal AMP
(OAMP) does not require this Onsager term, relying instead on an
orthogonalization procedure to keep the current errors uncorrelated with (i.e.,
orthogonal to) past errors. \LL{In this paper, we show the generality and
significance of the orthogonality in ensuring that errors are "asymptotically
independently and identically distributed Gaussian" (AIIDG).} This AIIDG
property, which is essential for the attractive performance of OAMP, holds for
separable functions. \LL{We present a simple and versatile procedure to
establish the orthogonality through Gram-Schmidt (GS) orthogonalization, which
is applicable to any prototype. We show that different AMP-type algorithms,
such as expectation propagation (EP), turbo, AMP and OAMP, can be unified under
the orthogonal principle.} The simplicity and generality of OAMP provide
efficient solutions for estimation problems beyond the classical linear models.
\LL{As an example, we study the optimization of OAMP via the GS model and GS
orthogonalization.} More related applications will be discussed in a companion
paper where new algorithms are developed for problems with multiple constraints
and multiple measurement variables.


  In this paper we present the microscopic origin of the ferromagnetism of
Fe0.25TaS2 and its finite-temperature magnetic properties. We first obtain the
band structures of Fe0.25TaS2 by the first-principles calculations and find
that both conventional and Dirac carriers coexist in metallic Fe0.25TaS2.
Accordingly, considering the spin-orbit coupling of Fe 3d ion, we derive an
effective RKKY-type Hamiltonian between Fe spins in the presence of both the
conventional parabolic-dispersion and the Dirac linear-dispersion carriers,
which contains a Heisenberg-like, an Ising-like and an XY-like term. In
addition, we obtain the ferromagnetic Curie temperature Tc by using the cluster
self-consistent field method. Our results could address not only the high
ferromagnetic Curie temperature, but also the large magnetic anisotropy in
FexTaS2.


  Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) are the
predominant modalities utilized in the field of medical imaging. Although MRI
capture the complexity of anatomical structures with greater detail than CT, it
entails a higher financial costs and requires longer image acquisition times.
In this study, we aim to train latent diffusion model for CT to MRI conversion,
replacing the commonly-used U-Net or Transformer backbone with a State-Space
Model (SSM) called Mamba that operates on latent patches. First, we noted
critical oversights in the scan scheme of most Mamba-based vision methods,
including inadequate attention to the spatial continuity of patch tokens and
the lack of consideration for their varying importance to the target task.
Secondly, extending from this insight, we introduce Diffusion Mamba (DiffMa),
employing soft masked to integrate Cross-Sequence Attention into Mamba and
conducting selective scan in a spiral manner. Lastly, extensive experiments
demonstrate impressive performance by DiffMa in medical image generation tasks,
with notable advantages in input scaling efficiency over existing benchmark
models. The code and models are available at
https://github.com/wongzbb/DiffMa-Diffusion-Mamba


  Discourse Representation Theory (DRT) is a formal account for representing
the meaning of natural language discourse. Meaning in DRT is modeled via a
Discourse Representation Structure (DRS), a meaning representation with a
model-theoretic interpretation, which is usually depicted as nested boxes. In
contrast, a directed labeled graph is a common data structure used to encode
semantics of natural language texts. The paper describes the procedure of
dressing up DRSs as directed labeled graphs to include DRT as a new framework
in the 2020 shared task on Cross-Framework and Cross-Lingual Meaning
Representation Parsing. Since one of the goals of the shared task is to
encourage unified models for several semantic graph frameworks, the conversion
procedure was biased towards making the DRT graph framework somewhat similar to
other graph-based meaning representation frameworks.


  The level of experimental precision that will be achieved with LHC Run-III
data and in the forthcoming High Luminosity stage calls for equally accurate
theoretical predictions to compare with. Here we present updated cross section
calculations for the electroweak production of SUSY particles at the LHC with
aNNLO+NNLL (approximate next-to-next-to-leading-order plus
next-to-next-to-leading-logarithmic) accuracy. Results are shown for slepton
pair production and for electroweakinos pair production in their mostly
higgsino or gaugino configuration, finding a further significant reduction of
the factorisation and renormalisation scale dependence that stabilises the
predictions to the permil level.


  Existing work in continual learning (CL) focuses on mitigating catastrophic
forgetting, i.e., model performance deterioration on past tasks when learning a
new task. However, the training efficiency of a CL system is
under-investigated, which limits the real-world application of CL systems under
resource-limited scenarios. In this work, we propose a novel framework called
Sparse Continual Learning(SparCL), which is the first study that leverages
sparsity to enable cost-effective continual learning on edge devices. SparCL
achieves both training acceleration and accuracy preservation through the
synergy of three aspects: weight sparsity, data efficiency, and gradient
sparsity. Specifically, we propose task-aware dynamic masking (TDM) to learn a
sparse network throughout the entire CL process, dynamic data removal (DDR) to
remove less informative training data, and dynamic gradient masking (DGM) to
sparsify the gradient updates. Each of them not only improves efficiency, but
also further mitigates catastrophic forgetting. SparCL consistently improves
the training efficiency of existing state-of-the-art (SOTA) CL methods by at
most 23X less training FLOPs, and, surprisingly, further improves the SOTA
accuracy by at most 1.7%. SparCL also outperforms competitive baselines
obtained from adapting SOTA sparse training methods to the CL setting in both
efficiency and accuracy. We also evaluate the effectiveness of SparCL on a real
mobile phone, further indicating the practical potential of our method.


  In this paper we present the implementation of a WebRTC gateway service that
can forward ad-hoc RTP data plane traffic from a browser on one local network
to a browser on another local network. The advantage compared to the existing
IETF STUN (RFC 5389), TURN (RFC 5766) and ICE (RFC 5245) protocols is that it
does not require a public host and port mapping for each participating local
host, and it works with more restrictive firewall policies. WebRTC implements
ICE which combines STUN and TURN probes to automatically find the best
connection between two peers who want to communicate. In corporate networks,
simple hole punching and NAT traversal techniques typically do not work, e.g.
because of symmetric NATs. Dynamic allocation of ports on an external 3rd party
relay service is also typically blocked on restricted hosts. In our use case,
doctors at hospitals can only access port 80 through the hospital firewall on
external machines, and they need to communicate with patients who are typically
behind a NAT in a local WiFi network. VPN solutions only work for staff but not
between patients and staff. Our solution solves this problem by redirecting all
WebRTC traffic through a gateway service on the local network that has a secure
tunnel established with a public gateway. The public gateway redirects traffic
from multiple concurrent streams securely between local gateway services that
connect to it. The local gateways also communicate with browsers on their local
network to mimic a direct browser-to-browser connection without having to
change the browser runtime. We have demonstrated that this technique works well
within the hospital network and arbitrary patient networks, without the need
for any individual host configuration. In our evaluation we show that the
latency overhead is 18-20 ms for each concurrent stream added to the same
gateway service.


  We study numerically transitional coherent structures in a boundary-layer
flow with homogeneous suction at the wall (the so-called asymptotic suction
boundary layer ASBL). The dynamics restricted to the laminar-turbulent
separatrix is investigated in a spanwise-extended domain that allows for robust
localisation of all edge states. We work at fixed Reynolds number and study the
edge states as a function of the streamwise period. We demonstrate the complex
spatio-temporal dynamics of these localised states, which exhibits
multistability and undergoes complex bifurcations leading from periodic to
chaotic regimes. It is argued that in all regimes the dynamics restricted to
the edge is essentially low-dimensional and non-extensive.


  The privacy concern exists when the central server has the copies of
datasets. Hence, there is a paradigm shift for the learning networks to change
from centralized in-cloud learning to distributed \mbox{on-device} learning.
Benefit from the parallel computing, the on-device learning networks have a
lower bandwidth requirement than the in-cloud learning networks. Moreover, the
on-device learning networks also have several desirable characteristics such as
privacy preserving and flexibility. However, the \mbox{on-device} learning
networks are vulnerable to the malfunctioning terminals across the networks.
The worst-case malfunctioning terminals are the Byzantine adversaries, that can
perform arbitrary harmful operations to compromise the learned model based on
the full knowledge of the networks. Hence, the design of secure learning
algorithms becomes an emerging topic in the on-device learning networks with
Byzantine adversaries. In this article, we present a comprehensive overview of
the prevalent secure learning algorithms for the two promising on-device
learning networks: Federated-Learning networks and decentralized-learning
networks. We also review several future research directions in the
\mbox{Federated-Learning} and decentralized-learning networks.


  The automatic verification of document authorships is important in various
settings. Researchers are for example judged and compared by the amount and
impact of their publications and public figures are confronted by their posts
on social media platforms. Therefore, it is important that authorship
information in frequently used web services and platforms is correct. The
question whether a given document is written by a given author is commonly
referred to as authorship verification (AV). While AV is a widely investigated
problem in general, only few works consider settings where the documents are
short and written in a rather uniform style. This makes most approaches
unpractical for online databases and knowledge graphs in the scholarly domain.
Here, authorships of scientific publications have to be verified, often with
just abstracts and titles available. To this point, we present our novel
approach LG4AV which combines language models and graph neural networks for
authorship verification. By directly feeding the available texts in a
pre-trained transformer architecture, our model does not need any hand-crafted
stylometric features that are not meaningful in scenarios where the writing
style is, at least to some extent, standardized. By the incorporation of a
graph neural network structure, our model can benefit from relations between
authors that are meaningful with respect to the verification process. For
example, scientific authors are more likely to write about topics that are
addressed by their co-authors and twitter users tend to post about the same
subjects as people they follow. We experimentally evaluate our model and study
to which extent the inclusion of co-authorships enhances verification decisions
in bibliometric environments.


  The main driven force of the electronic nematic phase in iron-based
superconductors is still under debate. Here, we report a comprehensive study on
the nematic fluctuations in a non-superconducting iron pnictide system
BaFe$_{1.9-x}$Ni$_{0.1}$Cr$_{x}$As$_{2}$ by electronic transport,
angle-resolved photoemission spectroscopy (ARPES) and inelastic neutron
scattering (INS) measurements. Previous neutron diffraction and transport
measurements suggested that the collinear antiferromagnetism persists to
$x=0.8$, with similar N\'{e}el temperature $T_N$ and structural transition
temperature $T_s$ around 32 K, but the charge carriers change from electron
type to hole type around $x=$ 0.5. In this study, we have found that the
in-plane resistivity anisotropy also highly depends on the Cr dopings and the
type of charge carriers. While ARPES measurements suggest possibly weak orbital
anisotropy onset near $T_s$ for both $x=0.05$ and $x=0.5$ compounds, INS
experiments reveal clearly different onset temperatures of low-energy spin
excitation anisotropy, which is likely related to the energy scale of spin
nematicity. These results suggest that the interplay between the local spins on
Fe atoms and the itinerant electrons on Fermi surfaces is crucial to the
nematic fluctuations of iron pnictides, where the orbital degree of freedom may
behave differently from the spin degree of freedom, and the transport
properties are intimately related to the spin dynamics.


  For a finite dimensional Frobenius cellular algebra, a sufficient and
necessary condition for a simple cell module to be projective is given. A
special case that dual bases of the cellular basis satisfying a certain
condition is also considered. The result is similar to that in symmetric case.


  We consider collision of two particles in rotating spacetimes without
horizons. If the metric coefficient responsible for rotation of spacetime is
big enough, the energy of collisions in the centre of mass frame can be as
large as one likes. This can happen in the ergoregion only. The results are
model-independent and apply both to relativistic stars and wormholes.


  We analyze entanglement swapping (ES) of partially entangled pure states with
arbitrary Schmidt rank from the perspective of quantum state discrimination. It
is shown that the standard deterministic ES protocol is related with an optimal
minimum-error strategy. In this case the amount of entanglement of the states
resulting from swapping is, in general, lower than the maximum achievable for
the quantum channels involved. In this regard, we show that the ES protocol can
be probabilistically improved resorting to optimal maximum-confidence (MC)
discrimination strategy. Additionally, we show that the success probability of
achieving entanglement above a prescribed value from standard deterministic ES
can be increased by applying sequential MC measurements.


  An edge colouring of a graph $G$ is called acyclic if it is proper and every
cycle contains at least three colours. We show that for every $\varepsilon>0$,
there exists a $g=g(\varepsilon)$ such that if $G$ has girth at least $g$ then
$G$ admits an acyclic edge colouring with at most $(1+\varepsilon)\Delta$
colours.


  For an isotropic convex body $K\subset\mathbb{R}^n$ we consider the isotropic
constant $L_{K_N}$ of the symmetric random polytope $K_N$ generated by $N$
independent random points which are distributed according to the cone
probability measure on the boundary of $K$. We show that with overwhelming
probability $L_{K_N}\leq C\sqrt{\log(2N/n)}$, where $C\in(0,\infty)$ is an
absolute constant. If $K$ is unconditional we argue that even $L_{K_N}\leq C$
with overwhelming probability. The proofs are based on concentration
inequalities for sums of sub-exponential or sub-Gaussian random variables,
respectively, and, in the unconditional case, on a new $\psi_2$-estimate for
linear functionals with respect to the cone measure in the spirit of Bobkov and
Nazarov, which might be of independent interest.


  We analyze transverse thrust in the framework of Soft Collinear Effective
Theory and obtain a factorized expression for the cross section that permits
resummation of terms enhanced in the dijet limit to arbitrary accuracy. The
factorization theorem for this hadron-collider event-shape variable involves
collinear emissions at different virtualities and suffers from a collinear
anomaly. We compute all its ingredients at the one-loop order, and show that
the two-loop input for next-to-next-to-leading logarithmic accuracy can be
extracted numerically, from existing fixed-order codes.


  Quantum correlators of pure supersymmetric Yang-Mills theories in D=3,4,6 and
10 dimensions can be reformulated via the non-linear and non-local
transformation (`Nicolai map') that maps the full functional measure of the
interacting theory to that of a free bosonic theory. As a special application
we show that for the maximally extended N=4 theory in four dimensions, and up
to order O(g^2), all known results for scalar correlators can be recovered in
this way without any use of anti-commuting variables, in terms of a purely
bosonic and ghost free functional measure for the gauge fields. This includes
in particular the dilatation operator yielding the anomalous dimensions of
composite operators. The formalism is thus competitive with more standard
perturbative techniques.


  The detection of binary neutron star mergers represents one of the most
important and complex astrophysical discoveries of the recent years. One of the
unclear aspects of the problem is the turbulent magnetic field amplification,
initially triggered by the Kelvin-Helmholtz instability at much smaller scales
than any reachable numerical resolution nowadays. Here we present numerical
simulations of the first ten milliseconds of a binary neutron star merger.
First, we confirm in detail how the simulated amplification depends on the
numerical resolution and is distributed on a broad range of scales, as expected
from turbulent MHD theory. We find that an initial large-scale magnetic field
of $10^{11}\,$G inside each star is amplified in the remnant to
root-mean-square values above $10^{16}\,$G within the first $5$ milliseconds
for our highest-resolution run. Then, we run large eddy simulations, exploring
the performance of the subgrid-scale gradient model, already tested
successfully in previous turbulent box simulations. We show that the addition
of this model is especially important in the induction equation, since it leads
to an amplification of the magnetic field comparable to a higher-resolution
run, but with a greatly reduced computational cost. In the first 10
milliseconds, there is no clear hint for an ordered, large-scale magnetic
field, which should indeed occur in longer timescales through magnetic winding
and the magneto-rotational instability.


  This paper addresses the problem of global tempo estimation in musical audio.
Given that annotating tempo is time-consuming and requires certain musical
expertise, few publicly available data sources exist to train machine learning
models for this task. Towards alleviating this issue, we propose a fully
self-supervised approach that does not rely on any human labeled data. Our
method builds on the fact that generic (music) audio embeddings already encode
a variety of properties, including information about tempo, making them easily
adaptable for downstream tasks. While recent work in self-supervised tempo
estimation aimed to learn a tempo specific representation that was subsequently
used to train a supervised classifier, we reformulate the task into the binary
classification problem of predicting whether a target track has the same or a
different tempo compared to a reference. While the former still requires
labeled training data for the final classification model, our approach uses
arbitrary unlabeled music data in combination with time-stretching for model
training as well as a small set of synthetically created reference samples for
predicting the final tempo. Evaluation of our approach in comparison with the
state-of-the-art reveals highly competitive performance when the constraint of
finding the precise tempo octave is relaxed.


  We extend an efficient homogenization procedure based on a Haydock
representation of the microscopic wave operator for the calculation of the
macroscopic dielectric response of a periodic composite to the case of an
arbitrary number of components of arbitrary composition. As a test, we apply
our numerical procedure to the calculation of the optical properties of a
Bouligand structure, made of a large number of anisotropic layers stacked on
top of each other and progresively rotated. This system consitutes a photonic
crystal with circularly polarized electromagnetic normal modes, naturally
ocurring in the cuticle of several arthropods, and which has a gap for one
polarization, which corresponds to the observation of circularly polarized
strong metallic like reflections. Our numerical procedure is validated through
its good agreement with the analytical solution for this simple chiral system.


  Following the strategy developed by the ALPHA collaboration, we present a
method to compute non-perturbatively the decay constant of a heavy-light meson
in HQET including the 1/m corrections. We start by a matching between HQET and
QCD in a small volume to determine the parameters of the effective theory
non-perturbatively. Observables in the effective theory are then evolved to
larger volumes. In two steps a large enough volume is reached to determine the
physical decay constant. Some preliminary results in the quenched approximation
are shown.


  We suggest an infrared-insensitive quark mass, defined by subtracting the
soft part of the quark self energy from the pole mass. We demonstrate the deep
relation of this definition with the static quark-antiquark potential. At
leading order in 1/m this mass coincides with the PS mass which is defined in a
completely different manner. Going beyond static limit, the small normalization
point introduces recoil corrections which are calculated here as well. Using
this mass concept and other concepts for the quark mass we calculate the cross
section of e+ e- -> t t-bar near threshold at NNLO accuracy adopting three
alternative approaches, namely (1) fixing the pole mass, (2) fixing the PS
mass, and (3) fixing the new mass which we call the PS-bar mass. We demonstrate
that perturbative predictions for the cross section become much more stable if
we use the PS or the PS-bar mass for the calculations. A careful analysis
suggests that the top quark mass can be extracted from a threshold scan at NLC
with an accuracy of about 100-200 MeV.


  A family of spherically symmetric solutions with horizon in the model with
m-component anisotropic fluid is presented. The metrics are defined on a
manifold that contains a product of n-1 Ricci-flat "internal" spaces. The
equation of state for any s-th component is defined by a vector U^s belonging
to R^{n + 1}. The solutions are governed by moduli functions H_s obeying
non-linear differential equations with certain boundary conditions imposed. A
simulation of black brane solutions in the model with antisymmetric forms is
considered. An example of solution imitating M_2-M_5 configuration (in D =11
supergravity) corresponding to Lie algebra A_2 is presented.


  We report on the investigation of coercivity changes of the
Co$_{72}$Pt$_{28}$/Co$_{81}$Ir$_{19}$ exchange-coupled composite (ECC) media
with negative soft-layer (SL) magnetocrystalline anisotropy (MA) . Our results
show that the hard-layer (HL) of our sample exhibits a columnar type
microstructure with well isolated grains and the SL with hcp-structure grows on
top of the HL with the same texture. Therefore, strong coupling of the two
layers have been realized as evidenced by the magnetic characterization.
Importantly, we observe a more effective reduction of the coercivity of the ECC
media by using SLs with negative MA when compared to the use of SLs with
positive or negligible MA. The experimental results are corroborated by
theoretical calculations.


  We present the results of our broadband spectral analysis of 42 SGR
J1550-5418 bursts simultaneously detected with the Swift/X-ray Telescope (XRT)
and the Fermi/Gamma-ray Burst Monitor (GBM), during the 2009 January active
episode of the source. The unique spectral and temporal capabilities of the XRT
Windowed Timing mode have allowed us to extend the GBM spectral coverage for
these events down to the X-ray domain (0.5-10 keV). Our earlier analysis of the
GBM data found that the SGR J1550-5418 burst spectra were described equally
well with a Comptonized model or with two blackbody functions; the two models
were statistically indistinguishable. Our new broadband (0.5 - 200 keV)
spectral fits show that, on average, the burst spectra are better described
with two blackbody functions than with the Comptonized model. Thus, our joint
XRT/GBM analysis clearly shows for the first time that the SGR J1550-5418 burst
spectra might naturally be expected to exhibit a more truly thermalized
character, such as a two-blackbody or even a multi-blackbody signal. Using the
Swift and RXTE timing ephemeris for SGR J1550-5418 we construct the
distribution of the XRT burst counts with spin phase and find that it is not
correlated with the persistent X-ray emission pulse phase from SGR J1550-5418.
These results indicate that the burst emitting sites on the neutron star need
not be co-located with hot spots emitting the bulk of the persistent X-ray
emission. Finally, we show that there is a significant pulse phase dependence
of the XRT burst counts, likely demonstrating that the surface magnetic field
of SGR J1550-5418 is not uniform over the emission zone, since it is
anticipated that regions with stronger surface magnetic field could trigger
bursts more efficiently.


  A recent conjecture of Caputo, Carlen, Lieb, and Loss, and, independently, of
the author, states that the maximum of the permanent of a matrix whose rows are
unit vectors in l_p is attained either for the identity matrix I or for a
constant multiple of the all-1 matrix J.
  The conjecture is known to be true for p = 1 (I) and for p \ge 2 (J).
  We prove the conjecture for a subinterval of (1,2), and show the conjectured
upper bound to be true within a subexponential factor (in the dimension) for
all 1 < p < 2. In fact, for p bounded away from 1, the conjectured upper bound
is true within a constant factor.
  This leads to a mild (subexponential) improvement in deterministic
approximation factor for the permanent. We present an efficient deterministic
algorithm that approximates the permanent of a nonnegative n\times n matrix
within exp{n - O(n/\log n)}.


  The age of the Internet of Things is adding an increasing number of new
devices to the Internet and is expected to have fifty billion connected units
by 2021. These form an extensive network that may have multiple points where
there is a risk of attacks that can compromise the entire system. This paper
has conducted a systematic review of security in LoRaWAN protocol specification
versions 1.0 and 1.1 by locating its vulnerabilities and determining what
measures can be taken for improvement and how they can be checked or tested.
The review identifies nineteen areas of vulnerability in the LoRaWAN protocol
and shows that the current studies focus on specification version 1.0, key
management, and authentication procedures.


  We present a method for self-consistently including the optical cavity field
into Monte Carlo-based carrier transport simulations. This approach allows for
an analysis of the actual lasing operation in quantum cascade lasers,
considering effects such as gain saturation and longitudinal mode competition.
Simulation results for a terahertz quantum cascade laser are found to be
consistent with experiment.


  We propose an experimental scheme to realize the valley-dependent gauge
fields for ultracold fermionic atoms trapped in a state-dependent square
optical lattice. Our scheme relies on two sets of Raman laser beams to engineer
the hopping between adjacent sites populated by two-component fermionic atoms.
One set of Raman beams are used to realize a staggered \pi-flux lattice, where
low energy atoms near two inequivalent Dirac points should be described by the
Dirac equation for spin-1/2 particles. Another set of laser beams with proper
Rabi frequencies are added to further modulate the atomic hopping parameters.
The hopping modulation will give rise to effective gauge potentials with
opposite signs near the two valleys, mimicking the interesting strain-induced
pseudo-gauge fields in graphene. The proposed valley-dependent gauge fields are
tunable and provide a new route to realize quantum valley Hall effects and
atomic valleytronics.