  We investigate the evolution of the galaxy stellar mass function (SMF) and
stellar mass density from redshift z=0.2 to z=1.5 of a $K_{AB}$<22-selected
sample with highly reliable photometric redshifts and over an unprecedentedly
large area. Our study is based on NIR observations carried out with WIRCam at
CFHT over the footprint of the VIPERS spectroscopic survey and benefits from
the high quality optical photometry from the CFHTLS and UV observations with
the GALEX satellite. The accuracy of our photometric redshifts is $\sigma_z$ <
0.03 and 0.05 for the bright ($i_{AB}$<22.5) and faint ($i_{AB}$>22.5) samples,
respectively. The SMF is measured with ~760,000 galaxies down to $K_s$=22 and
over an effective area of ~22.4 deg$^2$, the latter of which drastically
reduces the statistical uncertainties (i.e. Poissonian error & cosmic
variance). We point out the importance of a careful control of the photometric
calibration, whose impact becomes quickly dominant when statistical
uncertainties are reduced, which will be a major issue for future generation of
cosmological surveys with, e.g. EUCLID or LSST. By exploring the rest-frame
(NUV-r) vs (r-$K_s$) color-color diagram separating star-forming and quiescent
galaxies, (1) we find that the density of very massive log($M_*/ M_{\odot}$) >
11.5 galaxies is largely dominated by quiescent galaxies and increases by a
factor 2 from z~1 to z~0.2, which allows for additional mass assembly via dry
mergers, (2) we confirm a scenario where star formation activity is impeded
above a stellar mass log($M^*_{SF} / M_{\odot}$) = 10.64$\pm$0.01, a value that
is found to be very stable at 0.2 < z < 1.5, (3) we discuss the existence of a
main quenching channel that is followed by massive star-forming galaxies, and
finally (4) we characterise another quenching mechanism required to explain the
clear excess of low-mass quiescent galaxies observed at low redshift.


  Most heavy elements beyond the iron peak are synthesized via neutron capture
processes. The nature of the astrophysical sites of neutron capture processes
is still very unclear. In this work we explore the observational constraints of
the chemical abundances of s-process and r-process elements on the sites of
neutron-capture processes by applying Galactic chemical evolution (GCE) models
to the data from Gaia-ESO large spectroscopic stellar survey. For the
r-process, the [Eu/Fe]-[Fe/H] distribution suggests a short delay time of the
site that produces Eu. Other independent observations (e.g., NS-NS binaries),
however, suggest a significant fraction of long delayed ($>1$Gyr) neutron star
mergers (NSM). When assuming NSM as the only r-process sites, these two
observational constraints are inconsistent at above 1$\sigma$ level. Including
short delayed r-process sites like magneto-rotational supernova can resolve
this inconsistency. For the s-process, we find a weak metallicity dependence of
the [Ba/Y] ratio, which traces the s-process efficiency. Our GCE model with
up-to-date yields of AGB stars qualitatively reproduces this metallicity
dependence, but the model predicts a much higher [Ba/Y] ratio compared to the
data. This mismatch suggests that the s-process efficiency of low mass AGB
stars in the current AGB nucleosynthesis models could be overestimated.


  We provide theory for computing the lower semi-continuous convex envelope of
functionals of the type f(x) plus an l2 misfit, and discuss applications to
various non-convex optimization problems. The latter term is a data fit term
whereas f provides structural constraints on x. By minimizing the above
expression, possibly with additional constraints, we thus find a tradeoff
between matching the measured data and enforcing a particular structure on x,
such as sparsity or low rank. For these particular cases, the theory provides
alternatives to convex relaxation techniques such as l1 -minimization (for
vectors) and nuclear norm-minimization (for matrices). For functionals where
the l2 misfit includes a singular matrix and where the convex envelope usually
is not explicitly computable, we provide theory for how minimizers of
(explicitly computable) approximations of the convex envelope relate to
minimizers of the original functional. In particular, we give explicit
conditions on when the two coincide.


  Fibrosis is a common lesion in different pathologic diseases and is defined
by the excessive accumulation of collagen. Different approaches have been used
to treat different conditions characterized by fibrosis. FDA and EMA approved
collagenase to treat palmar fibromatosis, Dupuyten disease. EMA approved
additionally its use in severe Peyronie disease, but it has been used off label
in other conditions.1, 2. Approved treatment includes up to 3, in palmar
fibromatosis or up to 8, in penile fibromatosis, injections followed by finger
extension or penile modelling procedures, typically causing severe pain.
Frequently single injections are enough to treat palmar fibromatosis. 3, The
need to inject repeatedly doses of this enzyme can be originated by by the
labile nature of collagenase which exhibits a complete activity loss after
short periods of time. Herein, a novel strategy to manage this enzyme based on
the synthesis of polymeric nanocapsules which contains collagenase housed
within their matrix is presented. These nanocapsules have been engineered for
achieving a gradual release of the encapsulated enzyme for longer times which
can be up to ten days. The efficacy of these nanocapsules have been tested in
murine model of local dermal fibrosis yielding higher fibrosis reduction in
comparison with the injection of free enzyme which represent a significant
improvement over conventional therapy.


  We report the serendipitous detection of a previously unreported pulsar from
the direction of the Small Magellanic Cloud using data from the CHANDRA X-Ray
Observatory. Because of the luminosity of about 1.5x10^35 ergs/s, its near lack
of variability for more than 20 years, and its soft spectrum we propose that it
is an anomalous X-ray pulsar (AXP). Data from the ROSAT PSPC in conjunction
with the CHANDRA data give a period, P, of 5.44 s and a spin down time, Pdot/P,
of 11 ky. If this is a correct identification it will be the first
extragalactic AXP and the fastest yet discovered.


  Adversarial examples for neural network image classifiers are known to be
transferable: examples optimized to be misclassified by a source classifier are
often misclassified as well by classifiers with different architectures.
However, targeted adversarial examples -- optimized to be classified as a
chosen target class -- tend to be less transferable between architectures.
While prior research on constructing transferable targeted attacks has focused
on improving the optimization procedure, in this work we examine the role of
the source classifier. Here, we show that training the source classifier to be
"slightly robust" -- that is, robust to small-magnitude adversarial examples --
substantially improves the transferability of class-targeted and
representation-targeted adversarial attacks, even between architectures as
different as convolutional neural networks and transformers. The results we
present provide insight into the nature of adversarial examples as well as the
mechanisms underlying so-called "robust" classifiers.


  A theory of flow stress (FS), reviewing and developing our research,e.g.
arxiv:1803.08247;1908.09338, is proposed,including yield strength (YS) of PC
materials for quasi-static plastic loading for grain of average size d in range
10^{-8}-10^{-2}m. It's based on statistical model of energy spectrum
distribution in each grain of 1-mode PC sample under plastic loading,with
highest level equal to maximal dislocation energy. Found distribution of scalar
dislocation density leads to FS due to Taylor strain hardening containing usual
and anomalous HP laws for coarse and NC grains, respectively, and reaches
maximum for extreme grain size d_0 of order 10^{-8}m. Maximum undergoes shift
to region of larger grains for decreasing T and increasing strains. Coincidence
is established among theoretical and experimental data on YS for
BCC(\alpha-Fe), FCC(Cu,Al,Ni),HCP(\alpha-Ti,Zr) PC materials at T=300K.The
T-dependence of strength quantities is studied. It is shown using Al that YS
grows with decrease in T for all grains with d>3d_0,and then YS decreases in NC
region,thus determining a temperature-dimension effect (TDE).1-phase model of
PC sample is extended by including softening GB phase into 2-phase model,and
then by dispersion (un)hardening. A quasi-particle interpretation of
crystallite energy quantization is suggested.Analytic and graphic forms of HP
laws are obtained in above samples with different values of small-,large-angle
GB and constant pores.The maximum of YS and respective extremal grain size of
the samples are shifted by change of 2-nd phase.The T-dependence of YS in range
of 150-350K for Al demonstrates the validity of TDE. An enlargement of 2-nd
phase neutralizes TDE.Deformation curves for 1- and 2-mode 2-phase \alpha-Fe PC
model are constructed with Backofen-Considere fracture criterion,as compared to
experimental,1-phase model data, and strongly depend on multimodality and GB


  A cluster algorithm is presented for the simulation of the q-state Potts
models in which the number of spins is conserved in each state. The algorithm
constructs Fortuin-Kasteleyn cluster configurations from spin configurations,
in a way identical to the Swendsen-Wang algorithm; the spin assignment to these
clusters is however different, and conserves the number of spins for each
state. Compared to traditional non-local spin-exchange algorithms, the cluster
algorithm presented here suffers less from critical slowing down, and
consequently is more efficient near the critical temperature.


  In this paper we develop homogenization theory for spatiotemporally modulated
wire medium. We first solve for the modal waves that are supported by this
composite medium, we show peculiar properties such as extraordinary waves that
propagate at frequencies below the cut-off frequency of the corresponding
stationary medium. We explain how these unique solutions give rise to an
extreme Fresnel drag that exists already with weak and slow spatiotemporal
modulation. Next, we turn to derive the effective material permittivity that
corresponds to each of the first few supported modes, and write the average
fields and Poynting's vector. Nonlocality, nonreciprocity, and anisotropy due
to the spatiotemporal modulation direction, are three inherent properties of
this medium, and are clearly seen in the effective material parameters. As a
figure of merit, we also derive the effective permittivity of a plasma medium
with spatiotemporally modulated plasma frequency. This comparison is
interesting since the plasma medium can be considered as the effective medium
that is obtained by a stationary wire medium. We validate that homogenization
and spatiotemporal variation are not necessarily interchangeable operations.
And indeed, in certain parameter regimes the homogenization should be performed
directly on spatiotemporally modulated composite medium, rather than first
homogenize the stationary medium and then phenomenologically introduce the
effect of the space-time modulation.


  We obtain some new results on the topology of unary definable sets in densely
ordered Abelian groups of burden groups of burden 2. In the special case in
which the structure has dp-rank 2, we show that the existence of an infinite
definable discrete set precludes the definability of a set which is dense and
codense in an interval, or of a set which is topologically like the Cantor
middle-third set. If the structure has burden 2 and both an infinite discrete
set D and a dense-codense set X are definable, then translates of X must
witness the Independence Property. In the last section, an explicit example of
an ordered Abelian group of burden 2 is given in which both an infinite
discrete set and a dense-codense set are definable.


  In 1979, Vogan introduced a generalised $\\tau$ -invariant for characterising
primitive ideals in enveloping algebras. Via a known dictionary this translates
to an invariant of left cells in the sense of Kazhdan and Lusztig. Although it
is not a complete invariant, it is extremely useful in describing left cells.
Here, we propose a general framework for defining such invariants which also
applies to Hecke algebras with unequal parameters.


  An electrocardiogram (ECG) is vital for identifying cardiac diseases,
offering crucial insights for diagnosing heart conditions and informing
potentially life-saving treatments. However, like other types of medical data,
ECGs are subject to privacy concerns when distributed and analyzed. Diffusion
models have made significant progress in recent years, creating the possibility
for synthesizing data comparable to the real one and allowing their widespread
adoption without privacy concerns. In this paper, we use diffusion models with
structured state spaces for generating digital 10-second 12-lead ECG signals.
We propose the SSSD-ECG-nle architecture based on SSSD-ECG with a modified
conditioning mechanism and demonstrate its efficiency on downstream tasks. We
conduct quantitative and qualitative evaluations, including analyzing
convergence speed, the impact of adding positive samples, and assessment with
physicians' expert knowledge. Finally, we share the results of physician
evaluations and also make synthetic data available to ensure the
reproducibility of the experiments described.


  We study general properties of attractors for tachyonic potential chameleon
scalar-field model which possess cosmological scaling solutions. An analytic
formulation is given to obtain fixed points with a discussion on their
stability. The model predicts a dynamical equation of state parameter with
phantom crossing behavior for an accelerating universe. We constrain the
parameters of the model by best fitting with the recent data-sets from
supernovae and simulated data points for redshift drift experiment generated by
Monte Carlo simulations.


  We consider fast high-fidelity quantum control by using a shortcut to
adiabaticity (STA) technique and optimal control theory (OCT). Three specific
examples, including expansion of cold atoms from the harmonic trap, atomic
transport by moving harmonic trap, and spin dynamics in the presence of
dissipation, are explicitly detailed. Using OCT as a qualitative guide, we
demonstrate how STA protocols designed from inverse engineering method, can
approach with very high precision optimal solutions built about physical
constraints, by a proper choice of the interpolation function and with a very
reduced number of adjustable parameters.


  Deep Neural Networks (DNNs) are known to be strong predictors, but their
prediction strategies can rarely be understood. With recent advances in
Explainable Artificial Intelligence (XAI), approaches are available to explore
the reasoning behind those complex models' predictions. Among post-hoc
attribution methods, Layer-wise Relevance Propagation (LRP) shows high
performance. For deeper quantitative analysis, manual approaches exist, but
without the right tools they are unnecessarily labor intensive. In this
software paper, we introduce three software packages targeted at scientists to
explore model reasoning using attribution approaches and beyond: (1) Zennit - a
highly customizable and intuitive attribution framework implementing LRP and
related approaches in PyTorch, (2) CoRelAy - a framework to easily and quickly
construct quantitative analysis pipelines for dataset-wide analyses of
explanations, and (3) ViRelAy - a web-application to interactively explore
data, attributions, and analysis results. With this, we provide a standardized
implementation solution for XAI, to contribute towards more reproducibility in
our field.


  Soft gravitons produced by the expansion of de Sitter can be viewed as the
Nambu-Goldstone bosons of spontaneously broken asymptotic symmetries of the de
Sitter spacetime. We explicitly construct the associated charges, and show that
acting with the charges on the vacuum creates a new state equivalent to a
change in the local coordinates induced by the soft graviton. While the effect
remains unobservable within the domain of a single observer where the symmetry
is unbroken, this change is physical when comparing different asymptotic
observers, or between a transformed and un-transformed initial state,
consistent with the scale-dependent statistical anisotropies previously derived
using semiclassical relations. We then compute the overlap, $\langle0|
0'\rangle$, between the unperturbed de Sitter vacuum $|0\rangle$, and the state
$| 0'\rangle$ obtained by acting $\mathcal{N}$ times with the charge. We show
that when $\mathcal{N}\to M_p^2/H^2$ this overlap receives order one
corrections and $\langle0| 0'\rangle\to 0$, which corresponds to an infrared
perturbative breakdown after a time $t_{dS} \sim M_p^2/H^3$ has elapsed,
consistent with earlier arguments in the literature arguing for a perturbative
breakdown on this timescale. We also discuss the generalization to inflation,
and rederive the 3-point and one-loop consistency relations.


  Four-dimensional Digital Subtraction Angiography (4D DSA) is a medical
imaging technique that provides a series of 2D images captured at different
stages and angles during the process of contrast agent filling blood vessels.
It plays a significant role in the diagnosis of cerebrovascular diseases.
Improving the rendering quality and speed under sparse sampling is important
for observing the status and location of lesions. The current methods exhibit
inadequate rendering quality in sparse views and suffer from slow rendering
speed. To overcome these limitations, we propose TOGS, a Gaussian splatting
method with opacity offset over time, which can effectively improve the
rendering quality and speed of 4D DSA. We introduce an opacity offset table for
each Gaussian to model the temporal variations in the radiance of the contrast
agent. By interpolating the opacity offset table, the opacity variation of the
Gaussian at different time points can be determined. This enables us to render
the 2D DSA image at that specific moment. Additionally, we introduced a Smooth
loss term in the loss function to mitigate overfitting issues that may arise in
the model when dealing with sparse view scenarios. During the training phase,
we randomly prune Gaussians, thereby reducing the storage overhead of the
model. The experimental results demonstrate that compared to previous methods,
this model achieves state-of-the-art reconstruction quality under the same
number of training views. Additionally, it enables real-time rendering while
maintaining low storage overhead. The code will be publicly available.


  We describe a Kolyvagin system-theoretic refinement of Gross--Zagier formula
by comparing Heegner point Kolyvagin systems with Kurihara numbers when the
root number of a rational elliptic curve $E$ over an imaginary quadratic field
$K$ is $-1$. When the root number of $E$ over $K$ is 1, we first establish the
structure theorem of the $p^\infty$-Selmer group of $E$ over $K$. The
description is given by the values of certain families of quaternionic
automorphic forms, which is a part of bipartite Euler systems. By comparing
bipartite Euler systems with Kurihara numbers, we also obtain an analogous
refinement of Waldspurger formula. No low analytic rank assumption is imposed
in both refinements.
  We also prove the equivalence between the non-triviality of various
``Kolyvagin systems" and the corresponding main conjecture localized at the
augmentation ideal. As consequences, we obtain new applications of (weaker
versions of) the Heegner point main conjecture and the anticyclotomic main
conjecture to the structure of $p^\infty$-Selmer groups of elliptic curves of
arbitrary rank. In particular, the Heegner point main conjecture localized at
the augmentation ideal implies the strong rank one $p$-converse to the theorem
of Gross-Zagier and Kolyvagin.


  Atomic lattice clocks have spurred numerous ideas for tests of fundamental
physics, detection of general relativistic effects, and studies of interacting
many-body systems. On the other hand, molecular structure and dynamics offer
rich energy scales that are at the heart of new protocols in precision
measurement and quantum information science. Here we demonstrate a
fundamentally distinct type of lattice clock that is based on vibrations in
diatomic molecules, and present coherent Rabi oscillations between weakly and
deeply bound molecules that persist for 10's of milliseconds. This control is
made possible by a state-insensitive magic lattice trap that weakly couples to
molecular vibronic resonances and enhances the coherence time between molecules
and light by several orders of magnitude. The achieved quality factor
$Q=8\times10^{11}$ results from 30-Hz narrow resonances for a 25-THz clock
transition in Sr$_2$. Our technique of extended coherent manipulation is
applicable to long-term storage of quantum information in qubits based on
ultracold polar molecules, while the vibrational clock enables precise probes
of interatomic forces, tests of Newtonian gravitation at ultrashort range, and
model-independent searches for electron-to-proton mass ratio variations.


  We consider a computational model which is known as set automata.
  The set automata are one-way finite automata with an additional storage---the
set. There are two kinds of set automata---the deterministic and the
nondeterministic ones. We denote them as DSA and NSA respectively. The model
was introduced by M. Kutrib, A. Malcher, M. Wendlandt in 2014. It was shown
that DSA-languages look similar to DCFL due to their closure properties and
NSA-languages look similar to CFL due to their undecidability properties.
  In this paper we show that this similarity is natural: we prove that
languages recognizable by NSA form a rational cone, so as CFL.
  The main topic of this paper is computational complexity: we prove that
  - languages recognizable by DSA belong to P and there are P-complete
languages among them;
  - languages recognizable by NSA are in NP and there are NP-complete languages
among them;
  - the word membership problem is P-complete for DSA without epsilon-loops and
PSPACE-complete for general DSA;
  - the emptiness problem is in PSPACE for NSA and, moreover, it is
PSPACE-complete for DSA.


  Mean motion resonances (MMR) are a frequent phenomenon among extrasolar
planetary systems. Current observations indicate that many systems have planets
that are close to or inside the 2:1 MMR, when the orbital period of one of the
planets is twice the other. Analytical models to describe this particular MMR
can only be reduced to integrable approximations in a few specific cases. While
there are successful approaches to the study of this MMR in the case of very
elliptic and/or very inclined orbits using semi-analytical or semi-numerical
methods, these may not be enough to completely understand the resonant
dynamics.
  In this work, we propose to apply a well-established numerical method to
assess the global portrait of the resonant dynamics, which consists in
constructing dynamical maps. Combining these maps with the results from a
semi-analytical method, helps to better understand the underlying dynamics of
the 2:1 MMR, and to identify the behaviors that can be expected in different
regions of the phase space and for different values of the model parameters.
  We verify that the family of stable resonant equilibria bifurcate from
symmetric to asymmetric librations, depending on the mass ratio and
eccentricities of the resonant planets pair. This introduces new structures in
the phase space, that turns the classical V-shape of the MMR, in the semi-major
axis vs. eccentricity space, into a sand clock shape. We construct dynamical
maps for three extrasolar planetary systems, TOI-216, HD27894, and K2-24, and
discuss their phase space structure and their stability in the light of the
orbital fits available in the literature.


  Vehicle-to-vehicle (V2V) communications have a great potential to improve
traffic system performance. Most existing work of connected and autonomous
vehicles (CAVs) focused on adaptation to downstream traffic conditions,
neglecting the impact of CAVs' behaviors on upstream traffic flow. In this
paper, we introduce a notion of Leading Cruise Control (LCC) that retains the
basic car-following operation and explicitly considers the influence of the
CAV's actions on the vehicles behind. We first present a detailed modeling
process for LCC. Then, rigorous controllability analysis verifies the
feasibility of exploiting the CAV as a leader to actively lead the motion of
its following vehicles. Besides, the head-to-tail transfer function is derived
for LCC under adequate employment of V2V connectivity. Numerical studies
confirm the potential of LCC to strengthen the capability of CAVs in
suppressing traffic instabilities and smoothing traffic flow.


  Space solar missions such as {\it Yohkoh} and {\it RHESSI} observe the hard
X- and gamma-ray emission from energetic electrons in impulsive solar flares.
Their energization mechanism, however, is unknown. In this paper, we suggest
that the internal shocks are created in the reconnection jet and that they are
possible sites of particle acceleration. We examine how magnetic reconnection
creates the multiple shocks by performing two-dimensional resistive
magnetohydrodynamic simulations. In this paper, we use a very small grid to
resolve the diffusion region. As a result, we find that the current sheet
becomes thin due to the tearing instability, and it collapses to a Sweet-Parker
sheet. The thin sheet becomes unstable to the secondary tearing instability.
Fast reconnection starts by the onset of anomalous resistivity immediately
after the secondary tearing instability. During the bursty, time-dependent
magnetic reconnection, the secondary tearing instability continues in the
diffusion region where the anomalous resistivity is enhanced. As a result, many
weak shocks are created in the reconnection jet. This situation produces
turbulent reconnection. We suggest that multiple fast shocks are created in the
jet and that the energetic electrons can be accelerated by these shocks.


  Recent experimental results for the ratio of the branching fractions of $\bar
B \to D^{(*)}\tau \nu_\tau$ and $B\to D^{(*)} \mu \nu_\mu$ decays came as a
surprise and lead to a discussion of possibility to constraining new physics
through these modes. Here we focus on $Br(B \to D \tau \bar\nu_\tau)/Br(B \to D
\mu \bar\nu_\mu)$ and argue that the result is consistent with the Standard
Model within $2\,\sigma$ and that the test of compatibility of this ratio with
the Standard Model can be done experimentally with a minimal theory input. We
also show that these two decay channels can provide us with quite good
constraints of the new physics couplings.


  Collective cell responses to exogenous cues depend on cell-cell interactions.
In principle, these can result in enhanced sensitivity to weak and noisy
stimuli. However, this has not yet been shown experimentally, and, little is
known about how multicellular signal processing modulates single cell
sensitivity to extracellular signaling inputs, including those guiding complex
changes in the tissue form and function. Here we explored if cell-cell
communication can enhance the ability of cell ensembles to sense and respond to
weak gradients of chemotactic cues. Using a combination of experiments with
mammary epithelial cells and mathematical modeling, we find that multicellular
sensing enables detection of and response to shallow Epidermal Growth Factor
(EGF) gradients that are undetectable by single cells. However, the advantage
of this type of gradient sensing is limited by the noisiness of the signaling
relay, necessary to integrate spatially distributed ligand concentration
information. We calculate the fundamental sensory limits imposed by this
communication noise and combine them with the experimental data to estimate the
effective size of multicellular sensory groups involved in gradient sensing.
Functional experiments strongly implicated intercellular communication through
gap junctions and calcium release from intracellular stores as mediators of
collective gradient sensing. The resulting integrative analysis provides a
framework for understanding the advantages and limitations of sensory
information processing by relays of chemically coupled cells.


  There is significant observational evidence that a large fraction of galactic
centers, including those in the Milky Way and M31, host a supermassive black
hole (SMBH) embedded in a triaxial nuclear star cluster. In this work, we study
the secular orbital evolution of binaries in these environments, and
characterize the regions and morphological properties of nuclear star clusters
that lead to gravitational wave mergers and/or tidal captures. We show that
even a modest level of triaxiality in the density distribution of a cluster (an
ellipsoid with axis ratios of 0.7 and 0.95) dramatically enhances the merger
rates in the central parsecs of the Galaxy by a factor of up to ~10-30 relative
to a spherical density distribution. Moreover, we show that the merger fraction
of binaries with semi-major axes in the range 10-100 AU remains above 10% for
the entire central parsec of the cluster, reaching values close to unity at a
distance of ~0.2-0.4 pc from the SMBH. We understand this large merger
efficiency in terms of two distinct mechanisms: i) eccentricity oscillations
driven by the dominant axisymmetric part of the cluster potential that are
enhanced by the slow modulation of a binary's angular momentum from the
triaxial contribution, similar to the well-known octupole-level dynamics in
three-body systems; ii) chaotic diffusion of eccentricities arising when the
nodal precession timescale of a binary's orbit about the SMBH becomes
comparable to its characteristic secular timescale. Overall, our results
indicate that galactic centers are significantly more collisional than
previously thought, with mergers taking place up to the effective radii of
their nuclear star clusters.


  We propose an effective and flexible way to assemble finite element stiffness
and mass matrices in MATLAB. We apply this for problems discretized by edge
finite elements. Typical edge finite elements are Raviart-Thomas elements used
in discretizations of H(div) spaces and Nedelec elements in discretizations of
H(curl) spaces. We explain vectorization ideas and comment on a freely
available MATLAB code which is fast and scalable with respect to time.


  This paper presents the results of the first application of BERTopic, a
state-of-the-art topic modeling technique, to short text written in a
morphologi-cally rich language. We applied BERTopic with three multilingual
embed-ding models on two levels of text preprocessing (partial and full) to
evalu-ate its performance on partially preprocessed short text in Serbian. We
also compared it to LDA and NMF on fully preprocessed text. The experiments
were conducted on a dataset of tweets expressing hesitancy toward COVID-19
vaccination. Our results show that with adequate parameter setting, BERTopic
can yield informative topics even when applied to partially pre-processed short
text. When the same parameters are applied in both prepro-cessing scenarios,
the performance drop on partially preprocessed text is minimal. Compared to LDA
and NMF, judging by the keywords, BERTopic offers more informative topics and
gives novel insights when the number of topics is not limited. The findings of
this paper can be significant for re-searchers working with other
morphologically rich low-resource languages and short text.


  The strong coupling limit of a quantum system is in general quite
complicated, but in some cases a great simplification occurs: the strongly
coupled limit is equivalent to the weakly coupled limit of some other system.
In string theory conjectures of this type go back several years, but only in
the past year and a half has it been understood to be a general principle
applying to all string theories. This has improved our understanding of string
dynamics, including quantum gravity, in many new and sometimes surprising ways.
I describe these developments and put them in the context of the search for the
unified theory of particle physics and gravity.


  We present the Claire French Dialogue Dataset (CFDD), a resource created by
members of LINAGORA Labs in the context of the OpenLLM France initiative. CFDD
is a corpus containing roughly 160 million words from transcripts and stage
plays in French that we have assembled and publicly released in an effort to
further the development of multilingual, open source language models. This
paper describes the 24 individual corpora of which CFDD is composed and
provides links and citations to their original sources. It also provides our
proposed breakdown of the full CFDD dataset into eight categories of subcorpora
and describes the process we followed to standardize the format of the final
dataset. We conclude with a discussion of similar work and future directions.


  We compile a sample of spectral energy distribution (SED) of 12 GeV radio
galaxies (RGs), including eight FR I RGs and four FR II RGs. These SEDs can be
represented with the one-zone leptonic model. No significant unification as
expected in the unification model is found for the derived jet parameters
between FR I RGs and BL Lacertae objects (BL Lacs) and between FR II RGs and
flat spectrum radio quasars (FSRQs). However, on average FR I RGs have the
larger gamma_b (break Lorentz factor of electrons) and lower B (magnetic field
strength) than FR II RGs, analogous to the differences between BL Lacs and
FSRQs. The derived Doppler factors (delta) of RGs are on average smaller than
that of balzars, which is consistent with the unification model that RGs are
the misaligned parent populations of blazars with smaller delta. On the basis
of jet parameters from SED fits, we calculate their jet powers and the powers
carried by each component, and compare their jet compositions and radiation
efficiencies with blazars. Most of the RG jets may be dominated by particles,
like BL Lacs, not FSRQs. However, the jets of RGs with higher radiation
efficiencies tend to have higher jet magnetization. A strong anticorrelation
between synchrotron peak frequency and jet power is observed for the GeV RGs
and blazars in both the observer and co-moving frames, indicating that the
"sequence" behavior among blazars, together with the GeV RGs, may be dominated
by the jet power intrinsically.


  The two-photon-exchange (TPE) contribution in $ep\rightarrow ep\pi ^0$ with
$W=M_{\Delta}$ and small $Q^2$ is calculated and its corrections to the ratios
of electromagnetic transition form factors $R_{EM} =
E_{1+}^{(3/2)}/M_{1+}^{(3/2)} $ and $R_{SM} = S_{1+}^{(3/2)}/M_{1+}^{(3/2)}$,
are analysed. A simple hadronic model is used to estimate the TPE amplitude.
Two phenomenological models, MAID2007 and SAID, are used to approximate the
full $ep\rightarrow ep\pi ^0$ cross sections which contain both the TPE and the
one-photon-exchange (OPE) contributions. The genuine the OPE amplitude is then
extracted from an integral equation by iteration. We find that the TPE
contribution is not sensitive to whether MAID or SAID is used as input in the
region with $Q^2<2$ GeV$^2$.
  It gives small correction to $R_{EM}$ while for $R_{SM}$, the correction is
about -10\% at small $\epsilon$ and about $1\%$ at large $\epsilon$ for
$Q^2\approx2.5$ GeV$^2$. The large correction from TPE at small $\epsilon$ must
be included in the analysis to get a reliable extraction of $R_{SM}$.


  The goal of this note is to present a simple mathematical model with two
parameters for the number of deaths due to the corona (COVID-19) virus. The
model only requires basic knowledge in differential calculus, and can also be
understood by pupils attending secondary school. The model can easily be
implemented on a computer, and we will illustrate it on the basis of case
studies for different countries.


  Using a sample of face-on star-forming galaxies selected from the Sloan
Digital Sky Survey, we statistically derive the typical optical depth
$\tau_{\rm{cl}}$ of individual HII regions based on the ``Chocolate Chip
Cookie" model of Lu2022. By binning galaxies into stellar mass and gas-phase
metallicity bins and interpreting $\tau_{\rm{cl}}$ as the dust to gas ratio
(DGR) of HII regions, we further investigate the correlations among DGR and
stellar mass, gas-phase metallicity respectively. We find that DGR increases
monotonically with the stellar mass of galaxies. At a given stellar mass, DGR
shows a linear correlation with the gas-phase metallicity, which implies a
constant dust to metal ratio (DTM) of galaxies at a given stellar mass. These
results adequately indicate that the DTM of galaxies is simply a function of
their stellar masses. In terms of gas-phase metallicity, because of the
mass-metalliciy relation, DTM increases with increasing metallicity with a
power-law index 1.45 in the low metallicity region, while remains constant at
the high metallicity end.


  We have investigated clean and As-covered zinc-blende GaN (001) surfaces,
employing first-principles total-energy calculations. For clean GaN surfaces
our results reveal a novel surface structure very different from the
well-established dimer structures commonly observed on polar III-V (001)
surfaces: The energetically most stable surface is achieved by a Peierls
distortion of the truncated (1x1) surface rather than through addition or
removal of atoms. This surface exhibits a (1x4) reconstruction consisting of
linear Ga tetramers. Furthermore, we find that a submonolayer of arsenic
significantly lowers the surface energy indicating that As may be a good
surfactant. Analyzing surface energies and band structures we identify the
mechanisms which govern these unusual structures and discuss how they might
affect growth properties.


  We show the existence of weak solutions in the extended sense of the Cauchy
problem for the cubic nonlinear Schr\"odinger equation in the modulation space
$M_{p,q}^{s}(\mathbb R)$ where $1\leq q\leq2$, $2\leq p<\frac{10q'}{q'+6}$ and
$s\geq0$. Moreover, for either $1\leq q\leq\frac32, s\geq0$ and $2\leq p\leq 3$
or $\frac32<q\leq\frac{18}{11}, s>\frac23-\frac1{q}$ and $2\leq p\leq 3$ or
$\frac{18}{11}<q\leq2, s>\frac23-\frac1{q}$ and $2\leq p<\frac{10q'}{q'+6}$ we
show that the Cauchy problem is unconditionally wellposed in
$M_{p,q}^{s}(\mathbb R).$ This improves \cite{NP}, where the case $p=2$ was
considered and the differentiation by parts technique was introduced to a
problem with continuous Fourier variable. Here the same technique is used, but
more delicate estimates are necessary for $p\neq2$.


  Computing properties of molecular systems rely on estimating expectations of
the (unnormalized) Boltzmann distribution. Molecular dynamics (MD) is a broadly
adopted technique to approximate such quantities. However, stable simulations
rely on very small integration time-steps ($10^{-15}\,\mathrm{s}$), whereas
convergence of some moments, e.g. binding free energy or rates, might rely on
sampling processes on time-scales as long as $10^{-1}\, \mathrm{s}$, and these
simulations must be repeated for every molecular system independently. Here, we
present Implict Transfer Operator (ITO) Learning, a framework to learn
surrogates of the simulation process with multiple time-resolutions. We
implement ITO with denoising diffusion probabilistic models with a new SE(3)
equivariant architecture and show the resulting models can generate
self-consistent stochastic dynamics across multiple time-scales, even when the
system is only partially observed. Finally, we present a coarse-grained
CG-SE3-ITO model which can quantitatively model all-atom molecular dynamics
using only coarse molecular representations. As such, ITO provides an important
step towards multiple time- and space-resolution acceleration of MD. Code is
available at
\href{https://github.com/olsson-group/ito}{https://github.com/olsson-group/ito}.


  Theory of spin-orbit coupling in bilayer graphene is presented. The
electronic band structure of the AB bilayer in the presence of spin-orbit
coupling and a transverse electric field is calculated from first-principles
using the linearized augmented plane wave method implemented in the WIEN2k
code. The first-principles results around the K points are fitted to a
tight-binding model. The main conclusion is that the spin-orbit effects in
bilayer graphene derive essentially from the single-layer spin-orbit coupling
which comes almost solely from the d orbitals. The intrinsic spin-orbit
splitting (anticrossing) around the K points is about 24\mu eV for the
low-energy valence and conduction bands, which are closest to the Fermi level,
similarly as in the single layer graphene. An applied transverse electric field
breaks space inversion symmetry and leads to an extrinsic (also called
Bychkov-Rashba) spin-orbit splitting. This splitting is usually linearly
proportional to the electric field. The peculiarity of graphene bilayer is that
the low-energy bands remain split by 24\mu eV independently of the applied
external field. The electric field, instead, opens a semiconducting band gap
separating these low-energy bands. The remaining two high-energy bands are
spin-split in proportion to the electric field; the proportionality coefficient
is given by the second intrinsic spin-orbit coupling, whose value is 20\mu eV.
All the band-structure effects and their spin splittings can be explained by
our tight-binding model, in which the spin-orbit Hamiltonian is derived from
symmetry considerations. The magnitudes of intra- and interlayer
couplings---their values are similar to the single-layer graphene ones---are
determined by fitting to first-principles results.


  Theoretical studies of a planar tunnel junction between two superconductors
with antisymmetric spin-orbit coupling are presented. The half-space Green's
function for such a superconductor is determined. This is then used to derive
expressions for the dissipative current and the Josephson current of the
junction. Numerical results are presented in the case of the Rashba spin-orbit
coupling, relevant to the much studied compound CePt$_3$Si. Current-voltage
diagrams, differential conductance and the critical Josephson current are
presented for different crystallographic orientations and different weights of
singlet and triplet components of the pairing state. The main conclusion is
that Josephson junctions with different crystallographic orientations may
provide a direct connection between unconventional pairing in superconductors
of this kind and the absence of inversion symmetry in the crystal.


  Poor diet quality is a key modifiable risk factor for hypertension and
disproportionately impacts low-income women. \sw{Analyzing diet-driven
hypertensive outcomes in this demographic is challenging due to the complexity
of dietary data and selection bias when the data come from surveys, a main data
source for understanding diet-disease relationships in understudied
populations. Supervised Bayesian model-based clustering methods summarize
dietary data into latent patterns that holistically capture relationships among
foods and a known health outcome but do not sufficiently account for complex
survey design. This leads to biased estimation and inference and lack of
generalizability of the patterns}. To address this, we propose a supervised
weighted overfitted latent class analysis (SWOLCA) based on a Bayesian
pseudo-likelihood approach that integrates sampling weights into an
exposure-outcome model for discrete data. Our model adjusts for stratification,
clustering, and informative sampling, and handles modifying effects via
interaction terms within a Markov chain Monte Carlo Gibbs sampling algorithm.
Simulation studies confirm that the SWOLCA model exhibits good performance in
terms of bias, precision, and coverage. Using data from the National Health and
Nutrition Examination Survey (2015-2018), we demonstrate the utility of our
model by characterizing dietary patterns associated with hypertensive outcomes
among low-income women in the United States.


  We summarize and discuss recent work (Fregeau 2007) that presents the
confluence of three results suggesting that most Galactic globular clusters are
still in the process of core contraction, and have not yet reached the thermal
equilibrium phase driven by binary scattering interactions: that 1) the three
clusters that appear to be overabundant in X-ray binaries per unit encounter
frequency are observationally classified as "core-collapsed," 2) recent
numerical simulations of cluster evolution with primordial binaries show that
structural parameters of clusters in the binary-burning phase agree only with
"core-collapsed" clusters, and 3) a cluster in the binary-burning phase for the
last few Gyr should have about 5 times more dynamically formed X-ray sources
than if it were in the core contraction phase for the same time.


  Current rapid changes in climate increase the urgency to change energy
production and consumption management, to reduce carbon and other green-house
gas production. In this context, the French electricity network management
company RTE (R{\'e}seau de Transport d'{\'E}lectricit{\'e}) has recently
published the results of an extensive study outlining various scenarios for
tomorrow's French power management. We propose a challenge that will test the
viability of such a scenario. The goal is to control electricity transportation
in power networks, while pursuing multiple objectives: balancing production and
consumption, minimizing energetic losses, and keeping people and equipment safe
and particularly avoiding catastrophic failures. While the importance of the
application provides a goal in itself, this challenge also aims to push the
state-of-the-art in a branch of Artificial Intelligence (AI) called
Reinforcement Learning (RL), which offers new possibilities to tackle control
problems. In particular, various aspects of the combination of Deep Learning
and RL called Deep Reinforcement Learning remain to be harnessed in this
application domain. This challenge belongs to a series started in 2019 under
the name "Learning to run a power network" (L2RPN). In this new edition, we
introduce new more realistic scenarios proposed by RTE to reach carbon
neutrality by 2050, retiring fossil fuel electricity production, increasing
proportions of renewable and nuclear energy and introducing batteries.
Furthermore, we provide a baseline using state-of-the-art reinforcement
learning algorithm to stimulate the future participants.


  Long range quantum communication and quantum information processing require
the development of light-matter interfaces for distributed quantum networks.
Even though photons are ideal candidates for network links to transfer quantum
information, the system of choice for the realization of quantum nodes has not
been identified yet. Ideally, one strives for a hybrid network architecture,
which will consist of different quantum systems, combining the strengths of
each system. However, interfacing different quantum systems via photonic
channels remains a major challenge because a detailed understanding of the
underlying light-matter interaction is missing. Here, we show the coherent
manipulation of single photons generated on-demand from a semiconductor quantum
dot using a rubidium vapor quantum memory, forming a hybrid quantum network. We
demonstrate the engineering of the photons' temporal wave function using
four-level atoms and the creation of a new type of electromagnetic induced
transparency for quantum dot photons on resonance with rubidium transitions.
Given the short lifetime of our quantum dot transition the observed dynamics
cannot be explained in the established steady-state picture. Our results play a
pivotal role in understanding quantum light-matter interactions at short time
scales. These findings demonstrate a fundamental active node to construct
future large-scale hybrid quantum networks.


  The injection, propagation and arrival of solar energetic particles (SEPs)
during eruptive solar events is an important and current research topic of
heliospheric physics. During the largest solar events, particles may have
energies up to a few GeVs and sometimes even trigger ground-level enhancements
(GLEs) at Earth. We study the first GLE-event of solar cycle 24, from 17th May
2012, using data from multiple spacecraft (SOHO, GOES, MSL, STEREO-A, STEREO-B
and MESSENGER). These spacecraft are located throughout the inner heliosphere,
at heliocentric distances between 0.34 and 1.5 astronomical units (au),
covering nearly the whole range of heliospheric longitudes. We present and
investigate sub-GeV proton time profiles for the event at several energy
channels, obtained via different instruments aboard the above spacecraft. We
investigate issues due to magnetic connectivity, and present results of
three-dimensional SEP propagation simulations. We gather virtual time profiles
and perform qualitative and quantitative comparisons with observations,
assessing longitudinal injection and transport effects as well as peak
intensities. We distinguish different time profile shapes for well-connected
and weakly connected observers, and find our onset time analysis to agree with
this distinction. At select observers, we identify an additional low-energy
component of Energetic Storm Particles (ESPs). Using well-connected observers
for normalisation, our simulations are able to accurately recreate both time
profile shapes and peak intensities at multiple observer locations. This
synergetic approach combining numerical modeling with multi-spacecraft
observations is crucial for understanding the propagation of SEPs within the
interplanetary magnetic field. Our novel analysis provides valuable proof of
the ability to simulate SEP propagation throughout the inner heliosphere, at a
wide range of longitudes.


  Constantin and Saut showed in 1988 that solutions of the Cauchy problem for
general dispersive equations $$
  w_t +iP(D)w=0,\quad w(x,0)=q (x), \quad x\in \mathbb{R}^n, \ t\in \mathbb{R}
, $$ enjoy the local smoothing property $$ q\in H^s (\R ^n) \implies w\in L^2
\Big (-T,T; H^{s+\frac{m-1}{2}}_{loc} \left (\R^n\right )\Big ) , $$ where $m$
is the order of the pseudo-differential operator $P(D)$. This property, now
called local Kato smoothing, was first discovered by Kato for the KdV equation
and implicitly shown later by Sj\"olin for the linear Schr\"odinger equation.
In this paper, we show that the local Kato smoothing property possessed by
solutions general dispersive equations in the 1D case is sharp, meaning that
there exist initial data $q\in H^s \left (\R \right )$ such that the
corresponding solution $w$ does not belong to the space $ L^2 \Big (-T,T;
H^{s+\frac{m-1}{2} +\epsilon}_{loc} \left (\R\right )\Big )$ for any $\epsilon
>0$.


  We continue our investigation of the 4d effective field theory for closed
string axions in Type II compactifications with D-branes. The inclusion of
St\"uckelberg couplings for the axions requires the presence of chiral fermions
at D-brane intersections, whose interactions at strong non-Abelian gauge
coupling induce mass terms for the axions and scalar chiral condensate
excitations, dubbed infladrons. The set-up allows for a realization of
natural-like inflation with a closed string axion as inflaton and a flattened
scalar potential due to the back-reaction of the more massive infladrons. We
further point out that this large field inflationary model is not compromised
by axionic wormhole corrections.


  A major challenge for ferroelectric devices is the depolarization field,
which competes with and often destroys long-range polar order in the limit of
ultrathin films. Recent theoretical predictions suggest a new class of
materials, termed hyperferroelectics, that should be robust against the
depolarization field and enable ferroelectricity down to the monolayer limit.
Here we demonstrate the epitaxial growth of hexagonal LiZnSb, one of the
hyperferroelectric candidate materials, by molecular-beam epitaxy on GaSb
(111)B substrates. Due to the high volatility of all three atomic species, we
find that LiZnSb can be grown in an adsorption-controlled window, using an
excess zinc flux. Within this window, the desired polar hexagonal phase is
stabilized with respect to a competing cubic polymorph, as revealed by X-ray
diffraction and transmission electron microscopy measurements. First-principles
calculations show that for moderate amounts of epitaxial strain and moderate
concentrations of Li vacancies, the cubic LiZnSb phase is lower in formation
energy than the hexagonal phase, but only by a few meV per formula unit.
Therefore we suggest that kinetics plays a role in stabilizing the desired
hexagonal phase at low temperatures. Our results provide a path towards
experimentally demonstrating ferroelectricity and hyperferroelectricity in a
new class of ternary intermetallic compounds.


  Generalized zero shot learning (GZSL) is still a technical challenge of deep
learning as it has to recognize both source and target classes without data
from target classes. To preserve the semantic relation between source and
target classes when only trained with data from source classes, we address the
quantification of the knowledge transfer and semantic relation from an
information-theoretic viewpoint. To this end, we follow the prototypical model
and format the variables of concern as a probability vector. Leveraging on the
proposed probability vector representation, the information measurement such as
mutual information and entropy, can be effectively evaluated with simple closed
forms. We discuss the choice of common embedding space and distance function
when using the prototypical model. Then We propose three information-theoretic
loss functions for deterministic GZSL model: a mutual information loss to
bridge seen data and target classes; an uncertainty-aware entropy constraint
loss to prevent overfitting when using seen data to learn the embedding of
target classes; a semantic preserving cross entropy loss to preserve the
semantic relation when mapping the semantic representations to the common
space. Simulation shows that, as a deterministic model, our proposed method
obtains state of the art results on GZSL benchmark datasets. We achieve 21%-64%
improvements over the baseline model -- deep calibration network (DCN) and for
the first time demonstrate a deterministic model can perform as well as
generative ones. Moreover, our proposed model is compatible with generative
models. Simulation studies show that by incorporating with f-CLSWGAN, we obtain
comparable results compared with advanced generative models.


  The dynamic of a classical system can be expressed by means of Poisson
brackets. In this paper we generalize the relation between the usual non
covariant Hamiltonian and the Poisson brackets to a covariant Hamiltonian and
new brackets in the frame of the Minkowski space. These brackets can be related
to those used by Feynman in his derivation of Maxwell's equations. The case of
curved space is also considered with the introduction of Christoffel symbols,
covariant derivatives, and curvature tensors.


  We consider the problem of making efficient use of heterogeneous training
data in neural machine translation (NMT). Specifically, given a training
dataset with a sentence-level feature such as noise, we seek an optimal
curriculum, or order for presenting examples to the system during training. Our
curriculum framework allows examples to appear an arbitrary number of times,
and thus generalizes data weighting, filtering, and fine-tuning schemes. Rather
than relying on prior knowledge to design a curriculum, we use reinforcement
learning to learn one automatically, jointly with the NMT system, in the course
of a single training run. We show that this approach can beat uniform and
filtering baselines on Paracrawl and WMT English-to-French datasets by up to
+3.4 BLEU, and match the performance of a hand-designed, state-of-the-art
curriculum.


This paper has been withdrawn by the author due to crucial errors.


  A line packing is optimal if its coherence is as small as possible. Most
interesting examples of optimal line packings are achieving equality in some of
the known lower bounds for coherence. In this paper two infinite families of
real and complex biangular line packings are presented. New packings achieve
equality in the real or complex second Levenshtein bound respectively. Both
infinite families are constructed by analyzing well known representations of
the finite groups SL$(2,\mathbb{F}_q)$. Until now the only known infinite
familes meeting the second Levenshtein bounds were related to the maximal sets
of mutually unbiased bases (MUB). Similarly to the line packings related to the
maximal sets of MUBs, the line packings presented here are related to the
maximal sets of mutually unbiased weighing matrices. Another similarity is that
the new packings are projective 2-designs. The latter property together with
sufficiently large cardinalities of the new packings implies some improvement
on largest known cardinalities of real and complex biangular tight frames.


  The wave propagation problem on a taut cable resting on a bilinear substrate
is investigated, without and with a distribute transversal load. The piecewise
nature of the problem offers a sufficiently simple kind of nonlinearity as to
permit a closed form solution both for the wave phase velocity and the wave
form. We show that the solution depends only on the ratio between the two soil
stiffnesses, and that no waves propagate if one side of the substrate is rigid.
Some numerical simulations, based on a finite difference method, are performed
to confirm the analytical findings. The stability of the proposed waves is
discussed analytically and numerically.


  Machine Learning (ML) models are very effective in many learning tasks, due
to the capability to extract meaningful information from large data sets.
Nevertheless, there are learning problems that cannot be easily solved relying
on pure data, e.g. scarce data or very complex functions to be approximated.
Fortunately, in many contexts domain knowledge is explicitly available and can
be used to train better ML models. This paper studies the improvements that can
be obtained by integrating prior knowledge when dealing with a non-trivial
learning task, namely precision tuning of transprecision computing
applications. The domain information is injected in the ML models in different
ways: I) additional features, II) ad-hoc graph-based network topology, III)
regularization schemes. The results clearly show that ML models exploiting
problem-specific information outperform the purely data-driven ones, with an
average accuracy improvement around 38%.


  Let $H_V=-\Delta +V$ be a Schr\"odinger operator on an arbitrary open set
$\Omega$ of $\mathbb R^d$, where $d \geq 3$, and $\Delta$ is the Dirichlet
Laplacian and the potential $V$ belongs to the Kato class on $\Omega$. The
purpose of this paper is to show $L^p$-boundedness of an operator
$\varphi(H_V)$ for any rapidly decreasing function $\varphi$ on $\mathbb R$.
$\varphi(H_V)$ is defined by the spectral theorem. As a by-product,
$L^p$-$L^q$-estimates for $\varphi(H_V)$ are also obtained.


  The exact N-particle ground state wave function for a one-dimensional
condensate of hard core bosons in a harmonic trap is employed to obtain
accurate numerical results for the one-particle density matrix, occupation
number distribution of the natural orbitals, and momentum distribution. Our
results show that the occupation of the lowest orbital varies as N^{0.59}, in
contrast to N^{0.5} for a spatially uniform system, and N for a true BEC.


  We present a systematic methodology for the reformulation of a broad class of
three-dimensional (3D) piezoelectric problems into a two-dimensional (2D)
mathematical form. The sole underlying hypothesis is that the system geometry
and material properties as well as the applied loads (forces and charges) and
boundary conditions are translationally invariant along some direction. This
class of problems is commonly denoted here as the generalized plane
piezoelectric (GPP) problem. The first advantage of the generalized plane
problems is that they are more manageable from both analytical and
computational points of view. Moreover, they are flexible enough to accommodate
any geometric cross section, crystal class symmetry, axis orientation and a
wide range of boundary conditions. As an illustration we present numerical
simulation of indefinite lattice-mismatched core-shell nanowires made of
diamond Ge/Si and zincblende piezoelectric InN/GaN materials. The remarkable
agreement with exact 3D simulations of finite versions of those systems reveal
the GPP approach as a reliable procedure to study accurately and with moderate
computing resources the strain and electric field distribution in elongated
piezoelectric systems.


  Based on an argument for the noncommutativity of momenta in noncommutative
directions, we arrive at a generalization of the ${\cal N}=1$ super $E^2$
algebra associated to the deformation of translations in a noncommutative
Euclidean plane. The algebra is obtained using appropriate representaions of
its generators on the space of superfields in a $D=2, {\cal N}=1$
``noncommutative superspace.'' We find that the (anti)commutators between
several (super)translation generators are no longer vanishing, but involve a
new set of generators which together with the (super)translation and rotation
generators form a consistent closed algebra. We then analyze the spectrum of
this algebra in order to obtain its fundamental and adjoint representations.


  Spontaneous scalarization is an interesting mechanism for modification of
gravity by nonminimal coupling of a scalar field to matter or curvature
invariants in the context of scalar-tensor theories, and its onset is signaled
by linear instability of the scalar field around the corresponding general
relativity solution. We thus perform the linear stability analysis of the
scalar field about general relativity solutions and highlight a crucial
difference between a spherically symmetric profile and a planar symmetric
profile. We clarify that the critical value for the instability is sensitive to
the morphology and that the spontaneous scalarization occurs much more easily
with the planar symmetric shape than with the spherically symmetric shape.


  Let X be a smooth proper curve over a finite field of characteristic p. We
prove a product formula for p-adic epsilon factors of arithmetic D-modules on
X. In particular we deduce the analogous formula for overconvergent
F-isocrystals, which was conjectured previously. The p-adic product formula is
the equivalent in rigid cohomology of the Deligne-Laumon formula for epsilon
factors in l-adic \'etale cohomology (for a prime l different from p). One of
the main tools in the proof of this p-adic formula is a theorem of regular
stationary phase for arithmetic D-modules that we prove by microlocal
techniques.


  Let $\Sigma_{g,n}$ be an orientable surface of genus $g$ with $n$ punctures.
We study actions of the mapping class group of $\Sigma_{g,n}$ via
Hodge-theoretic and arithmetic techniques. We show that if $$\rho:
\pi_1(\Sigma_{g,n})\to GL_r(\mathbb{C})$$ is a representation whose conjugacy
class has finite orbit under the mapping class group, and $r<\sqrt{g+1}$, then
$\rho$ has finite image. This answers questions of Junho Peter Whang and Mark
Kisin. We give applications of our methods to the Putman-Wieland conjecture,
the Fontaine-Mazur conjecture, and a question of Esnault-Kerz.
  The proofs rely on non-abelian Hodge theory, our earlier work on
semistability of isomonodromic deformations, and recent work of
Esnault-Groechenig and Klevdal-Patrikis on Simpson's integrality conjecture for
cohomologically rigid local systems.


  We present results for the equation of state for pure SU(3) gauge theory
obtained on anisotropic lattices with the anisotropy $\xi \equiv a_s/a_t = 2$.
The pressure and energy density are calculated on $N_t / \xi = 4, 5$ and 6
lattices with the integral method. They are found to satisfy the leading
$1/N_t^2$ scaling from our coarsest lattice $N_t/\xi=4$. This enables us to
carry out well controlled continuum extrapolations. We find that the pressure
and energy density agree with those obtained using the isotropic plaquette
action, but have smaller and more reliable errors.


  Galactic bulges are central to understanding galaxy formation and evolution.
Here we report on recent studies using micro-lensing events to obtain spectra
of high resolution and moderately high signal-to-noise ratios of dwarf stars in
the Galactic bulge. Normally this is not feasible for the faint turn-off stars
in the Galactic bulge, but micro-lensing offers this possibility. Elemental
abundance trends in the Galactic bulge as traced by dwarf stars are very
similar to those seen for dwarf stars in the solar neighbourhood. We discuss
the implications of the ages and metallicity distribution function derived for
the micro-lensed dwarf stars in the Galactic bulge.


  Here we aim to show that the ratio of the momentum spectra of $K^{+}$ at
small transverse momentum measured for symmetric systems of different sizes can
be such an observable.


  Several refactorings performed while evolving software features aim to
improve internal quality attributes like cohesion and complexity. Indeed,
internal attributes can become critical if their measurements assume anomalous
values. Yet, current knowledge is scarce on how developers perceive the
relevance of critical internal attributes while evolving features. This
qualitative study investigates the developers' perception of the relevance of
critical internal attributes when evolving features. We target six class-level
critical attributes: low cohesion, high complexity, high coupling, large
hierarchy depth, large hierarchy breadth, and large size. We performed two
industrial case studies based on online focus group sessions. Developers
discussed how much (and why) critical attributes are relevant when adding or
enhancing features. We assessed the relevance of critical attributes
individually and relatively, the reasons behind the relevance of each critical
attribute, and the interrelations of critical attributes. Low cohesion and high
complexity were perceived as very relevant because they often make evolving
features hard while tracking failures and adding features. The other critical
attributes were perceived as less relevant when reusing code or adopting design
patterns. An example of perceived interrelation is high complexity leading to
high coupling.


  In practice functional data are sampled on a discrete set of observation
points and often susceptible to noise. We consider in this paper the setting
where such data are used as explanatory variables in a regression problem. If
the primary goal is prediction, we show that the gain by embedding the problem
into a scalar-on-function regression is limited. Instead we impose a factor
model on the predictors and suggest regressing the response on an appropriate
number of factor scores. This approach is shown to be consistent under mild
technical assumptions, numerically efficient and gives good practical
performance in both simulations as well as real data settings.


  We study Wick-rotations of left-invariant metrics on Lie groups, using
results from real GIT (\cite{1}, \cite{2}, \cite{3}). An invariant for
Wick-rotation of Lie groups is given, and we describe when a pseudo-Riemannian
Lie group can be Wick-rotated to a Riemannian Lie group. We also prove a
general version (for general Lie algebras) of $\acute{E}$. Cartan's result,
namely the existence and conjugacy of Cartan involutions.


  Preserving data analyses produced by the collaborations at LHC in a
parametrized fashion is crucial in order to maintain reproducibility and
re-usability. We argue for a declarative description in terms of individual
processing steps - packtivities - linked through a dynamic directed acyclic
graph (DAG) and present an initial set of JSON schemas for such a description
and an implementation - yadage - capable of executing workflows of analysis
preserved via Linux containers.


  Gamma-ray bursts categorically produce broadband afterglow emission, but in
some cases, emission in the optical band is dimmer than expected based on the
contemporaneously observed X-ray flux. This phenomenon, aptly dubbed "optical
darkness", has been studied extensively in long GRBs (associated with the
explosive deaths of massive stars), with possible explanations ranging from
host environment extinction to high redshift to possibly unique emission
mechanisms. However, investigations into optical darkness in short GRBs
(associated with the mergers of compact object binaries) have thus far been
limited. This work implements a procedure for determining the darkness of GRBs
based on spectral indices calculated using temporally-matched Swift-XRT data
and optical follow-up observations; presents a complete and up-to-date catalog
of known short GRBs that exhibit optical darkness; and outlines some of the
possible explanations for optically dark short GRBs. In the process of this
analysis, we developed versatile and scalable data processing code that
facilitates reproducibility and reuse of our pipeline. These analysis tools and
resulting complete sample of dark short GRBs enable a systematic statistical
study of the phenomenon and its origins, and reveal that optical darkness is
indeed quite rare in short GRBs, and highly dependent on observing response
time and observational effects.


  Internet of Things (IoT) is emerging as a significant technology in shaping
the future by connecting physical devices or things with internet. It also
presents various opportunities for intersection of other technological trends
which can allow it to become even more intelligent and efficient. In this paper
we focus our attention on the integration of Intelligent Conversational
Software Agents or Chatbots with IoT. Literature surveys have looked into
various applications, features, underlying technologies and known challenges of
IoT. On the other hand, Chatbots are being adopted in greater numbers due to
major strides in development of platforms and frameworks. The novelty of this
paper lies in the specific integration of Chatbots in the IoT scenario. We
analyzed the shortcomings of existing IoT systems and put forward ways to
tackle them by incorporating chatbots. A general architecture is proposed for
implementing such a system, as well as platforms and frameworks, both
commercial and open source, which allow for implementation of such systems.
Identification of the newer challenges and possible future directions with this
new integration, have also been addressed.


  Fraud in healthcare is widespread, as doctors could prescribe unnecessary
treatments to increase bills. Insurance companies want to detect these
anomalous fraudulent bills and reduce their losses. Traditional fraud detection
methods use expert rules and manual data processing.
  Recently, machine learning techniques automate this process, but hand-labeled
data is extremely costly and usually out of date. We propose a machine learning
model that automates fraud detection in an unsupervised way. Two deep learning
approaches include LSTM neural network for prediction next patient visit and a
seq2seq model. For normalization of produced anomaly scores, we propose
Empirical Distribution Function (EDF) approach. So, the algorithm works with
high class imbalance problems.
  We use real data on sequences of patients' visits data from Allianz company
for the validation. The models provide state-of-the-art results for
unsupervised anomaly detection for fraud detection in healthcare. Our EDF
approach further improves the quality of LSTM model.


  In this work, we present the correction formulas of the $k$-step BDF
convolution quadrature at the starting $k-1$ steps for the fractional
Feynman-Kac equation with L\'{e}vy flight.
  The desired $k$th-order convergence rate can be achieved with nonsmooth data.
Based on the idea of [{\sc Jin, Li, and Zhou}, SIAM J. Sci. Comput., 39 (2017),
A3129--A3152], we provide a detailed convergence analysis for the correction
BDF$k$ scheme. The numerical experiments with spectral method are given to
illustrate the effectiveness of the presented method. To the best of our
knowledge, this is the first proof of the convergence analysis and numerical
verified the sapce fractional evolution equation with correction BDF$k$.


  A search for long-lived particles (LLPs) produced in association with a Z
boson is presented. The study is performed using data from proton-proton
collisions with a center-of-mass energy of 13 TeV recorded by the CMS
experiment during 2016-2018, corresponding to an integrated luminosity of 117
fb$^{-1}$. The LLPs are assumed to decay to a pair of standard model quarks
that are identified as displaced jets within the CMS tracker system. Triggers
and selections based on Z boson decays to electron or muon pairs improve the
sensitivity to light LLPs (down to 15 GeV). This search provides sensitivity to
beyond the standard model scenarios which predict LLPs produced in association
with a Z boson. In particular, the results are interpreted in the context of
exotic decays of the Higgs boson to a pair of scalar LLPs (H $\to$ SS). The
Higgs boson decay branching fraction is constrained to values less than 6% for
proper decay lengths of 10-100 mm and for LLP masses between 40 and 55 GeV. In
the case of low-mass ($\approx$ 15 GeV) scalar particles that subsequently
decay to a pair of b quarks, the search is sensitive to branching fractions
$\mathcal{B}$(H $\to$ SS) $\lt$ 20% for proper decay lengths of 10-50 mm. The
use of associated production with a Z boson increases the sensitivity to
low-mass LLPs of this analysis with respect to gluon fusion searches. In the
case of 15 GeV scalar LLPs, the improvement corresponds to a factor of 2 at a
proper decay length of 30 mm.


  We investigate the phase diagram for the spin-$3/2$ ferromagnetic Blume-Capel
model in a transverse crystal field using the standard mean-field approximation
within the framework of Bogoliubov inequality for free energy. We draw a very
rich phase diagram with first- and second-order transition lines; tricritical
and tetracritical points; critical endpoint of order 2 and double critical
endpoint. Additionally, the behaviour of magnetisation as a function of
temperature over a wide range of values of both longitudinal and transverse
crystal fields is also analysed. To the best of our knowledge, this quantum
spin model has only been studied employing an effective field theory, which in
turn was not able to characterise completely the multicritical phenomena in its
phase diagram, because that procedure is not based on free energy. Thus, our
findings on the phase diagram for the present model are novel as they have been
not previously reported.


  In this paper we prove that every definable set has a definable triangulation
which is locally Lipschitz and weakly bi-Lipschitz on the natural simplicial
stratification of the simplicial complex. We also distinguish a class T of
regularity conditions and give a universal construction of a definable
triangulation with a T condition of a definable set. This class includes the
Whitney (B) condition and the Verdier condition.


  A big challenge in algorithmic composition is to devise a model that is both
easily trainable and able to reproduce the long-range temporal dependencies
typical of music. Here we investigate how artificial neural networks can be
trained on a large corpus of melodies and turned into automated music composers
able to generate new melodies coherent with the style they have been trained
on. We employ gated recurrent unit networks that have been shown to be
particularly efficient in learning complex sequential activations with
arbitrary long time lags. Our model processes rhythm and melody in parallel
while modeling the relation between these two features. Using such an approach,
we were able to generate interesting complete melodies or suggest possible
continuations of a melody fragment that is coherent with the characteristics of
the fragment itself.


  The elementary low energy excitations in the fractional quantum Hall (FQH)
regime are known to be fractionally charged quasiparticles and quasiholes. This
work focusses on quasiholes in a finite system of a few electrons treated by
exact numerical diagonalization. Recent experimental [Chung et al., PRB 67,
201104 (2003)] and theoretical [Kane, Fisher, PRB 67, 045307 (2003)] work on
quantum point contacts in the FQH regime showed strong evidence for single
quasiparticle tunneling to be forbidden at low temperature. We want to gain
insight into such constricted FQH systems by a numerical approach. Initially
the basics of numerically treating a system in rectangular geometry and
procedures to insert a quasihole excitation are presented. The excitations'
stability and fractional charge is confirmed for different interactions. The
question of quasihole tunneling is approached in two different systems: 1. A
system posessing bound, localized states of a quasihole shows evidence for
tunnel coupling between these states to exist. 2. Different potential forms to
model a quantum point contact are investigated and the injection of a single
quasihole near the constriction is surveyed in the system's time evolution.


  Various methods to deal with graph data have been proposed in recent years.
However, most of these methods focus on graph feature aggregation rather than
graph pooling. Besides, the existing top-k selection graph pooling methods have
a few problems. First, to construct the pooled graph topology, current top-k
selection methods evaluate the importance of the node from a single perspective
only, which is simplistic and unobjective. Second, the feature information of
unselected nodes is directly lost during the pooling process, which inevitably
leads to a massive loss of graph feature information. To solve these problems
mentioned above, we propose a novel graph self-adaptive pooling method with the
following objectives: (1) to construct a reasonable pooled graph topology,
structure and feature information of the graph are considered simultaneously,
which provide additional veracity and objectivity in node selection; and (2) to
make the pooled nodes contain sufficiently effective graph information, node
feature information is aggregated before discarding the unimportant nodes;
thus, the selected nodes contain information from neighbor nodes, which can
enhance the use of features of the unselected nodes. Experimental results on
four different datasets demonstrate that our method is effective in graph
classification and outperforms state-of-the-art graph pooling methods.


  In all available papers, on power integral bases of pure octic number fields
$K$, generated by a root $\alpha$ of a monic irreducible polynomial
$f(x)=x^8-m\in\mathbf Z[x]$, it was assumed that $m\neq \pm 1$ is square free.
In this paper, we investigate the monogenity of any pure octic number field,
without the condition that $m$ is square free. We start by calculating an
integral basis of $\mathbf Z_K$, the ring of integers of $K$. In particular, we
characterize when $\mathbf Z_K=\mathbf Z[\alpha]$. We give sufficient
conditions on $m$, which guarantee that $K$ is not monogenic. We finish the
paper by investigating the case when $m=a^u$, $u\in\{1,3,5,7\}$ and $a\neq \mp
1$ is a square free rational integer.


  Pinyin-to-character (P2C) conversion is the core component of pinyin-based
Chinese input method engine (IME). However, the conversion is seriously
compromised by the ambiguities of Chinese characters corresponding to pinyin as
well as the predefined fixed vocabularies. To alleviate such inconveniences, we
propose a neural P2C conversion model augmented by an online updated vocabulary
with a sampling mechanism to support open vocabulary learning during IME
working. Our experiments show that the proposed method outperforms commercial
IMEs and state-of-the-art traditional models on standard corpus and true
inputting history dataset in terms of multiple metrics and thus the online
updated vocabulary indeed helps our IME effectively follows user inputting
behavior.


  We systematically investigate the problem of representing Markov chains by
families of random maps, and which regularity of these maps can be achieved
depending on the properties of the probability measures. Our key idea is to use
techniques from optimal transport to select optimal such maps. Optimal
transport theory also tells us how convexity properties of the supports of the
measures translate into regularity properties of the maps via Legendre
transforms. Thus, from this scheme, we cannot only deduce the representation by
measurable random maps, but we can also obtain conditions for the
representation by continuous random maps. Finally, we present conditions for
the representation of Markov chain by random diffeomorphisms.


  The collections of spectral energy distributions (SEDs) in the \emph{Hubble
Space Telescope} (HST) CALSPEC database are augmented by 19 IR SEDs from Wide
Field Camera 3 (WFC3) IR grism spectra. Together, the two IR grisms, G102 and
G141, cover the 0.8--1.7~\micron\ range with resolutions R=200 and 150,
respectively. These new WFC3 SEDs overlap existing CALSPEC Space Telescope
Imaging Spectrograph (STIS) standard star flux distributions at 0.8-1~\micron\
with agreement to $\lesssim$1\%. Some CALSPEC standards already have near-IR
camera and multi-object spectrogragh (NICMOS) SEDs; but in their overlap region
at 0.8--1.7~\micron, the WFC3 data have better wavelength accuracy, better
spectral resolution, better repeatability, and, consequently, better flux
distributions of $\sim$1\% accuracy in our CALSPEC absolute flux SEDs vs.
$\sim$2\% for NICMOS. With the improved SEDs in the WFC3 range, the modeled
extrapolations to 32~\micron\ for JWST flux standards begin to lose precision
longward of the 1.7~\micron WFC3 limit, instead of at the 1.0~\micron\ long
wavelength limit for STIS. For example, the extrapolated IR flux longward of
1.7~\micron\ for 1808347 increases by $\sim$1\% for the model fit to the data
with WFC3, instead of just to the STIS SED alone.


  Accurate prediction of travel time is an essential feature to support
Intelligent Transportation Systems (ITS). The non-linearity of traffic states,
however, makes this prediction a challenging task. Here we propose to use
dynamic linear models (DLMs) to approximate the non-linear traffic states.
Unlike a static linear regression model, the DLMs assume that their parameters
are changing across time. We design a DLM with model parameters defined at each
time unit to describe the spatio-temporal characteristics of time-series
traffic data. Based on our DLM and its model parameters analytically trained
using historical data, we suggest an optimal linear predictor in the minimum
mean square error (MMSE) sense. We compare our prediction accuracy of travel
time for freeways in California (I210-E and I5-S) under highly congested
traffic conditions with those of other methods: the instantaneous travel time,
k-nearest neighbor, support vector regression, and artificial neural network.
We show significant improvements in the accuracy, especially for short-term
prediction.


  The production of Z bosons is studied in the dimuon and dielectron decay
channels in PbPb and pp collisions at sqrt(s[NN]) = 2.76 TeV, using data
collected by the CMS experiment at the LHC. The PbPb data sample corresponds to
an integrated luminosity of about 150 inverse microbarns, while the pp data
sample collected in 2013 at the same nucleon-nucleon centre-of-mass energy has
an integrated luminosity of 5.4 inverse picobarns. The Z boson yield is
measured as a function of rapidity, transverse momentum, and collision
centrality. The ratio of PbPb to pp yields, scaled by the number of inelastic
nucleon-nucleon collisions, is found to be 1.06 +/- 0.05 (stat) +/- 0.08 (syst)
in the dimuon channel and 1.02 +/- 0.08 (stat) +/- 0.15 (syst) in the
dielectron channel, for centrality-integrated Z boson production. This binary
collision scaling is seen to hold in the entire kinematic region studied, as
expected for a colourless probe that is unaffected by the hot and dense QCD
medium produced in heavy ion collisions.


  Microservice architecture has transformed traditional monolithic applications
into lightweight components. Scaling these lightweight microservices is more
efficient than scaling servers. However, scaling microservices still faces the
challenges resulted from the unexpected spikes or bursts of requests, which are
difficult to detect and can degrade performance instantaneously. To address
this challenge and ensure the performance of microservice-based applications,
we propose a status-aware and elastic scaling framework called StatuScale,
which is based on load status detector that can select appropriate elastic
scaling strategies for differentiated resource scheduling in vertical scaling.
Additionally, StatuScale employs a horizontal scaling controller that utilizes
comprehensive evaluation and resource reduction to manage the number of
replicas for each microservice. We also present a novel metric named
correlation factor to evaluate the resource usage efficiency. Finally, we use
Kubernetes, an open-source container orchestration and management platform, and
realistic traces from Alibaba to validate our approach. The experimental
results have demonstrated that the proposed framework can reduce the average
response time in the Sock-Shop application by 8.59% to 12.34%, and in the
Hotel-Reservation application by 7.30% to 11.97%, decrease service level
objective violations, and offer better performance in resource usage compared
to baselines.


  We present a Z_2 x Z_2 four dimensional orientifold in which supersymmetry is
broken by a temperature-like Scherk-Schwarz mechanism. As usual in this type of
models, at the tree-level the breaking affects only the branes tangent to the
direction involved by the SS deformation, and it can propagate only through
radiative corrections to other sectors, where the gauge group is broken. The
result is a non-chiral model with gauge group Usp(16)^2 x Usp(8)^4.


  We present the constraints on the amplitude of magnetic fields generated
prior to the recombination using CMB temperature and polarization anisotropy
data from Planck 2018 release, alone and in combination with those from
BICEP2/Keck array and the South Pole Telescope. We model the fields with a
generic parametrization and we make no assumptions on their origin in order to
provide general constraints on their characteristics. The analysis updates the
former corresponding Planck 2015 results both on data and numerical
implementation. We then perform forecasts for the next generation of CMB
experiments such as LiteBIRD satellite alone and in combination with future
ground based experiments.


  While most current high-throughput DNA sequencing technologies generate short
reads with low error rates, emerging sequencing technologies generate long
reads with high error rates. A basic question of interest is the tradeoff
between read length and error rate in terms of the information needed for the
perfect assembly of the genome. Using an adversarial erasure error model, we
make progress on this problem by establishing a critical read length, as a
function of the genome and the error rate, above which perfect assembly is
guaranteed. For several real genomes, including those from the GAGE dataset, we
verify that this critical read length is not significantly greater than the
read length required for perfect assembly from reads without errors.


  Computer Mediated Courseware (CMC) has been developed so far for individual
courses considering single or multiple text books. A group of courseware can be
developed by using multiple text books and in this case, it is a requirement to
cluster the contents of different books to form a generalized clustered
content. No work has been found to develop courseware applying generalized
clustered content. We have proposed a clustering of content supporting computer
mediated courseware development based on data mining techniques to construct a
hierarchical general structure of a group of courseware combining the
individual structure of a set of books. The clustering will help the courseware
developer to dynamically allocate contents to develop different courses using a
group of books. The authors have applied this methodology for different level
of courses on database. The methodology is generalized and can be applied to
any other courses.


  In the light of the recently predicted isotopic composition of the kpc-scale
jet in Centaurus A, we re-investigate whether this source could be responsible
for some of the ultra-high energy cosmic rays detected by the Pierre Auger
Observatory. We find that a nearby source like Centaurus A is well motivated by
the composition and spectral shape, and that such sources should start to
dominate the flux above ~ 4 EeV. The best-fitting isotopes from our modelling,
with the maximum 56Fe energy fixed at 250 EeV, are of intermediate mass, 12C to
16O, while the best-fitting particle index is 2.3.


  Various observables in different four-dimensional superconformal Yang-Mills
theories can be computed exactly as Fredholm determinants of truncated Bessel
operators. We exploit this relation to determine their dependence on the 't
Hooft coupling constant. Unlike the weak coupling expansion, which has a finite
radius of convergence, the strong coupling expansion is factorially divergent,
necessitating the inclusion of nonperturbative, exponentially small
corrections. We develop a method to systematically compute these corrections
and discuss the resurgent properties of the resulting transseries.


  We apply certain methods of nonlinear time series analysis to the extensive
air shower clusters found earlier in the data set obtained with the EAS-1000
Prototype array. In particular, we use the Grassberger-Procaccia algorithm to
compute the correlation dimension of samples in the vicinity of the clusters.
The validity of the results is checked by surrogate data tests and some
additional quantities. We compare our conclusions with the results of similar
investigations performed by the EAS-TOP and LAAS groups.


  The standard bag-of-words vector space model (VSM) is efficient, and
ubiquitous in information retrieval, but it underestimates the similarity of
documents with the same meaning, but different terminology. To overcome this
limitation, Sidorov et al. proposed the Soft Cosine Measure (SCM) that
incorporates term similarity relations. Charlet and Damnati showed that the SCM
is highly effective in question answering (QA) systems. However, the
orthonormalization algorithm proposed by Sidorov et al. has an impractical time
complexity of $\mathcal O(n^4)$, where n is the size of the vocabulary.
  In this paper, we prove a tighter lower worst-case time complexity bound of
$\mathcal O(n^3)$. We also present an algorithm for computing the similarity
between documents and we show that its worst-case time complexity is $\mathcal
O(1)$ given realistic conditions. Lastly, we describe implementation in
general-purpose vector databases such as Annoy, and Faiss and in the inverted
indices of text search engines such as Apache Lucene, and ElasticSearch. Our
results enable the deployment of the SCM in real-world information retrieval
systems.


  A learning approach for optimal feedback gains for nonlinear continuous time
control systems is proposed and analysed. The goal is to establish a rigorous
framework for computing approximating optimal feedback gains using neural
networks. The approach rests on two main ingredients. First, an optimal control
formulation involving an ensemble of trajectories with 'control' variables
given by the feedback gain functions. Second, an approximation to the feedback
functions via realizations of neural networks. Based on universal approximation
properties we prove the existence and convergence of optimal stabilizing neural
network feedback controllers.


  While one of the most promising applications of carbon nanotubes (CNTs) is to
enhance polymer orientation and crystallization to achieve advanced carbon
fibers, the successful realization of this goal has been hindered by the
insufficient atomistic understanding of polymer-CNT interfaces. We herein
theoretically study polyacrylonitrile (PAN)-CNT hybrid structures as a
representative example of polymer-CNT composites. Based on density-functional
theory calculations, we first find that the relative orientation of polar PAN
nitrile groups with respect to the CNT surface is the key factor that
determines the PAN-CNT interface energetics and the lying-down PAN
configurations are much more preferable than their standing-up counterparts.
The CNT curvature is identified as another important factor, giving the largest
binding energy in the zero-curvature graphene limit. Charge transfer analysis
explains the unique tendency of linear PAN alignments on the CNT surface and
the possibility of ordered PAN-PAN assembly. Next, performing large-scale
molecular dynamics simulations, we show that the desirable linear PAN-CNT
alignment can be achieved even for relatively large initial misorientations and
further demonstrate that graphene nanoribbons are a promising carbon
nano-reinforcement candidate. The microscopic understanding accumulated in this
study will provide design guidelines for the development of next-generation
carbon nanofibers.


  We study the morphology of dark lanes and filaments in the dust-rich galaxy
NGC 253 using an unsharp-masked $B$-band optical photograph. Dust features are
classified as `arcs', which have heights and scale radius of about 100 to 300
pc, connecting two or more dark clouds, and `loops' and `bubbles', which are
developed forms of arcs, expanding into the disk-halo interface. These have
diameters of a few hundred pc to $\sim 1$ kpc. Among the bubbles, we notice a
peculiar round-shaped bubble above the nucleus, which could be a large-diameter
($\sim 300$ pc) supernova remnant exploded in the halo over the nucleus. We
also find `vertical dust streamers', which comprise bunches of narrow filaments
with a thickness of a few tens of pc and are almost perpendicular to the
galactic plane, extending coherently for 1 to 2 kpc toward the halo. Finally,
we note `short vertical dust filaments' (or spicules) are found in the central
region. We interpret these features as due to three-dimensional structures of
gas extending from the disk into the halo. We propose a `boiling disk' model
where the filamentary features are produced by star-forming activity in the
disk as well as the influence of magnetic fluxes. We discuss the implication of
the model for the chemical evolution of the ISM in a galaxy disk.


  We present Plateau de Bure Interferometer observations of far infra-red
emission lines in BRI 0952-0115, a lensed quasar at z=4.4 powered by a
super-massive black hole (M_BH=2x10^9 M_sun). In this source, the resolved map
of the [CII] emission at 158 micron allows us to reveal the presence of a
companion galaxy, located at \sim 10 kpc from the quasar, undetected in optical
observations. From the CO(5-4) emission line properties we infer a stellar mass
M*<2.2x10^10 M_sun, which is significantly smaller than the one found in local
galaxies hosting black holes with similar masses (M* \sim 10^12 M_sun). The
detection of the [NII] emission at 205 micron suggests that the metallicity in
BRI 0952-0115 is consistent with solar, implying that the chemical evolution
has progressed very rapidly in this system. We also present PdBI observations
of the [CII] emission line in SDSSJ1148+5251, one of the most distant quasar
known, at z=6.4. We detect broad wings in the [CII] emission line, indicative
of gas which is outflowing from the host galaxy. In particular, the extent of
the wings, and the size of the [CII] emitting region associated to them, are
indicative of a quasar-driven massive outflow with the highest outflow rate
ever found (dM/dt>3500 M_sun/yr).


  In this paper, we realize the transmitter of high frequency (HF)
bidirectional transceiver radio. A bidirectional transceiver (Bitx) consists of
a transmitter and receiver, in which some common circuits are used together by
the transmitter and receiver. In addition, Bitx radio uses a single conversion
superheterodyne transmitter, which only shifts frequency once in a signal
generation process. The measurement result shows that it works at the frequency
of 6.8 MHz with 10 MHz BFO, 3,2 MHz VFO, and 50,3 dBm transmit power. The
transmitting frequency is obtained from the difference between BFO and VFO
oscillator. Bitx radio has a simple circuit and is designed with low-cost
components, and it could be an alternative solution for communication in remote
areas.


  The iconic Schr\"odinger's cat state describes a system that may be in a
superposition of two macroscopically distinct states, for example two clearly
separated oscillator coherent states. Quite apart from their role in
understanding the quantum classical boundary, such states have been suggested
as offering a quantum advantage for quantum metrology, quantum communication
and quantum computation. As is well known these applications have to face the
difficulty that the irreversible interaction with an environment causes the
superposition to rapidly evolve to a mixture of the component states in the
case that the environment is not monitored. Here we show that by engineering
the interaction with the environment there exists a large class of systems that
can evolve irreversibly to a cat state. To be precise we show that it is
possible to engineer an irreversible process so that the steady state is close
to a pure Schr\"odinger's cat state by using double well systems and an
environment comprising two-photon (or phonon) absorbers. We also show that it
should be possible to prolong the lifetime of a Schr\"odinger's cat state
exposed to the destructive effects of a conventional single-photon decohering
environment. Our protocol should make it easier to prepare and maintain
Schr\"odinger cat states which would be useful in applications of quantum
metrology and information processing as well as being of interest to those
probing the quantum to classical transition.