  We are interested in the dynamics of interfaces, or zeros, of shock waves in
general scalar viscous conservation laws with a locally Lipschitz continuous
flux function, such as the modular Burgers' equation. We prove that all
interfaces coalesce within finite time, leaving behind either a single
interface or no interface at all. Our proof relies on mass and energy
estimates, regularization of the flux function, and an application of the Sturm
theorems on the number of zeros of solutions of parabolic problems. Our
analysis yields an explicit upper bound on the time of extinction in terms of
the initial condition and the flux function. Moreover, in the case of a smooth
flux function, we characterize the generic bifurcations arising at a
coalescence event with and without the presence of odd symmetry. We identify
associated scaling laws describing the local interface dynamics near collision.
Finally, we present an extension of these results to the case of anti-shock
waves converging to asymptotic limits of opposite signs. Our analysis is
corroborated by numerical simulations in the modular Burgers' equation and its
regularizations.


  The cardiac interbeat (RR) increment time series can be decomposed into two
sub-sequences: a magnitude series and a sign series. We show that the sign
sequence, a simple binary representation of the original RR series, retains
fundamental scaling properties of the original series, is robust with respect
to outliers, and may provide useful information about neuroautonomic control
mechanisms.


  We study the spectral statistics in the center of the lowest Landau band of a
2D disordered system with smooth potential and strong transverse magnetic
field. Due to the finite size of the system, the energy range in which there
are extended states is finite as well. The behavior in this range can be viewed
as the analogue of the Anderson metal-insulator transition for the case of the
Hall system. Accordingly, we verify recent predictions regarding the exponent
of the asymptotic power law of $\Sigma^2 (\bar N)$, $\gamma$, and that of the
stretched exponential dominating the large $s$ behavior of the spacings
distribution, $\alpha$. Both the relations, $\alpha = 1- \gamma$, and $\gamma =
1 - {1\over{\nu d}}$ where $\nu$ is the critical exponent of the localization
length and $d$ is the dimension, are found to hold within the accuracy of our
computations. However, we find that none of several possible models of the
entire spacings distribution correctly describes our situation. Finally, for
very large $\bar N$, $\bar N > 60$, we find a new regime in which $\Sigma^2
(\bar N)$ behaves as a power law with an unexpectedly large power, $\gamma_1 =
1.38 \pm 0.02$.


  A 2D slab approximation of the interactions of electrons with intense
linearly polarized laser radiation and static electric and magnetic fields is
widely used for both numerical simulations and simplified semi-analytical
models. It is shown that in this case electron dynamics can be conveniently
described in the framework of 3/2 dimensional Hamiltonian approach. The
electron acceleration beyond a standard ponderomotive scaling, caused by the
synergistic effects of the laser and static electro-magnetic fields, is due to
an onset of stochastic electron motion.


  One exciting progress in recent cold atom experiments is the development of
high resolution, in situ imaging techniques for atomic quantum gases [1-3].
These new powerful tools provide detailed information on the distribution of
atoms in a trap with resolution approaching the level of single atom and even
single lattice site, and complement the well developed time-of-flight method
that probes the system in momentum space. In a condensed matter analogy, this
technique is equivalent to locating electrons of a material in a snap shot. In
situ imaging has offered a new powerful tool to study atomic gases and inspired
many new research directions and ideas. In this chapter, we will describe the
experimental setup of in situ absorption imaging, observables that can be
extracted from the images, and new physics that can be explored with this
technique.


  We study the radio properties at 1.4 GHz of Seyfert galaxies with strong
forbidden high-ionization lines (FHILs), selected from the Sloan Digital Sky
Survey - a large-sized sample containing nearly equal proportion of diverse
range of Seyfert galaxies showing similar redshift distributions compiled by
Gelbord et al. (2009) using the Very Large Array survey images. The radio
detection rate is low, 49%, which is lower than the detection rate of several
other known Seyfert galaxy samples. These galaxies show low star formation
rates and the radio emission is dominated by the active nucleus with $\le$10%
contribution from thermal emission, and possibly, none show evidence for
relativistic beaming. The radio detection rate, distributions of radio power,
and correlations between radio power and line luminosities or X-ray luminosity
for narrow-line Seyfert 1 (NLS1), Seyfert 1 and Seyfert 2 galaxies are
consistent with the predictions of the unified scheme hypothesis. Using
correlation between radio and [O\,III]\,$\lambda$ \,5007\,\AA\ luminosities, we
show that $\sim$8% sample sources are radio-intermediate and the remaining are
radio-quiet. There is possibly an ionization stratification associated with
clouds on scales of 0.1-1.0 kpc, which have large optical depths at 1.4 GHz,
and it seems these clouds are responsible for free-free absorption of radio
emission from the core, hence, leading to low radio detection rate for these
FHIL-emitting Seyfert galaxies.


  The small $x$ behaviour of polarized parton distributions is related to
non-leading reggeons in the framework of the high-energy effective action.
Double-logarithmic contributions to the reggeon interaction beyond the ones
included in the GLAP equation are encountered in all polarized parton
distributions. The transversity distributions of quarks and gluons behave
similar at small $x$. Contribution to the spin workshop at DESY-Zeuthen,
September 1997.


  This is a version of the author's Ph.D. thesis. The methods of effective
field theory are used to study generic theories of inflation with a single
inflaton field and to perform a general analysis of the associated
non-Gaussianities. We investigate the amplitudes and shapes of the various
three and four-point correlators which are generated by different classes of
single-field inflationary models. Besides the well-known results for the so
called P(X,\phi) model and the ghost inflationary theories, which we recover,
we point out that extrinsic curvature-generated interactions may give rise to
large non-Gaussianities with distinctive features in the form of specific
shape-functions (e.g. flat, orthogonal etc..) for the correlators.


  Semileptonic decays provide an excellent environment for testing the Standard
Model (SM). Violation of lepton universality would be a smoking gun for physics
beyond the SM. Using semi-tauonic $B$ decays, LHCb finds a value of
$\mathcal{R}(D^*) = \mathcal{B}(\bar{B}^0 \to D^{*+} \tau^{-}
\bar{\nu}_{\tau})/\mathcal{B}(\bar{B}^0 \to D^{*+} \mu^{-} \bar{\nu}_{\mu}) =
0.336 \pm 0.027 \rm{(stat)} \pm 0.030 \rm{(syst)}$, which is 2.1 standard
deviations larger than the value expected from the SM. Moreover, the
measurement of the $CP$ asymmetry in mixing of $B_s^0$ mesons is highly
sensitive to physics beyond the SM. This article presents the latest result on
semileptonic asymmetries; using the full Run 1 dataset, it is found that
$a_{\rm{sl}}^s = (0.39 \pm 0.26 \rm{(stat)} \pm 0.20 \rm{(syst)})\%$, which is
consistent with the Standard Model.


  Total solar irradiance and UV spectral solar irradiance have been monitored
since 1978 through a succession of space missions. This is accompanied by the
development of models aimed at replicating solar irradiance by relating the
variability to solar magnetic activity. The NRLSSI and SATIRE-S models provide
the most comprehensive reconstructions of total and spectral solar irradiance
over the period of satellite observation currently available. There is
persistent controversy between the various measurements and models in terms of
the wavelength dependence of the variation over the solar cycle, with
repercussions on our understanding of the influence of UV solar irradiance
variability on the stratosphere. We review the measurement and modelling of UV
solar irradiance variability over the period of satellite observation. The
SATIRE-S reconstruction is consistent with spectral solar irradiance
observations where they are reliable. It is also supported by an independent,
empirical reconstruction of UV spectral solar irradiance based on UARS/SUSIM
measurements from an earlier study. The weaker solar cycle variability produced
by NRLSSI between 300 and 400 nm is not evident in any available record. We
show that although the method employed to construct NRLSSI is principally
sound, reconstructed solar cycle variability is detrimentally affected by the
uncertainty in the SSI observations it draws upon in the derivation. Based on
our findings, we recommend, when choosing between the two models, the use of
SATIRE-S for climate studies.


  We propose a variational approach to approximate measures with measures
uniformly distributed over a 1 dimentional set. The problem consists in
minimizing a Wasserstein distance as a data term with a regularization given by
the length of the support. As it is challenging to prove existence of solutions
to this problem, we propose a relaxed formulation, which always admits a
solution. In the sequel we show that if the ambient space is $\mathbb{R}^2$ ,
under techinical assumptions, any solution to the relaxed problem is a solution
to the original one. Finally we manage to prove that any optimal solution to
the relaxed problem, and hence also to the original, is Ahlfors regular.


  A set of edges $X\subseteq E(G)$ of a graph $G$ is an edge general position
set if no three edges from $X$ lie on a common shortest path. The edge general
position number ${\rm gp}_{\rm e}(G)$ of $G$ is the cardinality of a largest
edge general position set in $G$. Graphs $G$ with ${\rm gp}_{\rm e}(G) = |E(G)|
- 1$ and with ${\rm gp}_{\rm e}(G) = 3$ are respectively characterized. Sharp
upper and lower bounds on ${\rm gp}_{\rm e}(G)$ are proved for block graphs $G$
and exact values are determined for several specific block graphs.


  Taking advantage of the recent Gaia Data Release 3 (DR3), we map chemical
inhomogeneities in the Milky Way's disc out to a distance of $\sim$ 4 kpc from
the Sun, using different samples of bright giant stars. The samples are
selected using effective temperatures and surface gravities from the GSP-Spec
module, and are expected to trace stellar populations of different typical age.
The cool (old) giants exhibit a relatively smooth radial metallicity gradient
with an azimuthal dependence. Binning in Galactic azimuth $\phi$, the slope
gradually varies from $d$[M/H]$/dR \sim -0.054$ dex kpc$^{-1}$ at $\phi \sim
-20^{\circ}$ to $\sim -0.035$ dex kpc$^{-1}$ at $\phi \sim 20^{\circ}$. On the
other hand, the relatively hotter (and younger) stars present remarkable
inhomogeneities, apparent as three (possibly four) metal-rich elongated
features in correspondence of the spiral arms' locations in the Galactic disc.
When projected onto Galactic radius, those features manifest themselves as
statistically significant bumps on top of the observed radial metallicity
gradients with amplitudes up to $ \sim 0.05-0.1$ dex, making the assumption of
a linear radial decrease not applicable to this sample. The strong correlation
between the spiral structure of the Galaxy and the observed chemical pattern in
the young sample indicates that the spiral arms might be at the origin for the
detected chemical inhomogeneities. In this scenario, the spiral arms would
leave in the younger stars a strong signature, which progressively disappears
when cooler (and older) giants are considered.


  Using IceTop, the surface component of the IceCube Neutrino Observatory, the
all-particle cosmic ray energy spectrum has been determined above a few PeV.
The measured energy spectrum leaves a gap of more than a decade in energy to
direct measurements by balloon and satellite experiments. In this analysis, we
lowered the energy threshold of IceTop to 250 TeV, narrowing the gap between
IceTop and direct measurements. In order to collect lower energy events, we
implemented a new trigger that uses four pairs of infill stations for which the
separation between stations is less than 50 m, compared to 125 m for the main
array. The new trigger collects data from the entire array for events with hits
on at least one infill pair. The low-energy extension of the all-particle
cosmic ray energy spectrum using these IceTop events is measured and is
compared with the energy spectrum from HAWC and other experiments. Air shower
simulations with two different hadronic interaction models, Sibyll 2.1 and
QGSJetII-04, are used in this analysis and an energy spectrum for each model is
produced. Both measured energy spectra show a bend around the knee region.


  We consider the mass-critical focusing nonlinear Schrodinger equation in the
presence of an external potential, when the nonlinearity is inhomogeneous. We
show that if the inhomogeneous factor in front of the nonlinearity is
sufficiently flat at a critical point, then there exists a solution which blows
up in finite time with the maximal (unstable) rate at this point. In the case
where the critical point is a maximum, this solution has minimal mass among the
blow-up solutions. As a corollary, we also obtain unstable blow-up solutions of
the mass-critical Schrodinger equation on some surfaces. The proof is based on
properties of the linearized operator around the ground state, and on a full
use of the invariances of the equation with an homogeneous nonlinearity and no
potential, via time-dependent modulations.


  Beamforming techniques are proposed for a joint multi-input-multi-output
(MIMO) radar-communication (RadCom) system, where a single device acts both as
a radar and a communication base station (BS) by simultaneously communicating
with downlink users and detecting radar targets. Two operational options are
considered, where we first split the antennas into two groups, one for radar
and the other for communication. Under this deployment, the radar signal is
designed to fall into the null-space of the downlink channel. The communication
beamformer is optimized such that the beampattern obtained matches the radar's
beampattern while satisfying the communication performance requirements. To
reduce the optimizations' constraints, we consider a second operational option,
where all the antennas transmit a joint waveform that is shared by both radar
and communications. In this case, we formulate an appropriate probing
beampattern, while guaranteeing the performance of the downlink communications.
By incorporating the SINR constraints into objective functions as penalty
terms, we further simplify the original beamforming designs to weighted
optimizations, and solve them by efficient manifold algorithms. Numerical
results show that the shared deployment outperforms the separated case
significantly, and the proposed weighted optimizations achieve a similar
performance to the original optimizations, despite their significantly lower
computational complexity.


  Accretion in the nuclei of active galaxies may occur chaotically. This can
produce accretion discs which are counter-rotating or strongly misaligned with
respect to the spin of the central supermassive black hole (SMBH), or the axis
of a close SMBH binary. Accordingly we consider the cancellation of angular
momentum in accretion discs with a significant change of plane (tilt) between
inner and outer parts. We estimate analytically the maximum accretion rate
through such discs and compare this with the results of Smoothed Particle
Hydrodynamics (SPH) simulations. These suggest that accretion rates on to
supermassive black holes may be larger by factors $\gtrsim 100$ if the disc is
internally tilted in this way rather than planar. This offers a natural way of
driving the rapid growth of supermassive black holes, and the coalescence of
SMBH binaries.


  Let $E(z,s)$ be the non-holomorphic Eisenstein series for the modular group
$SL(2,{\mathbb Z})$. The classical Kronecker limit formula shows that the
second term in the Laurent expansion at $s=1$ of $E(z,s)$ is essentially the
logarithm of the Dedekind eta function. This eta function is a weight $1/2$
modular form and Dedekind expressed its multiplier system in terms of Dedekind
sums. Building on work of Goldstein, we extend these results from the modular
group to more general Fuchsian groups $\Gamma$. The analogue of the eta
function has a multiplier system that may be expressed in terms of a map
$S:\Gamma \to {\mathbb R}$ which we call a modular Dedekind symbol. We obtain
detailed properties of these symbols by means of the limit formula.
  Twisting the usual Eisenstein series with powers of additive homomorphisms
from $\Gamma$ to ${\mathbb C}$ produces higher-order Eisenstein series. These
series share many of the properties of $E(z,s)$ though they have a more
complicated automorphy condition. They satisfy a Kronecker limit formula and
produce higher-order Dedekind symbols $S^*:\Gamma \to {\mathbb R}$. As an
application of our general results, we prove that higher-order Dedekind symbols
associated to genus one congruence groups $\Gamma_0(N)$ are rational.


  Recent experimental discovery of flavor symmetry breaking metallic phases in
Bernal-stacked bilayer graphene points to the strongly interacting nature of
electrons near the top (bottom) of its valence (conduction) band.
Superconductivity was also observed in between these symmetry breaking phases
when the graphene bilayer is placed under a small in-plane magnetic field or in
close proximity to a monolayer WSe$_2$ substrate. Here we address the
correlated nature of the band edge electrons and obtain the quantum phase
diagram of their many-body ground states incorporating the effect of proximity
induced spin-orbit coupling. We find that in addition to the spin/valley flavor
polarized half and quarter metallic states, two types of intervalley coherent
phases emerge near the phase boundaries between the flavor polarized metals.
Both spin-orbit coupling and in-plane magnetic field disfavor the
spin-unpolarized valley coherent phase. Our findings suggest possible
competition between intervalley coherence and superconducting orders, arising
from the intriguing correlation effects in bilayer graphene in the presence of
spin-orbit coupling.


  Convolutional neural networks have made significant progresses in edge
detection by progressively exploring the context and semantic features.
However, local details are gradually suppressed with the enlarging of receptive
fields. Recently, vision transformer has shown excellent capability in
capturing long-range dependencies. Inspired by this, we propose a novel
transformer-based edge detector, \emph{Edge Detection TransformER (EDTER)}, to
extract clear and crisp object boundaries and meaningful edges by exploiting
the full image context information and detailed local cues simultaneously.
EDTER works in two stages. In Stage I, a global transformer encoder is used to
capture long-range global context on coarse-grained image patches. Then in
Stage II, a local transformer encoder works on fine-grained patches to excavate
the short-range local cues. Each transformer encoder is followed by an
elaborately designed Bi-directional Multi-Level Aggregation decoder to achieve
high-resolution features. Finally, the global context and local cues are
combined by a Feature Fusion Module and fed into a decision head for edge
prediction. Extensive experiments on BSDS500, NYUDv2, and Multicue demonstrate
the superiority of EDTER in comparison with state-of-the-arts.


  We study the freeze-out parameters in a QCD-assisted effective theory that
accurately captures the quantum and in-medium effects of QCD at low energies.
Functional renormalization group approach is implemented in our work to
incorporate the non-perturbative quantum, thermal and density fluctuations. By
analyzing the calculated baryon number susceptibility ratios
$\chi_{2}^{B}/\chi_{1}^{B}$ and $\chi_{3}^{B}/\chi_{2}^{B}$, we determine the
chemical freeze-out temperatures and baryon chemical potentials in cases of
hard thermal or dense loop improved $\mu$-dependent glue potential and
$\mu$-independent glue potential. We calculate the
${\chi_{4}^{B}}/{\chi_{2}^{B}}\, (\kappa \sigma^{2})$ and
${\chi_{6}^{B}}/{\chi_{2}^{B}}$ along the freeze-out line for both cases. It's
found that $\kappa \sigma^{2}$ exhibits a nonmonotonic behavior in low
collision energy region and approach to one for lower collision energy.
${\chi_{6}^{B}}/{\chi_{2}^{B}}$ shows a similar complicated behavior in our
calculation.


  We recall the main facts about the odd Laplacian acting on half-densities on
an odd symplectic manifold and discuss a homological interpretation for it
suggested recently by P. {\v{S}}evera. We study the relationship of odd
symplectic geometry with classical objects. We show that the Berezinian of a
canonical transformation for an odd symplectic form is a polynomial in matrix
entries and a complete square. This is a simple but fundamental fact, parallel
to Liouville's theorem for an even symplectic structure. We draw attention to
the fact that the de Rham complex on $M$ naturally admits an action of the
supergroup of all canonical transformations of $\Pi T^*M$. The infinitesimal
generators of this action turn out to be the classical `Lie derivatives of
differential forms along multivector fields'.


  We present the discovery of three sub-Neptune-sized planets transiting the
nearby and bright Sun-like star HD 191939 (TIC 269701147, TOI 1339), a
$K_{s}=7.18$ magnitude G8 V dwarf at a distance of only 54 parsecs. We validate
the planetary nature of the transit signals by combining five months of data
from the Transiting Exoplanet Survey Satellite with follow-up ground-based
photometry, archival optical images, radial velocities, and high angular
resolution observations. The three sub-Neptunes have similar radii ($R_{b} =
3.42^{+0.11}_{-0.11}\,R_{\oplus}$, $R_{c}=3.23_{-0.11}^{+0.11}\,R_{\oplus}$,
and $R_{d}=3.16_{-0.11}^{+0.11}\,R_{\oplus}$) and their orbits are consistent
with a stable, circular, and co-planar architecture near mean motion resonances
of 1:3 and 3:4 ($P_{b}=8.88$ days, $P_{c}=28.58$ days, and $P_{d}=38.35$ days).
The HD~191939 system is an excellent candidate for precise mass determinations
of the planets with high-resolution spectroscopy due to the host star's
brightness and low chromospheric activity. Moreover, the system's compact and
near-resonant nature can provide an independent way to measure planetary masses
via transit timing variations while also enabling dynamical and evolutionary
studies. Finally, as a promising target for multi-wavelength transmission
spectroscopy of all three planets' atmospheres, HD 191939 can offer valuable
insight into multiple sub-Neptunes born from a proto-planetary disk that may
have resembled that of the early Sun.


  The shock model of gamma-ray bursts (GRBs) contains two equipartition
parameters: the magnetic energy density and the kinetic energy density of the
electrons relative to the total energy density of the shock, "epsilon_B" and
"epsilon_e", respectively. These are free parameters within the model. Whereas
the Weibel shock theory and numerical simulations fix "epsilon_B" at the level
of ~few times(10^{-3}...10^{-4}), no understanding of "epsilon_e" exists so
far. Here we demonstrate that it inevitably follows from the theory that
"epsilon_e"~(epsilon_B)^(1/2). The GRB afteglow data fully agree with this
theoretical prediction. Our result explains why the electrons are close to
equipartition in GRBs. The "epsilon_e"-"epsilon_B" relation can potentially be
used to reduce the number of free parameters in afterglow models.


  We have investigated the empirical lag-luminosity relation in the Gamma-ray
Burst (GRB) source-frame. We selected two energy bands (100-200 keV and 300-400
keV) in the GRB source-frame, which after redshift correction, lie in the
observer-frame energy range of the Swift Burst Alert Telescope (BAT). The
spectral lags between these energy channels are then presented as a function of
the isotropic peak luminosity of the GRBs in the sample.


  Enhancing and controlling light-matter interactions is crucial in
nanotechnology and material science, propelling research on green energy, laser
technology, and quantum cryptography. Central to enhanced light-matter coupling
are two parameters: the spectral overlap between an optical cavity mode and the
material's spectral features (e.g., excitonic or molecular absorption lines),
and the quality factor of the cavity. Controlling both parameters
simultaneously is vital, especially in complex systems requiring extensive data
to uncover the numerous effects at play. However, so far, photonic approaches
have focused solely on sampling a limited set of data points within this 2D
parameter space. Here we introduce a nanophotonic approach that can
simultaneously and continuously encode the spectral and quality factor
parameter space of light-matter interactions within a compact spatial area. Our
novel dual-gradient metasurface design is composed of a 2D array of smoothly
varying subwavelength nanoresonators, each supporting a unique mode. This
results in 27,500 distinct modes within one array and a resonance density
approaching the theoretical upper limit for metasurfaces. By applying our
dual-gradient to surface-enhanced molecular sensing, we demonstrate the
importance of coupling tailoring and unveil an additional coupling-based
dimension of spectroscopic data. Our metasurface design paves the way for
generalized light-matter coupling metasurfaces, leading to advancements in the
field of photocatalysis, chemical sensing, and entangled photon generation.


  Making use of the emergence of an entangling gate from the Mayer Vietoris
maps generating a torus and employing the correspondence between quantum error
correction codes and gauge symmetries I show that non-abelian gauge theories
are related to the existence of entanglement. This observation is based on the
fact that string compactification on a torus provide non-trivial fluxes
(gaugings) when the twists are chosen such that the obtained torus matches the
maps arising in the Mayer-Vietoris theorem which result in entangling gates.
This observation adds new indications towards the fact that low energy
non-abelian gauge theories emerge from entanglement related phenomena.


  We study the relation between the mass accretion rate, the jet power, and the
black hole mass of blazars. To this aim, we make use of the Sloan Digital Sky
Survey (SDSS) and the 11 months catalog of blazars detected at energies larger
than 100 MeV by the Large Area Telescope (LAT) onboard the Fermi satellite.
This allows to construct a relatively large sample of blazars with information
about the luminosity (or upper limits) of their emission lines used as a proxy
for the strength of the disc luminosity and on the luminosity of the high
energy emission, used as a proxy for the jet power. We find a good correlation
between the luminosity of the broad lines and the gamma-ray luminosity as
detected by Fermi, both using absolute values of the luminosities and
normalising them to the Eddington value. The data we have analyzed confirm that
the division of blazars into BL Lacs and Flat Spectrum Radio Quasars (FSRQs) is
controlled by the line luminosity in Eddington units. For small values of this
ratio the object is a BL Lac, while it is a FSRQs for large values. The
transition appears smooth, but a much larger number of objects is needed to
confirm this point.


  We study non-perturbative effects in supersymmetric U(N) gauge theories in
eight dimensions realized by means of D(-1)/D7-brane systems with non-trivial
world-volume fluxes turned on. Using an explicit string construction in terms
of vertex operators, we derive the action for the open strings ending on the
D(-1)-branes and exhibit its BRST structure. The space of vacua for these open
strings is shown to be in correspondence with the moduli space of generalized
ADHM gauge connections which trigger the non-perturbative corrections in the
eight-dimensional theory. These corrections are computed via localization and
turn out to depend on the curved background used to localize the integrals on
the instanton moduli space, and vanish in flat space. Finally, we show that for
specific choices of the background the instanton partition functions reduce to
weighted sums of the solid partitions of the integers.


  This paper considers the robust cooperative output regulation for a network
of parabolic PDE systems. The solution of this problem is obtained by extending
the cooperative internal model principle from finite to infinite dimensions.
For a time-invariant digraph describing the communication topology, a two-step
backstepping approach is presented to systematically design cooperative state
feedback regulators. They allow to solve both the leader-follower and the
leaderless output synchronization problem in the presence of disturbances and
model uncertainty for a finite-dimensional leader. Solvability conditions of
the robust cooperative output regulation problem are presented in terms of the
communication graph and the agent transfer behaviour. The results of the paper
are demonstrated for a MAS consisting of four uncertain parabolic agents with
and without a finite-dimensional leader in the presence of disturbances.


  We give a description of finite semigroups $S$ that are minimal for not being
Malcev nilpotent, i.e. every proper subsemigroup and every proper Rees factor
semigroup is Malcev nilpotent but $S$ is not. For groups this question was
considered by Schmidt.


  With the emerging sensing technologies such as mobile crowdsensing and
Internet of Things (IoT), people-centric data can be efficiently collected and
used for analytics and optimization purposes. This data is typically required
to develop and render people-centric services. In this paper, we address the
privacy implication, optimal pricing, and bundling of people-centric services.
We first define the inverse correlation between the service quality and privacy
level from data analytics perspectives. We then present the profit maximization
models of selling standalone, complementary, and substitute services.
Specifically, the closed-form solutions of the optimal privacy level and
subscription fee are derived to maximize the gross profit of service providers.
For interrelated people-centric services, we show that cooperation by service
bundling of complementary services is profitable compared to the separate sales
but detrimental for substitutes. We also show that the market value of a
service bundle is correlated with the degree of contingency between the
interrelated services. Finally, we incorporate the profit sharing models from
game theory for dividing the bundling profit among the cooperative service
providers.


  We study relative and logarithmic characteristic cycles associated to
holonomic $\mathscr D$-modules. As applications, we obtain: (1) an alternative
proof of Ginsburg's log characteristic cycle formula for lattices of regular
holonomic $\mathscr D$-modules following ideas of Sabbah and
Briancon-Maisonobe-Merle, and (2) the constructibility of the log de Rham
complexes for lattices of holonomic $\mathscr D$-modules, which is a natural
generalization of Kashiwara's constructibility theorem.


  (Abridged) Photometry of archival Spitzer observations of the Large
Magellanic Cloud (LMC) are used to search for young stellar objects (YSOs).
Simple mid-infrared selection criteria were used to exclude most normal and
evolved stars and background galaxies. We identify a sample of 2,910 sources in
the LMC that could potentially be YSOs. We then simultaneously considered
images and photometry from the optical through mid-IR wavelengths to assess the
source morphology, spectral energy distribution (SED), and the surrounding
interstellar environment to determine the most likely nature of each source.
  From this examination of the initial sample, we suggest 1,172 sources are
most likely YSOs and 1,075 probable background galaxies, consistent with
expectations based on SWIRE survey data. Spitzer IRS observations of 269 of the
brightest YSOs from our sample have confirmed that ~>95% are indeed YSOs.
  A comprehensive search for YSOs in the LMC has also been carried out by the
SAGE team. There are three major differences between these two searches. (1) In
the common region of color-magnitude space, ~850 of our 1,172 probable YSOs are
missed in the SAGE YSO catalog because their conservative point source
identification criteria have excluded YSOs superposed on complex diffuse
emission. (2) About 20-30% of the YSOs identified by the SAGE team are sources
we classify as background galaxies. (3) the SAGE YSO catalog identifies YSO in
parts of color-magnitude space that we excluded and thus contains more evolved
or fainter YSOs missed by our analysis. Finally, the mid-IR luminosity
functions of our most likely YSO candidates in the LMC can be well described by
N(L) propto L^-1, which is consistent with the Salpeter initial mass function
if a mass-luminosity relation of L propto M^2.4 is adopted.


  Recent advances in adversarial attacks show the vulnerability of deep neural
networks searched by Neural Architecture Search (NAS). Although NAS methods can
find network architectures with the state-of-the-art performance, the
adversarial robustness and resource constraint are often ignored in NAS. To
solve this problem, we propose an Effective, Efficient, and Robust Neural
Architecture Search (E2RNAS) method to search a neural network architecture by
taking the performance, robustness, and resource constraint into consideration.
The objective function of the proposed E2RNAS method is formulated as a
bi-level multi-objective optimization problem with the upper-level problem as a
multi-objective optimization problem, which is different from existing NAS
methods. To solve the proposed objective function, we integrate the
multiple-gradient descent algorithm, a widely studied gradient-based
multi-objective optimization algorithm, with the bi-level optimization.
Experiments on benchmark datasets show that the proposed E2RNAS method can find
adversarially robust architectures with optimized model size and comparable
classification accuracy.


  We present a full vectorial first-order approach to the scattering by
arbitrary photonic structures with a low refractive index contrast. Our
approach uses the first-order Born approximation and keeps the simple
geometrical representation of the Ewald sphere construction. Via normalization
to a representative sample volume, the approach can also predict the scattering
by infinitely extended layers of scattering media. It can therefore be used to
describe and efficiently calculate the scattering by structures where the
linear first-order scattering terms dominate, e.g. in low index contrast
disordered structures creating a color impression.


  We re-consider the old problem of Brownian motion in homogeneous
high-temperature thermal environment. The semiclassical theory implies that the
diffusion coefficient does not depend on whether the thermal fluctuations are
correlated in space or disordered. We show that the corresponding quantum
analysis exhibits a remarkable breakdown of quantum-to-classical
correspondence. Explicit results are found for a tight binding model, within
the framework of an Ohmic master equation, where we distinguish between on-site
and on-bond dissipators. The breakdown is second-order in the inverse
temperature, and therefore, on the quantitative side, involves an inherent
ambiguity that is related to the Ohmic approximation scheme.


  We study coupling constants of the standard model like Higgs boson with the
gauge bosons $hZZ$ and $hWW$ and fermions $hf\bar{f}$ in the general Higgs
sector which contains higher isospin representations with arbitrary
hypercharge. In Higgs sectors with exotic Higgs representations, the $hZZ$ and
$hWW$ coupling constants can be larger than those in the standard model. We
calculate deviations in the Higgs boson couplings from standard model values in
the model with a real or complex triplet field, the Georgi-Machacek model and
the model with a septet scalar field. We also study deviations in the event
rates of $h\to ZZ^*$, $h\to WW^*$, $h\to \gamma\gamma$, $h\to b\bar{b}$ and
$h\to \tau\tau$ channels.


  Domain adaptation has been vastly investigated in computer vision but still
requires access to target images at train time, which might be intractable in
some uncommon conditions. In this paper, we propose the task of `Prompt-driven
Zero-shot Domain Adaptation', where we adapt a model trained on a source domain
using only a general description in natural language of the target domain,
i.e., a prompt. First, we leverage a pretrained contrastive vision-language
model (CLIP) to optimize affine transformations of source features, steering
them towards the target text embedding while preserving their content and
semantics. To achieve this, we propose Prompt-driven Instance Normalization
(PIN). Second, we show that these prompt-driven augmentations can be used to
perform zero-shot domain adaptation for semantic segmentation. Experiments
demonstrate that our method significantly outperforms CLIP-based style transfer
baselines on several datasets for the downstream task at hand, even surpassing
one-shot unsupervised domain adaptation. A similar boost is observed on object
detection and image classification. The code is available at
https://github.com/astra-vision/PODA .


  Scattered light images of transition discs in the near-infrared often show
non-axisymmetric structures in the form of wide-open spiral arms in addition to
their characteristic low-opacity inner gap region. We study self-gravitating
discs and investigate the influence of gravitational instability on the shape
and contrast of spiral arms induced by planet-disc interactions.
Two-dimensional non-isothermal hydrodynamical simulations including viscous
heating and a cooling prescription are combined with three-dimensional dust
continuum radiative transfer models for direct comparison to observations. We
find that the resulting contrast between the spirals and the surrounding disc
in scattered light is by far higher for pressure scale height variations, i.e.
thermal perturbations, than for pure surface density variations. Self-gravity
effects suppress any vortex modes and tend to reduce the opening angle of
planet-induced spirals, making them more tightly wound. If the disc is only
marginally gravitationally stable with a Toomre parameter around unity, an
embedded massive planet (planet-to-star mass ratio of $10^{-2}$) can trigger
gravitational instability in the outer disc. The spirals created by this
instability and the density waves launched by the planet can overlap resulting
in large-scale, more open spiral arms in the outer disc. The contrast of these
spirals is well above the detection limit of current telescopes.


  Verlinde (2016) proposed that the observed excess gravity in galaxies and
clusters is the consequence of Emergent Gravity (EG). In this theory the
standard gravitational laws are modified on galactic and larger scales due to
the displacement of dark energy by baryonic matter. EG gives an estimate of the
excess gravity (described as an apparent dark matter density) in terms of the
baryonic mass distribution and the Hubble parameter. In this work we present
the first test of EG using weak gravitational lensing, within the regime of
validity of the current model. Although there is no direct description of
lensing and cosmology in EG yet, we can make a reasonable estimate of the
expected lensing signal of low redshift galaxies by assuming a background
LambdaCDM cosmology. We measure the (apparent) average surface mass density
profiles of 33,613 isolated central galaxies, and compare them to those
predicted by EG based on the galaxies' baryonic masses. To this end we employ
the ~180 square degrees overlap of the Kilo-Degree Survey (KiDS) with the
spectroscopic Galaxy And Mass Assembly (GAMA) survey. We find that the
prediction from EG, despite requiring no free parameters, is in good agreement
with the observed galaxy-galaxy lensing profiles in four different stellar mass
bins. Although this performance is remarkable, this study is only a first step.
Further advancements on both the theoretical framework and observational tests
of EG are needed before it can be considered a fully developed and solidly
tested theory.


  In this contribution we identify two scenarios for the evolutionary branch
cut universe. In the first scenario, the universe evolves continuously from the
negative complex cosmological time sector, prior to a primordial singularity,
to the positive one, circumventing continuously a branch cut, and no primordial
singularity occurs in the imaginary sector, only branch points. In the second
scenario, the branch cut and branch point disappear after the realisation of
the imaginary component of the complex time by means of a Wick rotation, which
is replaced by the thermal time. In the second scenario, the universe has its
origin in the Big Bang, but the model contemplates simultaneously a mirrored
parallel evolutionary universe going backwards in the cosmological thermal time
negative sector. A quantum formulation based on the WDW equation is sketched
and preliminary conclusions are drawn.


  Intrusive uncertainty quantification methods for hyperbolic problems exhibit
spurious oscillations at shocks, which leads to a significant reduction of the
overall approximation quality. Furthermore, a challenging task is to preserve
hyperbolicity of the gPC moment system. An intrusive method which guarantees
hyperbolicity is the intrusive polynomial moment (IPM) method, which performs
the gPC expansion on the entropy variables. The method, while still being
subject to oscillations, requires solving a convex optimization problem in
every spatial cell and every time step. The aim of this work is to mitigate
oscillations in the IPM solution by applying filters. Filters reduce
oscillations by damping high order gPC coefficients. Naive filtering, however,
may lead to unrealizable moments, which means that the IPM optimization problem
does not have a solution and the method breaks down. In this paper, we propose
and analyze two separate strategies to guarantee the existence of a solution to
the IPM problem. First, we propose a filter which maintains realizability by
being constructed from an underlying Fokker-Planck equation. Second, we
regularize the IPM optimization problem to be able to cope with non-realizable
gPC coefficients. Consequently, standard filters can be applied to the
regularized IPM method. We demonstrate numerical results for the two strategies
by investigating the Euler equations with uncertain shock structures in one-
and two-dimensional spatial settings. We are able to show a significant
reduction of spurious oscillations by the proposed filters.


  We present an M_V absolute magnitude calibration including the B-V colour and
[Fe/H] metallicity for the red clump stars in the globular and open clusters
with a wide range of metallicities: M_V =
0.627(0.104)(B-V)o+0.046(0.043)[Fe/H]+0.262(0.111). The calibration equation is
valid in the ranges 0.42<(B-V)o<1.20 mag, -1.55<[Fe/H]<+0.40 dex and
0.43<M_V<1.03 mag. We found that the consistencies in the comparisons of the
distances estimated from the calibration equation in this study both with the
distances obtained from trigonometric parallaxes and spectrophotometric
analysis demonstrate that reliable precise absolute magnitudes for the clump
giants can be estimated from the calibration formula.


  The ability to reliably perceive the environmental states, particularly the
existence of objects and their motion behavior, is crucial for autonomous
driving. In this work, we propose an efficient deep model, called MotionNet, to
jointly perform perception and motion prediction from 3D point clouds.
MotionNet takes a sequence of LiDAR sweeps as input and outputs a bird's eye
view (BEV) map, which encodes the object category and motion information in
each grid cell. The backbone of MotionNet is a novel spatio-temporal pyramid
network, which extracts deep spatial and temporal features in a hierarchical
fashion. To enforce the smoothness of predictions over both space and time, the
training of MotionNet is further regularized with novel spatial and temporal
consistency losses. Extensive experiments show that the proposed method overall
outperforms the state-of-the-arts, including the latest scene-flow- and
3D-object-detection-based methods. This indicates the potential value of the
proposed method serving as a backup to the bounding-box-based system, and
providing complementary information to the motion planner in autonomous
driving. Code is available at https://github.com/pxiangwu/MotionNet.


  In this paper, we prove the conic version of YTD conjecture on log Fano
manifolds.


  With the increasing demand for computing capability given limited resource
and power budgets, it is crucial to deploy applications to customized
accelerators like FPGAs. However, FPGA programming is non-trivial. Although
existing high-level synthesis (HLS) tools improve productivity to a certain
extent, they are limited in scope and capability to support sufficient
FPGA-oriented optimizations. This paper focuses on FPGA-based accelerators and
proposes POM, an optimizing framework built on multi-level intermediate
representation (MLIR). POM has several features which demonstrate its scope and
capability of performance optimization. First, most HLS tools depend
exclusively on a single-level IR to perform all the optimizations, introducing
excessive information into the IR and making debugging an arduous task. In
contrast, POM introduces three layers of IR to perform operations at suitable
abstraction levels, streamlining the implementation and debugging process and
exhibiting better flexibility, extensibility, and systematicness. Second, POM
integrates the polyhedral model into MLIR, enabling advanced dependence
analysis and various FPGA-oriented loop transformations. By representing nested
loops with integer sets and maps, loop transformations can be conducted
conveniently through manipulations on polyhedral semantics. Finally, to further
relieve design effort, POM has a user-friendly programming interface (DSL) that
allows a concise description of computation and includes a rich collection of
scheduling primitives. An automatic design space exploration (DSE) engine is
provided to search for high-performance optimization schemes efficiently and
generate optimized accelerators automatically. Experimental results show that
POM achieves a $6.46\times$ average speedup on typical benchmark suites and a
$6.06\times$ average speedup on real-world applications compared to the
state-of-the-art.


  We study scalar QCD at nonzero density in the strong coupling limit. It has a
sign problem which looks structurally similar to the one in QCD. We show first
data for the reweighting factor. After introducing dual variables by
integrating out the SU(3) gauge links, we find that at least 3 flavors are
needed for a nontrivial dependence on the chemical potential. In this dual
representation there is no sign problem remaining. The dual variables are
partially constrained, thus we propose to use a hybrid approach for the
updates: For unconstrained variables local updates can be used, while for
constrained variables using updates based on the worm algorithm is more
promising.


  We study a new dark sector signature for an atomic process of "rearrangement"
in the galaxy. In this process, a hydrogen-like atomic dark matter state
together with its anti-particle can rearrange to form a highly-excited bound
state. This bound state will then de-excite into the ground state emitting a
large number of dark photons that can be measured in experiments on Earth
through their kinetic mixing with the photon. We find that for DM masses in the
GeV range, the dark photons have enough energy to pass the thresholds of
neutrino observatories such as Borexino and Super-Kamiokande that can probe for
our scenario even when our atomic states constitute a small fraction of the
total DM abundance. We study the corresponding bounds on the parameters of our
model from current data as well as the prospects for future detectors.


  This article describes high-speed multiprocessor architecture for the
concurrent analyzing information represented in analytic, graph- and table
forms of associative relations to search, recognize and make a decision in
n-dimensional vector discrete space. Vector-logical process models of actual
applications,for which the quality of solution is estimated by the proposed
integral non-arithmetical metric of the interaction between Boolean vectors,
are described.


  We investigate the synchronization transition of the Shinomoto-Kuramoto model
on networks of the fruit-fly and two large human connectomes. This model
contains a force term, thus is capable of describing critical behavior in the
presence of external excitation. By numerical solution we determine the
crackling noise durations with and without thermal noise and show extended
non-universal scaling tails characterized by $2< \tau_t < 2.8$, in contrast
with the Hopf transition of the Kuramoto model, without the force
$\tau_t=3.1(1)$. Comparing the phase and frequency order parameters we find
different transition points and fluctuations peaks as in case of the Kuramoto
model. Using the local order parameter values we also determine the Hurst
(phase) and $\beta$ (frequency) exponents and compare them with recent
experimental results obtained by fMRI. We show that these exponents,
characterizing the auto-correlations are smaller in the excited system than in
the resting state and exhibit module dependence.


  Stable ultrashort light pulses and frequency combs generated by mode-locked
lasers have many important applications including high-resolution spectroscopy,
fast chemical detection and identification, studies of ultrafast processes, and
laser metrology. While compact mode-locked lasers emitting in the visible and
near infrared range have revolutionized photonic technologies, the systems
operating in the mid-infrared range where most gases have their strong
absorption lines, are bulky and expensive and rely on nonlinear frequency
down-conversion. Quantum cascade lasers are the most powerful and versatile
compact light sources in the mid-infrared range, yet achieving their mode
locked operation remains a challenge despite dedicated effort. Here we report
the first demonstration of active mode locking of an external-cavity quantum
cascade laser. The laser operates in the mode-locked regime at room temperature
and over the full dynamic range of injection currents of a standard commercial
laser chip.


  The observation of the Hawking effect from black holes in the astrophysical
context is unlikely. However, the analog of this effect is present in condensed
matter systems. We focus on Bose-Einstein condensates, and on a proposal to
detect it through correlation measurements.


  In this paper we discuss massive gravity in de Sitter space via gravitational
Higgs mechanism, which provides a nonlinear definition thereof. The Higgs
scalars are described by a nonlinear sigma model, which includes higher
derivative terms required to obtain the Fierz-Pauli mass term. Using the
aforesaid non-perturbative definition, we address appearance of an enhanced
local symmetry and a null norm state in the linearized massive gravity in de
Sitter space at the special value of the graviton mass to the Hubble parameter
ratio. By studying full non-perturbative equations of motion, we argue that
there is no enhanced symmetry in the full nonlinear theory. We then argue that
in the full nonlinear theory no null norm state is expected to arise at the
aforesaid special value. This suggests that no ghost might be present for lower
graviton mass values and the full nonlinear theory might be unitary for all
values of the graviton mass and the Hubble parameter with no van
Dam-Veltman-Zakharov discontinuity. We argue that this is indeed the case by
studying full nonlinear Hamiltonian for the relevant conformal and helicity-0
longitudinal modes. In particular, we argue that no negative norm state is
present in the full nonlinear theory.


  We investigate the problem of privately recovering a single erasure for
Reed-Solomon codes with low communication bandwidths. For an $[n,k]_{q^\ell}$
code with $n-k\geq q^{m}+t-1$, we construct a repair scheme that allows a
client to recover an arbitrary codeword symbol without leaking its index to any
set of $t$ colluding helper nodes at a repair bandwidth of $(n-1)(\ell-m)$
sub-symbols in $\mathbb{F}_q$. When $t=1$, this reduces to the bandwidth of
existing repair schemes based on subspace polynomials. We prove the optimality
of the proposed scheme when $n=q^\ell$ under a reasonable assumption about the
schemes being used. Our private repair scheme can also be transformed into a
private retrieval scheme for data encoded by Reed-Solomon codes.


  We prove that every del Pezzo surface of degree two over a finite field is
unirational, building on the work of Manin and an extension by Salgado, Testa,
and V\'arilly-Alvarado, who had proved this for all but three surfaces. Over
general fields, we state several sufficient conditions for a del Pezzo surface
of degree two to be unirational.


  Road transportation is one of the largest sectors of greenhouse gas (GHG)
emissions affecting climate change. Tackling climate change as a global
community will require new capabilities to measure and inventory road transport
emissions. However, the large scale and distributed nature of vehicle emissions
make this sector especially challenging for existing inventory methods. In this
work, we develop machine learning models that use satellite imagery to perform
indirect top-down estimation of road transport emissions. Our initial
experiments focus on the United States, where a bottom-up inventory was
available for training our models. We achieved a mean absolute error (MAE) of
39.5 kg CO$_{2}$ of annual road transport emissions, calculated on a
pixel-by-pixel (100 m$^{2}$) basis in Sentinel-2 imagery. We also discuss key
model assumptions and challenges that need to be addressed to develop models
capable of generalizing to global geography. We believe this work is the first
published approach for automated indirect top-down estimation of road transport
sector emissions using visual imagery and represents a critical step towards
scalable, global, near-real-time road transportation emissions inventories that
are measured both independently and objectively.


  Basing on the work of Pellegrino et al. on factorable strongly p-summing
multilinear operators, we will continue study this class of operators and
borrowing the same idea for the category of p-nuclear operators. Therefore, we
will construct other multilinear and polynomial ideals for which the most
valuable results of the theory of p-nuclear linear operators are available,
namely the Pietsch domination theorem and the well known factorization given by
Cohen and Kwapien for p-nuclear operators.


  We report detection of quasi-periodic (1.5 day) dimming of HD 240779, the
solar-mass primary in a 5" visual binary (also TIC 284730577), by the
Transiting Exoplanet Survey Satellite. This dimming, as has been shown for
other "dipper" stars, is likely due to occultation by circumstellar dust. The
barycentric space motion, lithium abundance, rotation, and chromospheric
emission of the stars in this system point to an age of ~125 Myr, and possible
membership in the AB Doradus moving group. As such it occupies an important but
poorly explored intermediate regime of stars with transient dimming between
young stellar objects in star forming regions and main sequence stars, and
between UX Orionis-type Ae/Be stars and M-type "dippers". HD 240779, but not
its companion BD+10714B, has WISE-detected excess infrared emission at 12 and
22 microns indicative of circumstellar dust. We propose that infrared emission
is produced by collisions of planetesimals during clearing of a residual disk
at the end of rocky planet formation, and that quasi-periodic dimming is
produced by the rapid disintegration of a 100 km planetesimal near the silicate
evaporation radius. Further studies of this and similar systems will illuminate
a poorly understood final phase of rocky planet formation like that which
produced the inner Solar System.


  Superconductivity develops from an attractive interaction between itinerant
electrons that creates electron pairs which condense into a macroscopic quantum
state--the superconducting state. On the other hand, magnetic order in a metal
arises from electrons localized close to the ionic core and whose interaction
is mediated by itinerant electrons. The dichotomy between local moment magnetic
order and superconductivity raises the question of whether these two states can
coexist and involve the same electrons. Here we show that the single
4f-electron of cerium in CeRhIn5 simultaneously produces magnetism,
characteristic of localization, and superconductivity that requires itinerancy.
The dual nature of the 4f-electron allows microscopic coexistence of
antiferromagnetic order and superconductivity whose competition is tuned by
small changes in pressure and magnetic field. Electronic duality contrasts with
conventional interpretations of coexisting spin-density magnetism and
superconductivity and offers a new avenue for understanding complex states in
classes of materials.


  To achieve reliable mining results for massive vessel trajectories, one of
the most important challenges is how to efficiently compute the similarities
between different vessel trajectories. The computation of vessel trajectory
similarity has recently attracted increasing attention in the maritime data
mining research community. However, traditional shape- and warping-based
methods often suffer from several drawbacks such as high computational cost and
sensitivity to unwanted artifacts and non-uniform sampling rates, etc. To
eliminate these drawbacks, we propose an unsupervised learning method which
automatically extracts low-dimensional features through a convolutional
auto-encoder (CAE). In particular, we first generate the informative trajectory
images by remapping the raw vessel trajectories into two-dimensional matrices
while maintaining the spatio-temporal properties. Based on the massive vessel
trajectories collected, the CAE can learn the low-dimensional representations
of informative trajectory images in an unsupervised manner. The trajectory
similarity is finally equivalent to efficiently computing the similarities
between the learned low-dimensional features, which strongly correlate with the
raw vessel trajectories. Comprehensive experiments on realistic data sets have
demonstrated that the proposed method largely outperforms traditional
trajectory similarity computation methods in terms of efficiency and
effectiveness. The high-quality trajectory clustering performance could also be
guaranteed according to the CAE-based trajectory similarity computation
results.


  We report on an 105 ks Suzaku observation of the supernova remnant CTA 1
(G119.5+10.2). The Suzaku soft X-ray observation was carried out with both
timing mode and imaging mode. A ~ 10' extended feature, which is interpreted as
a bow-shock component of the pulsar wind nebula (PWN), is revealed in this deep
observation for the first time. The nebular spectrum can be modelled by a
power-law with a photon index of ~ 1.8 which suggests a slow synchrotron
cooling scenario. The photon index is approximately constant across this
extended feature. We compare and discuss our observations of this complex
nebula with previous X-ray investigations. We do not obtain any significant
pulsation from the central pulsar in the soft (0.2-12 keV) and hard (10-60 keV)
X-ray data. The non-detection is mainly due to the loss of the precise imaging
ability to accurately determine the source contribution. The spectra of XIS and
HXD can be directly connected without a significant spectral break according to
our analysis. Future observations of NuSTAR and Astro-H would be able to
resolve the contamination and provide an accurate hard X-ray measurement of CTA
1.


  Atmospheric haze is the leading candidate for the flattening of expolanetary
spectra, as it's also an important source of opacity in the atmospheres of
solar system planets, satellites, and comets. Exoplanetary transmission
spectra, which carry information about how the planetary atmospheres become
opaque to stellar light in transit, show broad featureless absorption in the
region of wavelengths corresponding to spectral lines of sodium, potassium and
water. We develop a detailed atomistic model, describing interactions of atomic
or molecular radiators with dust and atmospheric haze particulates. This model
incorporates a realistic structure of haze particulates from small nano-size
seed particles up to sub-micron irregularly shaped aggregates, accounting for
both pairwise collisions between the radiator and haze perturbers, and
quasi-static mean field shift of levels in haze environments. This formalism
can explain large flattening of absorption and emission spectra in haze
atmospheres and shows how the radiator - haze particle interaction affects the
absorption spectral shape in the wings of spectral lines and near their
centers. The theory can account for nearly all realistic structure, size and
chemical composition of haze particulates and predict their influence on
absorption and emission spectra in hazy environments. We illustrate the utility
of the method by computing shift and broadening of the emission spectra of the
sodium D line in an argon haze. The simplicity, elegance and generality of the
proposed model should make it amenable to a broad community of users in
astrophysics and chemistry.


  Examples of test electromagnetic waves on a
Friedmann-Lemaitre-Robertson-Walker(FLRW) background are constructed from
explicit perturbations of the FLRW space-times describing gravitational waves
propagating in the isotropic universes. A possible physical mechanism for the
production of the test electromagnetic waves is shown to be the coupling of the
gravitational waves with a test magnetic field, confirming the observation of
Marklund, Dunsby and Brodin [Phys.Rev. D62,101501(R) (2000)].


  Humans constantly interact with daily objects to accomplish tasks. To
understand such interactions, computers need to reconstruct these from cameras
observing whole-body interaction with scenes. This is challenging due to
occlusion between the body and objects, motion blur, depth/scale ambiguities,
and the low image resolution of hands and graspable object parts. To make the
problem tractable, the community focuses either on interacting hands, ignoring
the body, or on interacting bodies, ignoring hands. The GRAB dataset addresses
dexterous whole-body interaction but uses marker-based MoCap and lacks images,
while BEHAVE captures video of body object interaction but lacks hand detail.
We address the limitations of prior work with InterCap, a novel method that
reconstructs interacting whole-bodies and objects from multi-view RGB-D data,
using the parametric whole-body model SMPL-X and known object meshes. To tackle
the above challenges, InterCap uses two key observations: (i) Contact between
the hand and object can be used to improve the pose estimation of both. (ii)
Azure Kinect sensors allow us to set up a simple multi-view RGB-D capture
system that minimizes the effect of occlusion while providing reasonable
inter-camera synchronization. With this method we capture the InterCap dataset,
which contains 10 subjects (5 males and 5 females) interacting with 10 objects
of various sizes and affordances, including contact with the hands or feet. In
total, InterCap has 223 RGB-D videos, resulting in 67,357 multi-view frames,
each containing 6 RGB-D images. Our method provides pseudo ground-truth body
meshes and objects for each video frame. Our InterCap method and dataset fill
an important gap in the literature and support many research directions. Our
data and code are areavailable for research purposes.


  Most reinforcement learning methods operate on propositional representations
of the world state. Such representations are often intractably large and
generalize poorly. Using a deictic representation is believed to be a viable
alternative: they promise generalization while allowing the use of existing
reinforcement-learning methods. Yet, there are few experiments on learning with
deictic representations reported in the literature. In this paper we explore
the effectiveness of two forms of deictic representation and a na\"{i}ve
propositional representation in a simple blocks-world domain. We find,
empirically, that the deictic representations actually worsen learning
performance. We conclude with a discussion of possible causes of these results
and strategies for more effective learning in domains with objects.


  Analytical treatment of premixed flame propagation in vertical tubes with
smooth walls is given. Using the on-shell flame description, equations
describing quasi-steady flame with a small but finite front thickness are
obtained and solved numerically. It is found that near the limits of
inflammability, solutions describing upward flame propagation come in pairs
having close propagation speeds, and that the effect of gravity is to reverse
the burnt gas velocity profile generated by the flame. On the basis of these
results, a theory of partial flame propagation driven by the gravitational
field is developed. A complete explanation is given of the intricate observed
behavior of limit flames, including dependence of the inflammability range on
the size of the combustion domain, the large distances of partial flame
propagation, and the progression of flame extinction. The role of the finite
front-thickness effects is discussed in detail. Also, various mechanisms
governing flame acceleration in smooth tubes are identified. Acceleration of
methane-air flames in open tubes is shown to be a combined effect of the
hydrostatic pressure difference produced by the ambient cold air and the
difference of dynamic gas pressure at the tube ends. On the other hand, a
strong spontaneous acceleration of the fast methane-oxygen flames at the
initial stage of their evolution in open-closed tubes is conditioned by
metastability of the quasi-steady propagation regimes. An extensive comparison
of the obtained results with the experimental data is made.


  We show that there exists an uniformly recurrent infinite word whose set of
factors is closed under reversal and which has only finitely many palindromic
factors.


  Quantum computers currently rely on a hybrid quantum-classical approach known
as Variational Quantum Algorithms (VQAs) to solve problems. Still, there are
several challenges with VQAs on the classical computing side: it corresponds to
a black-box optimization problem that is generally non-convex, the observations
from the quantum hardware are noisy, and the quantum computing time is
expensive. The first point is inherent to the problem structure; as a result,
it requires the classical part of VQAs to be solved using global optimization
strategies. However, there is a trade-off between cost and accuracy; typically,
quantum computers return a set of bit strings, where each bitstring is referred
to as a shot. The probabilistic nature of quantum computing (QC) necessitates
many shots to measure the circuit accurately. Since QC time is charged per
shot, reducing the number of shots yields cheaper and less accurate
observations. Recently, there has been increasing interest in using basic
Bayesian optimization (BO) methods to globally optimize quantum circuit
parameters. This work proposes two modifications to the basic BO framework to
provide a shot-efficient optimization strategy for VQAs. Specifically, we
provide a means to place a prior on the periodicity of the rotation angles and
a framework to place a topological prior using few-shot quantum circuit
observations. We demonstrate the effectiveness of our proposed approach through
an ablation study, showing that using both proposed features statistically
outperforms a standard BO implementation within VQAs for computational
chemistry simulations.


  This report studies the emergent behavior of systems of agents performing
cyclic pursuit controlled by an external broadcast signal detected by a random
set of the agents. Two types of cyclic pursuit are analyzed: 1)linear cyclic
pursuit, where each agent senses the relative position of its target or leading
agent 2)non-linear cyclic pursuit, where the agents can sense only bearing to
their leading agent and colliding agents merge and continue on the path of the
pursued agent (a so-called "bugs" model). Cyclic pursuit is, in both cases, a
gathering algorithm, which has been previously analyzed. The novelty of our
work is the derivation of emergent behaviours, in both linear and non-linear
cyclic pursuit, in the presence of an exogenous broadcast control detected by a
random subset of agents. We show that the emergent behavior of the swarm
depends on the type of cyclic pursuit. In the linear case, the agents
asymptotically align in the desired direction and move with a common speed
which is a proportional to the ratio of the number of agents detecting the
broadcast control to the total number of agents in the swarm, for any magnitude
of input (velocity) signal. In the non-linear case, the agents gather and move
with a shared velocity, which equals the input velocity signal, independently
of the number of agents detecting the broadcast signal.


  We continue our investigation of the two-dimensional Abelian sandpile model
in terms of a logarithmic conformal field theory with central charge c=-2, by
introducing two new boundary conditions. These have two unusual features: they
carry an intrinsic orientation, and, more strangely, they cannot be imposed
uniformly on a whole boundary (like the edge of a cylinder). They lead to seven
new boundary condition changing fields, some of them being in highest weight
representations (weights -1/8, 0 and 3/8), some others belonging to
indecomposable representations with rank 2 Jordan cells (lowest weights 0 and
1). Their fusion algebra appears to be in full agreement with the fusion rules
conjectured by Gaberdiel and Kausch.


  A forward amplitude analysis on $pp$ and $\bar{p}p$ elastic scattering above
5 GeV is presented. The dataset includes the recent high-precision TOTEM
measurements of the $pp$ total and elastic (integrated) cross-sections at 7 TeV
and 8 TeV. Following previous works, the leading high-energy contribution for
the total cross-section ($\sigma_{tot}$) is parametrized as
$\ln^{\gamma}(s/s_h)$, where $\gamma$ and $s_h$ are free \textit{real} fit
parameters. Singly-subtracted derivative dispersion relations are used to
connect $\sigma_{tot}$ and the rho parameter ($\rho$) in an analytical way.
Different fit procedures are considered, including individual fits to
$\sigma_{tot}$ data, global fits to $\sigma_{tot}$ and $\rho$ data, constrained
and unconstrained data reductions. The results favor a rise of the
$\sigma_{tot}$ faster than the log-squared bound by Froissart and Martin at the
LHC energy region. The parametrization for $\sigma_{tot}$ is extended to fit
the elastic cross-section ($\sigma_{el}$) data with satisfactory results. The
analysis indicates an asymptotic ratio $\sigma_{el}/\sigma_{tot}$ consistent
with 1/3 (as already obtained in a previous work). A critical discussion on the
correlation, practical role and physical implications of the parameters
$\gamma$ and $s_h$ is presented. The discussion confronts the 2002 prediction
of $\sigma_{tot}$ by the COMPETE Collaboration and the recent result by the
Particle Data Group (2012 edition of the Review of Particle Physics). Some
conjectures on possible implications of a fast rise of the proton-proton total
cross-section at the highest energies are also presented.


  Strain-gradient theories of plasticity have been successful in modeling the
behavior of complex materials. However, the traditional formulation of these
theories lacks a material length scale, and is thus incapable of capturing
experimentally observed size effects that play an important role in the
behavior of nano structures. As a result, a modified theory was proposed which
incorporates an intrinsic dissipative length scale. The theory predicts that
the solutions to the flow rule are global minimizers of the functional for
energy dissipation. We prove that there are no global minimizers of the
functional, thus resolving a previously unsolved conjecture. Our result shows
that the variational formulation of the theory is unviable. The non-existence
of a global minimizer appears to be related to the formation of infinitely fine
plastic boundary layers.


  Training deep neural networks requires massive amounts of training data, but
for many tasks only limited labeled data is available. This makes weak
supervision attractive, using weak or noisy signals like the output of
heuristic methods or user click-through data for training. In a semi-supervised
setting, we can use a large set of data with weak labels to pretrain a neural
network and then fine-tune the parameters with a small amount of data with true
labels. This feels intuitively sub-optimal as these two independent stages
leave the model unaware about the varying label quality. What if we could
somehow inform the model about the label quality? In this paper, we propose a
semi-supervised learning method where we train two neural networks in a
multi-task fashion: a "target network" and a "confidence network". The target
network is optimized to perform a given task and is trained using a large set
of unlabeled data that are weakly annotated. We propose to weight the gradient
updates to the target network using the scores provided by the second
confidence network, which is trained on a small amount of supervised data. Thus
we avoid that the weight updates computed from noisy labels harm the quality of
the target network model. We evaluate our learning strategy on two different
tasks: document ranking and sentiment classification. The results demonstrate
that our approach not only enhances the performance compared to the baselines
but also speeds up the learning process from weak labels.


  While multilingual language models (MLMs) have been trained on 100+
languages, they are typically only evaluated across a handful of them due to a
lack of available test data in most languages. This is particularly problematic
when assessing MLM's potential for low-resource and unseen languages. In this
paper, we present an analysis of existing evaluation frameworks in multilingual
NLP, discuss their limitations, and propose several directions for more robust
and reliable evaluation practices. Furthermore, we empirically study to what
extent machine translation offers a {reliable alternative to human translation}
for large-scale evaluation of MLMs across a wide set of languages. We use a
SOTA translation model to translate test data from 4 tasks to 198 languages and
use them to evaluate three MLMs. We show that while the selected subsets of
high-resource test languages are generally sufficiently representative of a
wider range of high-resource languages, we tend to overestimate MLMs' ability
on low-resource languages. Finally, we show that simpler baselines can achieve
relatively strong performance without having benefited from large-scale
multilingual pretraining.


  In the first part of this article we present some exact solutions for special
hyperbolic-parabolic systems with sustained oscillations induced by the initial
data, most notably the compressible Navier-Stokes system with non-monotone
pressure. This part complements \cite{Tzavaras23} where such examples are
extensively studied. The second part deals with the problem of homogenization
for one-dimensional models describing phase transitions for viscoelastic
materials . Ideas from the kinetic formulation of conservation laws are
employed to derive effective equations that describe the propagation of
oscillations.


  The Lagrangian formalism for the N=2 supersymmetric sinh-Gordon model with a
jump defect is considered. The modified conserved momentum and energy are
constructed in terms of border functions. The supersymmetric Backlund
transformation is given and an one-soliton solution is obtained.
  The Lax formulation based on the affine super Lie algebra $sl(2,2)$ within
the space split by the defect leads to the integrability of the model and
henceforth to the existence of an infinite number of constants of motion.


  We demonstrate how exact structures can be placed on the additive category of
right operator modules over an operator algebra in order to discuss global
dimension for operator algebras. The properties of the Haagerup tensor product
play a decisive role in this.


  Sentiment Analysis (SA) is an indispensable task for many real-world
applications. Compared to limited resourced languages (i.e., Arabic, Bengali),
most of the research on SA are conducted for high resourced languages (i.e.,
English, Chinese). Moreover, the reasons behind any prediction of the Arabic
sentiment analysis methods exploiting advanced artificial intelligence
(AI)-based approaches are like black-box - quite difficult to understand. This
paper proposes an explainable sentiment classification framework for the Arabic
language by introducing a noise layer on Bi-Directional Long Short-Term Memory
(BiLSTM) and Convolutional Neural Networks (CNN)-BiLSTM models that overcome
over-fitting problem. The proposed framework can explain specific predictions
by training a local surrogate explainable model to understand why a particular
sentiment (positive or negative) is being predicted. We carried out experiments
on public benchmark Arabic SA datasets. The results concluded that adding noise
layers improves the performance in sentiment analysis for the Arabic language
by reducing overfitting and our method outperformed some known state-of-the-art
methods. In addition, the introduced explainability with noise layer could make
the model more transparent and accountable and hence help adopting AI-enabled
system in practice.


  Next-nearest-neighbor Heisenberg chain plays important roles in solid state
physics, such as predicting exotic electric properties of two-dimensional
materials or magnetic properties of organic compounds. Direct experimental
studies of the many-body electron systems or spin systems associating to these
materials are challenging tasks, while optical simulation provides an effective
and economical way for immediate observation. Comparing with bulk optics,
integrated optics are more of fascinating for steady, large scale and long-time
evolution simulations. Photonic crystal is an artificial microstructure
material with multiple methods to tune the propagation properties, which are
essential for various simulation tasks. Here we report for the first time an
experimental simulation of next-nearest-neighbor Heisenberg chain with an
integrated optical chip of photonic crystal waveguide array. The use of
photonic crystal enhances evanescent field thus allows coupling between
next-nearest-neighbor waveguides in such a planar waveguide array, without
breaking the weak coupling condition of the coupled mode equation.
Particularly, similarities between the model and coherent light propagation
could reach 0.99 in numerical simulations and 0.89 in experiment. Localization
effect induced by second-order coupling and coupling strengthening with
increasing wavelengths were also revealed in both numerical simulations and
experiments. The platform proposed here is compatible with mature complementary
metal oxide semiconductor technology thus possesses the potential for
larger-scale problems and photonic crystals further allows simulations of
specific target Hamiltonians.


  We prove a compactness and integral-representation theorem for sequences of
families of lattice energies describing atomistic interactions defined on
lattices with vanishing lattice spacing. The densities of these energies may
depend on interactions between all points of the corresponding lattice
contained in a reference set. We give conditions that ensure that the limit is
an integral defined on a Sobolev space. A homogenization theorem is also
proved. The result is applied to multibody interactions corresponding to
discrete Jacobian determinants and to linearizations of Lennard-Jones energies
with mixtures of convex and concave quadratic pair-potentials.


  We introduce a novel approach to graph-level representation learning, which
is to embed an entire graph into a vector space where the embeddings of two
graphs preserve their graph-graph proximity. Our approach, UGRAPHEMB, is a
general framework that provides a novel means to performing graph-level
embedding in a completely unsupervised and inductive manner. The learned neural
network can be considered as a function that receives any graph as input,
either seen or unseen in the training set, and transforms it into an embedding.
A novel graph-level embedding generation mechanism called Multi-Scale Node
Attention (MSNA), is proposed. Experiments on five real graph datasets show
that UGRAPHEMB achieves competitive accuracy in the tasks of graph
classification, similarity ranking, and graph visualization.


  In the present work, we investigate the possibility of obtaining stellar
interiors for static self-gravitating systems describing an anisotropic matter
distribution in the framework of Rastall gravity through gravitational
decoupling by means of minimal geometric deformation approach. Due to Rastall
gravity breaks down the minimal coupling matter principle, we have provided an
exhaustive explanation about how Israel-Darmois junction conditions work in
this scenario. Furthermore, to obtain the deformed space-time, the mimic
constraint procedure has been used. In order to check the viability of this
proposal, we have applied it to the well known Tolman IV solution. A complete
thermodynamic description of the effects introduced by the additional source is
given. Additionally, the results have been compared with their similes in the
picture of pure general relativity, pure Rastall gravity and within the
framework of general relativity including gravitational decoupling. To perform
the mathematical and graphical analysis we have taken the gravitational
decoupling constant $\alpha$ and the Rastall's parameter $\lambda$ as free
parameters and the compactness factor describing the general relativity sector
to be $0.2$. Besides, to provide a more realistic picture we have bounded both
parameters $\alpha$ and $\lambda$ by using real observational data to explore
the limits of the theory under this particular model. Applications to study
neutron or quark stars are suggested by using this methodology.


  A data tree is a finite tree whose every node carries a label from a finite
alphabet and a datum from some infinite domain. We introduce a new model of
automata over unranked data trees with a decidable emptiness problem. It is
essentially a bottom-up alternating automaton with one register that can store
one data value and can be used to perform equality tests with the data values
occurring within the subtree of the current node. We show that it captures the
expressive power of the vertical fragment of XPath - containing the child,
descendant, parent and ancestor axes - obtaining thus a decision procedure for
its satisfiability problem.


  We have carried out in ferritin the Field-Cooling method and data analysis
proposed by Mamiya et al. (Phys. Rev. Lett. 88, 67202 (2002) at T = 5 K in
order to check the time magnetic relaxation of these antiferromagnetic
nanoparticles as a function of the magnetic field. We found that relaxation at
T = 5 K in ferritin is faster in the absence of magnetic field, in good
agreement with the zero-field Resonant Spin Quantum Tunneling observed
previously in ferritin (Phys. Rev. Lett. 79, 1754 (1997).


  Resource allocation problems are a family of problems in which resources must
be selected to satisfy given demands. This paper focuses on the two-stage
stochastic generalization of resource allocation problems where future demands
are expressed in a finite number of possible scenarios. The goal is to select
cost effective resources to be acquired in the present time (first stage), and
to implement a complete solution for each scenario (second stage), while
minimizing the total expected cost of the choices in both stages.
  We propose an evolutionary framework for solving general two-stage stochastic
resource allocation problems. In each iteration of our framework, a local
search algorithm selects resources to be acquired in the first stage. A genetic
metaheuristic then completes the solutions for each scenario and relevant
information is passed onto the next iteration, thereby supporting the
acquisition of promising resources in the following first stage.
Experimentation on numerous instances of the two-stage stochastic Steiner tree
problem suggests that our evolutionary framework is powerful enough to address
large instances of a wide variety of two-stage stochastic resource allocation
problems.


  This report summarizes the major progresses to develop the dynamic core for
next-generation atmospherical model for both numerical weather prediction and
climate simulation. The numerical framework is based on a general formulation,
so-called multi-moment constrained finite volume (MCV) method, which is
well-balanced among solution quality (accuracy and robustness), algorithmic
simplicity, computational efficiency and flexibility for model configuration. A
local high-order limiting projection is also devised to remove spurious
oscillations and noises in numerical solutions, which allows the numerical
model working well alone without artificial diffusion or filter. The resulted
numerical schemes are very simple, efficient and easy to implement for both
structured and unstructured grids, which provide a promising plateform of great
practical significance. We have implemented the MCV method to shallow water
equations on various spherical grids, including Yin-Yang overset grid, cubed
sphere grid and geodesic icosahedral grid, non-hydrostatic compressible
atmosherical model under complex topographic boundary conditions. In addition,
the moist dynamics simulation like moist thermal bubble has been validated by
using direct microphysical feedback. We have also constructed a prototype of 3D
global non-hydrostatic compressible atmosherical model on cubed sphere grid
with an explicit/implicit-hybrid time integration scheme, which can be used as
the base to develop global atmospheric GCM. All the MCV models have been
verified with widely used benchmark tests. The numerical results show that the
present MCV models have solution quality competitive to other exiting high
order models. Parallelization of the MCV shallow water model on cubed sphere
grid reveals its suitability for large scale parallel processing with desirable
scalability.


  Circumstellar disks are exposed to intense ultraviolet radiation from the
young star. In the inner disks, the UV radiation can be enhanced by more than
seven orders of magnitude compared with the average interstellar field,
resulting in a physical and chemical structure that resembles that of a dense
photon-dominated region (PDR). This intense UV field affects the chemistry, the
vertical structure of the disk, and the gas temperature, especially in the
surface layers of the disk. The parameters which make disks different from
traditional PDRs are discussed, including the shape of the UV radiation field,
grain growth, the absence of PAHs, the gas/dust ratio and the presence of inner
holes. New photorates for selected species, including simple ions, are
presented. Also, a summary of available cross sections at Lyman alpha 1216 A is
made. Rates are computed for radiation fields with color temperatures ranging
from 4000 to 30,000 K, and can be applied to a wide variety of astrophysical
regions including exo-planetary atmospheres. The importance of photoprocesses
is illustrated for a number of representative disk models, including disk
models with grain growth and settling.


  \begin{abstract}
  This paper deals with an extremal problem for bounded harmonic functions in
the unit ball $\mathbb{B}^n.$ We solve the Khavinson conjecture in
$\mathbb{R}^3,$ an intriguing open question since 1992 posed by D. Khavinson,
later considered in a general context by Kresin and Maz'ya. Precisely, we
obtain the following inequality:
  $$|\nabla u(x)|\leq
\frac{1}{\rho^2}\bigg({\frac{(1+\frac{1}{3}\rho^2)^{\frac{3}{2}}}{1-\rho^2}-1}\bigg)
\sup_{|y|<1} |u(y)|, $$ with $\rho=|x|,$ thus sharpening the previously known
with $|\langle \nabla u(x),n_{x} \rangle |$ instead of $|\nabla u(x)|, $ where
$n_{x}=\frac{x}{|x|}.$ \end{abstract}


  We establish an empirical effective temperature calibration of main sequence,
luminosity class V to III B-type stars for the Delta a photometric system which
was originally developed to detect magnetic chemically peculiar objects of the
upper main sequence (early B-type to early F-type) at 5200A. However, this
system provides the index (g1-y) which shows an excellent correlation with
(B-V) as well as (b-y) and can be used as an indicator of the effective
temperature. This is supplemented by a very accurate color-magnitude diagram, y
or V versus (g1-y), which can be used, for example, to determine the reddening,
distance and age of an open cluster. This makes the Delta a photometric system
an excellent tool to investigate the Hertzsprung-Russell-Diagram (HRD) in more
detail. Using the reddening-free parameters and already established
calibrations within the Stromgren uvbybeta, Geneva 7-color and Johnson UBV
systems, a polynomial fit of third degree for the averaged effective
temperatures to the individual (g1-y)0 values was derived. For this purpose,
data from the literature as well as new observations were taken resulting in
225 suitable bright normal B-type objects. The statistical mean of the error
for this sample is 238K which is sufficient to investigate the HRD of distant
galactic open clusters as well as extragalactic aggregates in the future.


  NGC 6791 is a well studied open cluster1 that it is so close to us that can
be imaged down to very faint luminosities. The main sequence turn-off age (~8
Gyr) and the age derived from the termination of the white dwarf cooling
sequence (~6 Gyr) are significantly different. One possible explanation is that
as white dwarfs cool, one of the ashes of helium burning, 22Ne, sinks in the
deep interior of these stars. At lower temperatures, white dwarfs are expected
to crystallise and phase separation of the main constituents of the core of a
typical white dwarf, 12C and 16O, is expected to occur. This sequence of events
is expected to introduce significant delays in the cooling times, but has not
hitherto been proven. Here we report that, as theoretically anticipated,
physical separation processes occur in the cores of white dwarfs, solving the
age discrepancy for NGC 6791.


  Aiming at monitoring a time series to detect stationarity as soon as
possible, we introduce monitoring procedures based on kernel-weighted
sequential Dickey-Fuller (DF) processes, and related stopping times, which may
be called weighted Dickey-Fuller control charts. Under rather weak assumptions,
(functional) central limit theorems are established under the unit root null
hypothesis and local-to-unity alternatives. For gen- eral dependent and
heterogeneous innovation sequences the limit processes depend on a nuisance
parameter. In this case of practical interest, one can use estimated control
limits obtained from the estimated asymptotic law. Another easy-to-use approach
is to transform the DF processes to obtain limit laws which are invariant with
respect to the nuisance pa- rameter. We provide asymptotic theory for both
approaches and compare their statistical behavior in finite samples by
simulation.


  In this paper a comparative study of the electronic and magnetic properties
of quasi-two-dimensional electrons in an artificial graphene-like superlattice
composed of circular and elliptical quantum dots is presented. A complete
orthonormal set of basis wave functions, which has previously been constructed
in the frame of the Coulomb gauge for the vector potential has been implemented
for calculation of the energy dispersions, the Hofstadter spectra, the density
of states and the orbital magnetization of the considered systems, taking into
account both the translational symmetry of the superlattice and the wave
function phase-shifts due to the presence of a transverse external magnetic
field. Our calculations indicate a topological change in the miniband structure
due to the ellipticity of the quantum dots, and non-trivial modifications of
the electron energy dispersion surfaces in reciprocal space with the change of
the number of magnetic flux quanta through the unit cell of the superlattice.
The ellipticity of the QDs leads to an opening of a gap and considerable
modifications of the Hofstadter spectrum. The orbital magnetization is shown to
reveal significant oscillations with the change of the magnetic flux. The
deviation from the circular geometry of quantum dots has a qualitative impact
on the dependencies of the magnetization on both the magnetic flux and the
temperature.


  Salient Object Detection (SOD) domain using RGB-D data has lately emerged
with some current models' adequately precise results. However, they have
restrained generalization abilities and intensive computational complexity. In
this paper, inspired by the best background/foreground separation abilities of
deformable convolutions, we employ them in our Densely Deformable Network
(DDNet) to achieve efficient SOD. The salient regions from densely deformable
convolutions are further refined using transposed convolutions to optimally
generate the saliency maps. Quantitative and qualitative evaluations using the
recent SOD dataset against 22 competing techniques show our method's efficiency
and effectiveness. We also offer evaluation using our own created
cross-dataset, surveillance-SOD (S-SOD), to check the trained models' validity
in terms of their applicability in diverse scenarios. The results indicate that
the current models have limited generalization potentials, demanding further
research in this direction. Our code and new dataset will be publicly available
at https://github.com/tanveer-hussain/EfficientSOD


  This paper is devoted to the complete algebraic and geometric classification
of complex 4 and 5-dimensional antiassociative algebras. In particular, we
proved that the variety of complex 4-dimensional antiassociative algebras has
dimension 12 and it is defined by three irreducible components (in particular,
there is only 1 rigid algebra in this variety); the variety of complex
5-dimensional antiassociative algebras has dimension 24 and it is defined by 8
irreducible components (in particular, there are only 4 rigid algebras in this
variety).


  We have performed direct numerical simulation of turbulent open channel flow
over a smooth horizontal wall in the presence of finite-size, heavy particles.
The spherical particles have a diameter of approximately 7 wall units, a
density of 1.7 times the fluid density and a solid volume fraction of 0.0005.
The value of the Galileo number is set to 16.5, while the Shields parameter
measures approximately 0.2. Under these conditions, the particles are
predominantly located in the vicinity of the bottom wall, where they exhibit
strong preferential concentration which we quantify by means of Voronoi
analysis and by computing the particle-conditioned concentration field. As
observed in previous studies with similar parameter values, the mean streamwise
particle velocity is smaller than that of the fluid. We propose a new
definition of the fluid velocity "seen" by finite-size particles based on an
average over a spherical surface segment, from which we deduce in the present
case that the particles are instantaneously lagging the fluid only by a small
amount. The particle-conditioned fluid velocity field shows that the particles
preferentially reside in the low-speed streaks, leading to the observed
apparent lag. Finally, a vortex eduction study reveals that spanwise particle
motion is significantly correlated with the presence of vortices with the
corresponding sense of rotation which are located in the immediate vicinity of
the near-wall particles.


  A prediction of the steady-state reconnection electric field in asymmetric
reconnection is obtained by maximizing the reconnection rate as a function of
the opening angle made by the upstream magnetic field on the weak magnetic
field (magnetosheath) side. The prediction is within a factor of two of the
widely examined asymmetric reconnection model [Cassak and Shay, Phys. Plasmas
14, 102114, 2007] in the collisionless limit, and they scale the same over a
wide parameter regime. The previous model had the effective aspect ratio of the
diffusion region as a free parameter, which simulations and observations
suggest is on the order of 0.1, but the present model has no free parameters.
In conjunction with the symmetric case [Liu et al., Phys. Rev. Lett. 118,
085101, 2017], this work further suggests that this nearly universal number
0.1, essentially the normalized fast reconnection rate, is a geometrical factor
arising from maximizing the reconnection rate within magnetohydrodynamic
(MHD)-scale constraints.


  We propose a model of directed lines where the average direction has the
nature of a cholesteric liquid crystal. This model, for instance, would
describe the liquid of screw dislocations in the twist-grain-boundary (TGB)
phase of liquid crystals. We show that the presence of lines does not alter the
long wavelength elasticity of a cholesteric and, therefore, does not stabilize
Landau-Peierls instability of the cholesteric phase. We discuss other possible
mechanisms for stabilizing the twist-grain-boundary phase.