  We describe an "active" antenna system for HF/VHF (long wavelength) radio
astronomy that has been successfully deployed 256-fold as the first station
(LWA1) of the planned Long Wavelength Array. The antenna system, consisting of
crossed dipoles, an active balun/preamp, a support structure, and a ground
screen has been shown to successfully operate over at least the band from 20
MHz (15 m wavelength) to 80 MHz (3.75 m wavelength) with a noise figure that is
at least 6 dB better than the Galactic background emission noise temperature
over that band. Thus, the goal to design and construct a compact, inexpensive,
rugged, and easily assembled antenna system that can be deployed many-fold to
form numerous large individual "stations" for the purpose of building a large,
long wavelength synthesis array telescope for radio astronomical and
ionospheric observations was met.


  After showing that the anelastic approximation is better than the subseismic
one to filter out acoustic waves when studying low-frequency stellar
oscillations, we compute gravito-inertial modes of a typical Gamma-Doradus star
using this approximation. We show that eigenmodes can be regular or singular,
according to the possible focusing towards attractors of the underlying
characteristics. Consequences on the oscillations spectrum are then discussed.


  Photoacoustic spectroscopy (PAS) based gas sensors with high sensitivity,
wide dynamic range, low cost, and small footprint are desirable across a broad
range of applications in energy, environment, safety, and public health.
However, most works have focused on either acoustic resonator to enhance
acoustic wave or optical resonator to enhance optical wave. Herein, we develop
a gas sensor based on doubly resonant PAS in which the acoustic and optical
waves are simultaneously enhanced using combined optical and acoustic
resonators in a centimeter-long configuration. Not only the lower detection
limit is enhanced by the double standing waves, but also the upper detection
limit is expanded due to the short resonators. As an example, we developed a
sensor by detecting acetylene (C2H2), achieving a noise equivalent absorption
of 5.7*10-13 cm-1 and a dynamic range of eight orders. Compared to the
state-of-the-art PAS gas sensors, the developed sensor increases the
sensitivity by two orders of magnitude and extends the dynamic range by three
orders of magnitude. Besides, a laser-cavity-molecule locking strategy is
proposed to provide additional flexibility of fast gas detection.


  We say a structure $M$ in a first-order language is indivisible if for every
coloring of its universe in two colors, there is a monochromatic substructure
$M'$ of $M$ such that $M'$ is isomorphic to $M$. Additionally, we say that $M$
is symmetrically indivisible if $M'$ can be chosen to be symmetrically embedded
in $M$ (that is, every automorphism of $M'$ can be extended to an automorphism
of $M$). Similarly, we say that $M$ is elementarily indivisible if $M'$ can be
chosen to be an elementary substructure. We define new products of structures
in a relational language. We use these products to give recipes for
construction of elementarily indivisible structures which are not transitive
and elementarily indivisible structures which are not symmetrically
indivisible, answering two questions presented by A. Hasson, M. Kojman and A.
Onshuus.


  The quantum state of a single photon stands among the most fundamental and
intriguing manifestations of quantum physics. At the same time single photons
and pairs of single photons are important building blocks in the fields of
linear optical based quantum computation and quantum repeater infrastructure.
These fields possess enormous potential and much scientific and technological
progress has been made in developing individual components, like quantum
memories and photon sources using various physical implementations. However,
further progress suffers from the lack of compatibility between these different
components. Ultimately, one aims for a versatile source of single photons and
photon pairs in order to overcome this hurdle of incompatibility. Such a photon
source should allow for tuning of the spectral properties (wide wavelength
range and narrow bandwidth) to address different implementations while
retaining high efficiency. In addition, it should be able to bridge different
wavelength regimes to make implementations compatible. Here we introduce and
experimentally demonstrate such a versatile single photon and photon pair
source based on the physics of whispering gallery resonators. A disk-shaped,
monolithic and intrinsically stable resonator is made of lithium niobate and
supports a cavity-assisted triply-resonant spontaneous parametric
down-conversion process. Measurements show that photon pairs are efficiently
generated in two highly tunable resonator modes. We verify wavelength tuning
over 100 nm between both modes with a controllable bandwidth between 7.2 and 13
MHz. Heralding of single photons yields anti-bunching with $g^{(2)}(0) < 0.2$.
This compact source provides unprecedented possibilities to couple to different
physical quantum systems and renders it ideal for the implementation of quantum
repeaters and optical quantum information processing.


  It is proved in this paper that to every underdetermined linear system $Ax=b$
there corresponds a constant $p(A,b)>0$ such that every solution to the
$l_p$-norm minimization problem also solves the $l_0$-norm minimization problem
whenever $0<p<p(A,b)$. This phenomenon is named $NP/CLP$ equivalence.


  We investigate several infinite product of cosines and find the closed form
using the Fourier transform. The answers provide limiting distributions for
some elementary probability experiments.


  We study the effects of strong electron-electron interactions on the surface
of cubic topological Kondo insulators (such as samarium hexaboride, SmB$_6$).
Cubic topological Kondo insulators generally support three copies of massless
Dirac nodes on the surface, but only two of them are energetically degenerate
and exhibit an energy offset relative to the third one. With a tunable chemical
potential, when the surface states host electron and hole pockets of comparable
size, strong interactions may drive this system into rotational symmetry
breaking nematic and translational symmetric breaking excitonic spin- or
charge-density-wave phases, depending on the relative chirality of the Dirac
cones. Taking a realistic surface band structure into account we analyze the
associated Ginzburg-Landau theory and compute the mean field phase diagram for
interacting surface states. Beyond mean field theory, this system can be
described by a two-component isotropic Ashkin-Teller model at finite
temperature, and we outline the phase diagram of this model. Our theory
provides a possible explanation of recent measurements which detect a two-fold
symmetric magnetoresistance and an upturn in surface resistivity with tunable
gate voltage in SmB$_6$. Our discussion can also be germane to other cubic
topological insulators, such as ytterbium hexaboride (YbB$_6$), plutonium
hexaboride (PuB$_6$).


  Le Roux and Ziegler asked whether every simply connected compact nonempty
planar co-c.e. closed set always contains a computable point. In this paper, we
solve the problem of le Roux and Ziegler by showing that there exists a
contractible planar co-c.e. dendroid without computable points. We also provide
several pathological examples of tree-like co-c.e. continua fulfilling certain
global incomputability properties: there is a computable dendrite which does
not *-include a co-c.e. tree; there is a co-c.e. dendrite which does not
*-include a computable dendrite; there is a computable dendroid which does not
*-include a co-c.e. dendrite. Here, a continuum A *-includes a member of a
class P of continua if, for every positive real, A includes a P-continuum B
such that the Hausdorff distance between A and B is smaller than the real.


  Brownian motion in the plane in the presence of a "trap" at which motion is
stopped is studied. If the trap $T$ is a connected compact set, it is shown
that the probability for planar Brownian motion to hit this set before a given
time $t$ is well approximated even at short times by the probability that
Brownian motion hits a disk of radius $r_T$ equal to the conformal radius of
the trap $T$.


  The chiral symmetry breaking in the 4-dimensional QED with the chirally
invariant four-fermion interaction is discussed by using a novel path integral
expression in terms of the field-strength tensor. In the local potential
approximation, we find that the chiral symmetry is spontaneously broken for any
nonzero gauge and four-fermion couplings on the tree level of an auxiliary
field $\sigma$. The present approach allows us to easily include higher orders
of the gauge coupling so that the effective potential up to the sixth order is
obtained.


  With the multiallelic parent-independent mutation-drift model, the
equilibrium proportions of alleles are known to be Dirichlet distributed. A
special case is the biallelic model, in which the proportions are beta
distributed. A sample taken from these models is then Dirichlet-multinomially
or beta-binomially distributed, respectively. Maximum likelihood (ML)
estimators for the mutation parameters of the biallelic parent-independent
mutation model are available via an expectation maximization algorithm.
Assuming small scaled mutation rates, the distribution of a sample of size $M$
can be expanded in a Taylor series of first order. Then the ML estimators for
the two parameters in the biallelic model can be expressed using the site
frequency spectrum. In this article, we go beyond parent-independent mutation
and analyse a strand-symmetric mutation model with six scaled mutation
parameters that deviates from parent independent mutation and, generally, from
detailed balance. We derive ML estimators for these six parameters assuming
mutation-drift equilibrium and small scaled mutation rates. This is the first
time that ML estimators are provided for a mutation model more complex than
parent-independent mutation.


  Data-driven science is heralded as a new paradigm in materials science. In
this field, data is the new resource, and knowledge is extracted from materials
data sets that are too big or complex for traditional human reasoning -
typically with the intent to discover new or improved materials or materials
phenomena. Multiple factors, including the open science movement, national
funding, and progress in information technology, have fueled its development.
Such related tools as materials databases, machine learning, and
high-throughput methods are now established as parts of the materials research
toolset. However, there are a variety of challenges that impede progress in
data-driven materials science: data veracity, integration of experimental and
computational data, data longevity, standardization, and the gap between
industrial interests and academic efforts. In this perspective article, we
discuss the historical development and current state of data-driven materials
science, building from the early evolution of open science to the rapid
expansion of materials data infrastructures. We also review key successes and
challenges so far, providing a perspective on the future development of the
field.


  We show by means of ab initio calculations and tight-binding modeling that an
oxide system based on a honeycomb lattice can sustain topologically non-trivial
states if a single orbital dominates the spectrum close to the Fermi level. In
such situation, the low energy spectra is described by two Dirac equations that
become non-trivially gapped when spin-orbit coupling (SOC) is switched on. We
provide one specific example for this but the recipe is general. We discuss a
realization of this starting from a conventional spin-a-half honeycomb
antiferromagnet whose states close to the Fermi energy are d$_{z^2}$ orbitals.
Switching off magnetism by atomic substitution and ensuring that the electronic
structure becomes two-dimensional is sufficient for topologicality to arise in
such a system. We show that the gap in such model scales linearly with SOC,
opposed to other oxide-based topological insulators, where smaller gaps tend to
appear by construction of the lattice. We also provide a study of the quantum
Hall effect in such system, showing the close connections with the physics of
graphene but in a d-electron system.


  In this paper, we address the problem of image semantic communication in a
multi-user deployment scenario and propose a federated learning (FL) strategy
for a Swin Transformer-based semantic communication system (FSSC). Firstly, we
demonstrate that the adoption of a Swin Transformer for joint source-channel
coding (JSCC) effectively extracts semantic information in the communication
system. Next, the FL framework is introduced to collaboratively learn a global
model by aggregating local model parameters, rather than directly sharing
clients' data. This approach enhances user privacy protection and reduces the
workload on the server or mobile edge. Simulation evaluations indicate that our
method outperforms the typical JSCC algorithm and traditional separate-based
communication algorithms. Particularly after integrating local semantics, the
global aggregation model has further increased the Peak Signal-to-Noise Ratio
(PSNR) by more than 2dB, thoroughly proving the effectiveness of our algorithm.


  Driven by the recent advances in deep learning methods and, in particular, by
the development of modern self-supervised learning algorithms, increased
interest and efforts have been devoted to build foundation models (FMs) for
medical images. In this work, we present our scalable training pipeline for
large pathology imaging data, and a comprehensive analysis of various
hyperparameter choices and training techniques for building pathology FMs. We
release and make publicly available the first batch of our pathology FMs
(https://github.com/kaiko-ai/towards_large_pathology_fms) trained on
open-access TCGA whole slide images, a commonly used collection of pathology
images. The experimental evaluation shows that our models reach
state-of-the-art performance on various patch-level downstream tasks, ranging
from breast cancer subtyping to colorectal nuclear segmentation. Finally, to
unify the evaluation approaches used in the field and to simplify future
comparisons of different FMs, we present an open-source framework
(https://github.com/kaiko-ai/eva) designed for the consistent evaluation of
pathology FMs across various downstream tasks.


  We consider the conductance of an Andreev interferometer, i.e., a hybrid
structure where a dissipative current flows through a mesoscopic normal (N)
sample in contact with two superconducting (S) "mirrors". Giant conductance
oscillations are predicted if the superconducting phase difference $\phi$ is
varied. Conductance maxima appear when $\phi$ is on odd multiple of $\pi$ due
to a bunching at the Fermi energy of quasiparticle energy levels formed by
Andreev reflections at the N-S boundaries. For a ballistic normal sample the
oscillation amplitude is giant and proportional to the number of open
transverse modes. We estimate using both analytical and numerical methods how
scattering and mode mixing --- which tend to lift the level degeneracy at the
Fermi energy --- effect the giant oscillations. These are shown to survive in a
diffusive sample at temperatures much smaller than the Thouless temperature
provided there are potential barriers between the sample and the normal
electron reservoirs. Our results are in good agreement with previous work on
conductance oscillations of diffusive samples, which we propose can be
understood in terms of a Feynman path integral description of quasiparticle
trajectories.


  A phenomenological free energy model is proposed to describe the behavior of
smectic liquid crystals, an intermediate phase that exhibits orientational
order and layering at the molecular scale. Advantageous properties render the
functional amenable to numerical simulation. The model is applied to a number
of scenarios involving geometric frustration, leading to emergent structures
such as focal conic domains and oily streaks and enabling detailed elucidation
of the very rich energy landscapes that arise in these problems.


  The tensor network variety is a variety of tensors associated to a graph and
a set of positive integer weights on its edges, called bond dimensions. We
determine an upper bound on the dimension of the tensor network variety. A
refined upper bound is given in cases relevant for applications such as
varieties of matrix product states and projected entangled pairs states. We
provide a range (the "supercritical range") of the parameters where the upper
bound is sharp.


  BPMS (Business Process Management System) represents a type of software that
automates the organizational processes looking for efficiency. Since the
knowledge of organizations lies in their processes, it seems probable that a
BPMS can be used to manage the knowledge applied in these processes. Through
the BPMS-KM Support Model, this study aims to determine the reliability and
validity of a 65-item instrument to measure the utility and the use of a BPMS
for knowledge management (KM). A questionnaire was sent to 242 BPMS users and
to determine its validity, a factorial analysis was conducted. The results
showed that the measuring instrument is trustworthy and valid. It represents
implications for research, since it provides an instrument validated for
research on the success of a BPMS for KM. There would also be practical
implications, since managers can evaluate the use of BPMS, in addition to
automating processes to manage knowledge.


  We present the first observations of zero-n bandgaps in photonic crystal
superlattices consisting of alternating stacks of negative index photonic
crystals and positive index dielectric materials in the near-infrared. Guided
by ab initio three-dimensional numerical simulations, the fabricated
nanostructured superlattices demonstrate the presence of zero-order gaps in
remarkable agreement with theoretical predictions across a range of different
superlattice periods and unit cell variations. These volume-averaged zero-index
superlattice structures present a new type of photonic band gap, with potential
for complete wavefront control for arbitrary phase delay lines and open cavity
resonances.


  The recent report on the observation of soft magnetorotons in the dispersion
of charge-density excitations across the tunneling gap in coupled bilayers at
total Landau level filling factor $\nu_T=1$ is reviewed. The inelastic light
scattering experiments take advantage of the breakdown of wave-vector
conservation that occurs under resonant excitation. The results offer evidence
that in the quantum Hall state there is a roton that softens and sharpens
markedly when the phase boundary for transitions to highly-correlated
compressible states is approached. These findings are interpreted with
Hartree-Fock evaluations of the dynamic structure factor. The model includes
the effect of disorder in the breakdown of wave-vector conservation and
resonance enhancement profiles within a phenomenological approach. These
results link the softening of magnetorotons to enhanced excitonic Coulomb
interactions in the ferromagnetic bilayers.


  The Monte Carlo wave function method or the quantum trajectory/jump approach
is a powerful tool to study dissipative dynamics governed by the Markovian
master equation, in particular for high-dimensional systems and when it is
difficult to simulate directly. In this paper, we extend this method to the
non-Markovian case described by the generalized Lindblad master equation. Two
examples to illustrate the method are presented and discussed. The results show
that the method can correctly reproduce the dissipative dynamics for the
system. The difference between this method and the traditional Markovian jump
approach and the computational efficiency of this method are also discussed.


  The most natural supersymmetric solution to the hierarchy problem prefers the
scalar top partner to be close in mass to the top quark. Experimental searches
exclude top squarks across a wide range of masses, but a gap remains when the
difference between the masses of the stop and the lightest supersymmetric
particle is close to the top mass. We propose to search for stops in this
regime by exploiting the azimuthal angular correlation of forward tagging jets
in (s)top pair production. As shown in earlier work, this correlation is
sensitive to the spin of the heavy states, allowing one to distinguish between
top and stop pair production. Here, we demonstrate that this angular
information can give a statistically significant stop pair production signal in
the upcoming LHC run. While the appropriate simulation including parton
showering and detector simulation requires some care, we find stable
predictions for the angular correlation using multi-jet merging.


  The reentrant superconductivity is the peculiar phenomenon observed in
paramagnetic metal UTe$_2$ in magnetic field parallel to the hard magnetisation
axis. It is difficult to explain it in terms of field dependent intensity of
magnetic fluctuations like it is done for explanation of the formally similar
phenomena in the ferromagnetic uranium superconductors URhGe, UCoGe. Extremely
large initial slope of the upper critical field temperature dependence suggests
that the phenomenon has the quasi-two-dimensional nature. Indeed, according to
the recent band structure calculations by Yuanji Xu et al, Phys.Rev. Lett. {\bf
123}, 217002 (2019) the Fermi surface of UTe$_2$ consists of two types slightly
corrugated cylinders.The theory of reentrant superconductivity in UTe$_2$ based
on its quasi-two-dimensional structure is presented here.


  We report here the evidences of hydrogen bond symmetrization in the simplest
amino acid- carboxylic acid complex, glycinium oxalate, at moderate pressures
of 8 GPa using in-situ infrared and Raman spectroscopic investigations combined
with first-principles simulations. The protonation of the semioxalate units
through dynamic proton movement results in infinite oxalate chains. At
pressures above 12 GPa, the glycine units systematically reorient with pressure
to form hydrogen bonded supramolecular assemblies held together by these
chains.


  Based on optical/near-IR Magellan FIRE spectra of 25 starburst galaxies at
0.5 < z < 0.9, Calabr\`o et al.(2018) showed that their attenuation properties
can be explained by a single-parameter sequence of total obscurations ranging
from A(V)=2 to A(V)=30 towards the starburst core centers in a mixed stars and
dust configuration. We investigate here the origin of this sequence for the
same sample. We show that total attenuations anti-correlate with the starburst
sizes in radio (3 GHz) with a significance larger than 5sigma and a scatter of
0.26 dex. More obscured and compact starbursts also show enhanced N2
(=[NII]/Halpha) ratios and larger line velocity widths that we attribute to an
increasing shock contribution toward later merger phases, driven by deeper
gravitational potential wells at the coalescence. Additionally, the attenuation
is also linked to the equivalent width (EW) of hydrogen recombination lines,
which is sensitive to the luminosity weighted age of the relatively unobscured
stellar populations. Overall, the correlations among A(V), radio size, line
width, N2 and EW of Balmer/Paschen lines converge towards suggesting an
evolutionary sequence of merger stages: all of these quantities are likely to
be good time-tracers of the merger phenomenon, and their large spanned range
appears to be characteristic of the different merger phases. Half of our sample
at higher obscurations have radio sizes approximately 3 times smaller than
early type galaxies at the same redshift, suggesting that, in analogy with
local Ultraluminous Infrared galaxies (ULIRGs), these cores cannot be directly
forming elliptical galaxies. Finally, we detect mid-IR AGN torus for half of
our sample and additional X-ray emission for 6 starbursts; intriguingly, the
latter have systematically more compact sizes, suggestive of emerging AGNs
towards later merger stages, possibly precursors of a later QSO phase.


  The model interpretation is essential in many application scenarios and to
build a classification model with a ease of model interpretation may provide
useful information for further studies and improvement. It is common to
encounter with a lengthy set of variables in modern data analysis, especially
when data are collected in some automatic ways. This kinds of datasets may not
collected with a specific analysis target and usually contains redundant
features, which have no contribution to a the current analysis task of
interest. Variable selection is a common way to increase the ability of model
interpretation and is popularly used with some parametric classification
models. There is a lack of studies about variable selection in nonparametric
classification models such as the density estimation-based methods and this is
especially the case for multiple-class classification situations. In this study
we study multiple-class classification problems using the thought of sparse
non-parametric density estimation and propose a method for identifying high
impacts variables for each class. We present the asymptotic properties and the
computation procedure for the proposed method together with some suggested
sample size. We also repost the numerical results using both synthesized and
some real data sets.


  Several experiments have been conducted worldwide, with the goal of observing
low-energy nuclear recoils induced by WIMPs scattering off target nuclei in
ultra-sensitive, low-background detectors. In the last few decades noble liquid
detectors designed to search for dark matter in the form of WIMPs have been
extremely successful in improving their sensitivities and setting the best
limits. One of the crucial problems to be faced for the development of large
size (multi ton-scale) liquid argon experiments is the lack of reliable and low
background cryogenic PMTs: their intrinsic radioactivity, cost, and borderline
performance at 87 K rule them out as a possible candidate for photosensors. We
propose a brand new concept of liquid argon-based detector for direct dark
matter search: the Geiger-mode Avalanche Photodiode Time Projection Chamber
(GAP-TPC) optimized in terms of residual radioactivity of the photosensors,
energy and spatial resolution, light and charge collection efficiency


  Covariance matrices are fundamental to the analysis and forecast of economic,
physical and biological systems. Although the eigenvalues $\{\lambda_i\}$ and
eigenvectors $\{{\bf u}_i\}$ of a covariance matrix are central to such
endeavors, in practice one must inevitably approximate the covariance matrix
based on data with finite sample size $n$ to obtain empirical eigenvalues
$\{\tilde{\lambda}_i\}$ and eigenvectors $\{\tilde{{\bf u}}_i\}$, and therefore
understanding the error so introduced is of central importance. We analyze
eigenvector error $\|{\bf u}_i - \tilde{{\bf u}}_i \|^2$ while leveraging the
assumption that the true covariance matrix having size $p$ is drawn from a
matrix ensemble with known spectral properties---particularly, we assume the
distribution of population eigenvalues weakly converges as $p\to\infty$ to a
spectral density $\rho(\lambda)$ and that the spacing between population
eigenvalues is similar to that for the Gaussian orthogonal ensemble. Our
approach complements previous analyses of eigenvector error that require the
full set of eigenvalues to be known, which can be computationally infeasible
when $p$ is large. To provide a scalable approach for uncertainty
quantification of eigenvector error, we consider a fixed eigenvalue $\lambda$
and approximate the distribution of the expected square error $r=
\mathbb{E}\left[\| {\bf u}_i - \tilde{{\bf u}}_i \|^2\right]$ across the matrix
ensemble for all ${\bf u}_i$ associated with $\lambda_i=\lambda$. We find, for
example, that for sufficiently large matrix size $p$ and sample size $n>p$, the
probability density of $r$ scales as $1/nr^2$. This power-law scaling implies
that eigenvector error is extremely heterogeneous---even if $r$ is very small
for most eigenvectors, it can be large for others with non-negligible
probability. We support this and further results with numerical experiments.


  A study of the centrally produced ppbar, ppbarpi, ppbarpipi and lambda lambda
channels has been performed in pp collisions using an incident beam momentum of
450 GeV/c. No significant new structures are observed in the mass spectra,
however, important new information on the production dynamics is obtained. A
systematic study of the production properties of these systems has been
performed and it is found that these systems are not produced dominantly by
double Pomeron exchange.


  We present results of a deep mid-infrared survey in the SSA13 field with the
Infrared Space Observatory (ISO). In order to probe the near-infrared light at
high redshifts, we surveyed the field with the broad band LW2 (5-8.5um) filter
of the mid-infrared camera ISOCAM. Adopting a highly redundant imaging strategy
for the 23 hour observation and carefully treating gradual changes in the
detector responsivity caused by a very high rate of cosmic ray impacts, we
succeeded in reaching an 80% completeness limit of 16uJy in the central 7
arcmin2 region. Utilizing the signal-to-noise ratio map, we detected 65 sources
down to 6uJy in the 16 arcmin2 field. Integral galaxy number counts at 6.7um
are then derived, reaching 1.3e4/deg2 at the faint limit with a slope of -1.6
between 13uJy and 130uJy. Integrating individual sources in this flux range,
the resolved fraction of the extragalactic background light at 6.7um is
estimated to be 0.56nW/m2/sr. These results, which reach a flux limit three
times fainter than those in the Hubble Deep Fields, are in fairly good
agreement with a model prediction by Franceschini et al. (1997). Finally, we
discuss the relation of distant massive E/S0 galaxies to the faint 6.7um galaxy
population.


  We study quantum corrections in four-dimensional theories with $N=1$
supersymmetry in the context of Quantum Gravity Conjectures. According to the
Emergent String Conjecture, infinite distance limits in quantum gravity either
lead to decompactification of the theory or result in a weakly coupled string
theory. We verify this conjecture in the framework of $N=1$ supersymmetric
F-theory compactifications to four dimensions including perturbative $\alpha'$
as well as non-perturbative corrections. After proving uniqueness of the
emergent critical string at the classical level, we show that quantum
corrections obstruct precisely those limits in which the scale of the emergent
critical string would lie parametrically below the Kaluza-Klein scale. Limits
in which the tension of the asymptotically tensionless string sits at the
Kaluza-Klein scale, by contrast, are not obstructed. In the second part of the
paper we study the effect of quantum corrections for the Weak Gravity
Conjecture away from the strict weak coupling limit. We propose that gauge
threshold corrections and mass renormalisation effects modify the
super-extremality bound in four dimensions. For the infinite distance limits in
F-theory the classical super-extremality bound is generically satisfied by a
sublattice of states in the tower of excitations of an emergent heterotic
string. By matching the F-theory $\alpha'$ corrections to gauge threshold
corrections of the dual heterotic theory we predict how the masses of this
tower must be renormalised in order for the Weak Gravity Conjecture to hold at
the quantum level.


  This paper addresses the problem of Multi-robot Coverage Path Planning (MCPP)
for unknown environments in the presence of robot failures. Unexpected robot
failures can seriously degrade the performance of a robot team and in extreme
cases jeopardize the overall operation. Therefore, this paper presents a
distributed algorithm, called Cooperative Autonomy for Resilience and
Efficiency (CARE), which not only provides resilience to the robot team against
failures of individual robots, but also improves the overall efficiency of
operation via event-driven replanning. The algorithm uses distributed Discrete
Event Supervisors (DESs), which trigger games between a set of feasible players
in the event of a robot failure or idling, to make collaborative decisions for
task reallocations. The game-theoretic structure is built using Potential
Games, where the utility of each player is aligned with a shared objective
function for all players. The algorithm has been validated in various complex
scenarios on a high-fidelity robotic simulator, and the results demonstrate
that the team achieves complete coverage under failures, reduced coverage time,
and faster target discovery as compared to three alternative methods.


  Here we employ both Fe K and L2,3 edge x-ray absorption near-edge structure
(XANES) spectroscopy techniques to clarify that iron in the B-site ordered
double-perovskite halfmetal, Sr2FeMoO6.0, possesses a mixed-valence state,
FeII/III, and accordingly molybdenum a mixed MoV/VI valence state. A reliable
interpretation of the spectral features has been made possible by using a
series of samples of the Sr2Fe(Mo,W/Ta)O6.0 system. Replacing MoV/VI gradually
with WVI causes increasing amount of Fe to adopt the FeII state, whereas TaV
substitution shifts the valence of iron towards FeIII. As the valence of Fe
increases from II to III in the Sr2Fe(Mo,W/Ta)O6.0 system, the absorption
energy at the Fe K-edge gradually shifts towards the higher energy side.
Similarly, in the L2,3-edge XANES spectra intermediate spectral features are
revealed for the Sr2FeMoO6.0 sample in comparison with those for samples
heavily substituted with either W or Ta.


  We report a quantum ring-like toroidal cavity naturally formed in a
vertical-cavity-like active microdisk plane due to Rayleigh's band of
whispering gallery modes. The $\sqrt{T}$-dependent redshift and a square-law
property of microampere-range threshold currents down to 2 $\mu$A are
consistent with a photonic quantum wire view, due to whispering gallery
mode-induced dimensional reduction.


  We consider the motion of many confined billiard balls in interaction and
discuss their transport and chaotic properties. In spite of the absence of mass
transport, due to confinement, energy transport can take place through binary
collisions between neighbouring particles. We explore the conditions under
which relaxation to local equilibrium occurs on time scales much shorter than
that of binary collisions, which characterize the transport of energy, and
subsequent relaxation to local thermal equilibrium. Starting from the
pseudo-Liouville equation for the time evolution of phase-space distributions,
we derive a master equation which governs the energy exchange between the
system constituents. We thus obtain analytical results relating the transport
coefficient of thermal conductivity to the frequency of collision events and
compute these quantities. We also provide estimates of the Lyapunov exponents
and Kolmogorov-Sinai entropy under the assumption of scale separation. The
validity of our results is confirmed by extensive numerical studies.


  We propose a method for quantum noise extraction from the interference of
laser pulses with random phase. Our technique is based on the calculation of a
parameter, which we called the quantum reduction factor, and which allows
determining the contributions of quantum and classical noises in the assumption
that classical fluctuations exhibit Gaussian distribution. To the best of our
knowledge, the concept of the quantum reduction factor is introduced for the
first time. We use such an approach to implement the post-processing-free
optical quantum random number generator with the random bit generation rate of
2 Gbps.


  We present FrankWolfe.jl, an open-source implementation of several popular
Frank-Wolfe and Conditional Gradients variants for first-order constrained
optimization. The package is designed with flexibility and high-performance in
mind, allowing for easy extension and relying on few assumptions regarding the
user-provided functions. It supports Julia's unique multiple dispatch feature,
and interfaces smoothly with generic linear optimization formulations using
MathOptInterface.jl.


  Using different segmental dynamics and relaxation, characteristics of the
interface growth is examined in an electrophoretic deposition of polymer chains
on a three (2+1) dimensional discrete lattice with a Monte Carlo simulation.
Incorporation of faster modes such as crankshaft and reptation movements along
with the relatively slow kink-jump dynamics seems crucial in relaxing the
interface width. As the continuously released polymer chains are driven (via
segmental movements) and deposited, the interface width $W$ grows with the
number of time steps $t$, $W \propto t^{\beta},$ ($\beta \sim 0.4$--$0.8)$,
which is followed by its saturation to a steady-state value $W_s$. Stopping the
release of additional chains after saturation while continuing the segmental
movements relaxes the saturated width to an equilibrium value ($W_s \to W_r$).
Scaling of the relaxed interface width $W_r$ with the driving field $E$, $W_r
\propto E^{-1/2}$ remains similar to that of the steady-state $W_s$ width. In
contrast to monotonic increase of the steady-state width $W_s$, the relaxed
interface width $W_r$ is found to decay (possibly as a stretched exponential)
with the molecular weight.


  This dissertation introduces executable refinement types, which refine
structural types by semi-decidable predicates, and establishes their metatheory
and accompanying implementation techniques. These results are useful for
undecidable type systems in general.
  Particular contributions include: (1) Type soundness and a logical relation
for extensional equivalence for executable refinement types (though type
checking is undecidable); (2) hybrid type checking for executable refinement
types, which blends static and dynamic checks in a novel way, in some sense
performing better statically than any decidable approximation; (3) a type
reconstruction algorithm - reconstruction is decidable even though type
checking is not, when suitably redefined to apply to undecidable type systems;
(4) a novel use of existential types with dependent types to ensure that the
language of logical formulae is closed under type checking (5) a prototype
implementation, Sage, of executable refinement types such that all dynamic
errors are communicated back to the compiler and are thenceforth static errors.


  Muon colliders and neutrino factories are attractive options for future
facilities aimed at achieving the highest lepton-antilepton collision energies
and precision measurements of parameters of the Higgs boson and the neutrino
mixing matrix. The performance and cost of these depend on how well a beam of
muons can be cooled. Recent progress in muon cooling design studies and
prototype tests nourishes the hope that such facilities can be built starting
in the coming decade. The status of the key technologies and their various
demonstration experiments is summarized, with emphasis on recent results from
the Muon Ionization Cooling Experiment (MICE).


  We study quasilinear degenerate parabolic-hyperbolic stochastic partial
differential equations with general multiplicative noise within the framework
of kinetic solutions. Our results are twofold: First, we establish new
regularity results based on averaging techniques. Second, we prove the
existence and uniqueness of solutions in a full $L^1$ setting requiring no
growth assumptions on the nonlinearities. In addition, we prove a comparison
result and an $L^1$-contraction property for the solutions.


  We study a nonlocal equation, analogous to the Kuramoto-Sivashinsky equation,
in which short waves are stabilized by a possibly fractional diffusion of order
less than or equal to two, and long waves are destabilized by a backward
fractional diffusion of lower order. We prove the global existence, uniqueness,
and analyticity of solutions of the nonlocal equation and the existence of a
compact attractor. Numerical results show that the equation has chaotic
solutions whose spatial structure consists of interacting traveling waves
resembling viscous shock profiles.


  We find a new class of data for which the Prandtl boundary layer equations
and the hydrostatic Euler equations are locally in time well-posed. In the case
of the Prandtl equations, we assume that the initial datum $u_0$ is monotone on
a number of intervals (on some strictly increasing on some strictly decreasing)
and analytic on the complement and show that the local existence and uniqueness
hold. The same is true for the hydrostatic Euler equations except that we
assume this for the vorticity $\omega_0=\partial_y u_0$.


  We propose a nonparametric procedure to achieve fast inference in generative
graphical models when the number of latent states is very large. The approach
is based on iterative latent variable preselection, where we alternate between
learning a 'selection function' to reveal the relevant latent variables, and
use this to obtain a compact approximation of the posterior distribution for
EM; this can make inference possible where the number of possible latent states
is e.g. exponential in the number of latent variables, whereas an exact
approach would be computationally unfeasible. We learn the selection function
entirely from the observed data and current EM state via Gaussian process
regression. This is by contrast with earlier approaches, where selection
functions were manually-designed for each problem setting. We show that our
approach performs as well as these bespoke selection functions on a wide
variety of inference problems: in particular, for the challenging case of a
hierarchical model for object localization with occlusion, we achieve results
that match a customized state-of-the-art selection method, at a far lower
computational cost.


  We show that $SL(2;C)/SU(2)$ model which had been recently proposed to
describe the behaviour of the local densities of states at the plateau
transition in Integer Quantum Hall effect, has logarithmic operators. They
unusual properties are studied in this letter.


  This article presents a proof of Pogorelov's result that there exists a
$C^{2,1}$ metric with no local $C^2$ realization in $\mathbb{R}^3$. It also
construct in a very elementary way a $C^{1,1}$ realization of this metric.
Pogorelov's result is somewhat controversial among the community of researchers
that study isometric immersions. This in part owes to the lack of details in
Pogorelov's original paper. The chief aim of the paper is therefore to provide
the missing details. The construction is the same as Pogorelov's, although the
verification differs in some important respects.


  In \cite{joux}, Joux devised an algorithm to compute discrete logarithms
between elements in a certain subset of the multiplicative group of an
extension of the finite field $\mathbb{F}_{p^n}$ in time polynomial in $p$ and
$n$. Shortly after, Barbulescu, Gaudry, Joux and Thome \cite{bgjt} proposed a
descent algorithm that in $(p n)^{\mathcal{O}(\log n)}$ time projects an
arbitrary element in $\mathbb{F}_{p^n}^\times$ as a product of powers of
elements in the aforementioned subset. Together, these two algorithms yield a
quasi-polynomial time algorithm for computing discrete logarithms in finite
fields of small characteristic. The success of both the algorithms are reliant
on heuristic assumptions. We identify obstructions that prevent certain
heuristic assumptions they make from being true in general. Further, we
describe methods to overcome these obstructions.


  The spin-1 particles is an admirable two quarks bound state system to
understand electromagnetic properties from hadronic states. These systems are
generally relativistic, and therefore, need an approach using quantum field
theory. In the present work, we will use both the quantum field theory at the
instant form, as well, quantum field theory on the light-front~(LFQFT). In
general, it is used to calculate the electromagnetic properties of spin-1
vector particles in the LFQFT formalism, with the plus component of the
electromagnetic current. In the present work, we used, in addition to the plus
component of the electromagnetic current; the minus component of the current,
and we use that components o the current, to extract the covariant form
factors; showing that to have an equivalence between these we need to add
non-valence terms to the electromagnetic current, in order to restore the
covariance, and obtain exactly the same results when using the instant form
quantum field theory.


  For an abelian category, a category equivalent to its derived category is
constructed by means of specific projective (injective) multicomplexes, the
so-called homological resolutions.


  This paper investigates rate independent systems (RIS), where the dissipation
functional depends not only on the rate but also on the history of the state.
The latter is expressed in terms of a Volterra integral operator. We establish
an existence result for the original problem and for the control thereof,
without resorting to smallness assumptions. Under a smoothness condition, we
prove the uniqueness of solutions to a certain class of history dependent RIS
with unbounded dissipation potentials. In this context, we derive an essential
estimate that opens the door to future research on the topic of optimization.


  This paper deals with shape optimization for elastic materials under
stochastic loads. It transfers the paradigm of stochastic dominance, which
allows for flexible risk aversion via comparison with benchmark random
variables, from finite-dimensional stochastic programming to shape
optimization. Rather than handling risk aversion in the objective, this enables
risk aversion by including dominance constraints that single out subsets of
nonanticipative shapes which compare favorably to a chosen stochastic
benchmark. This new class of stochastic shape optimization problems arises by
optimizing over such feasible sets. The analytical description is built on
risk-averse cost measures. The underlying cost functional is of compliance type
plus a perimeter term, in the implementation shapes are represented by a phase
field which permits an easy estimate of a regularized perimeter. The analytical
description and the numerical implementation of dominance constraints are built
on risk-averse measures for the cost functional. A suitable numerical
discretization is obtained using finite elements both for the displacement and
the phase field function. Different numerical experiments demonstrate the
potential of the proposed stochastic shape optimization model and in particular
the impact of high variability of forces or probabilities in the different
realizations.


  We address the question of whether the superconducting transition temperature
(Tc) of high-Tc cuprates is enhanced when randomly distributed dopant atoms
form an ordered array in the charge reservoir layers. This study is possible
for the Sr2CuO3+d superconductor with K2NiF4-type structure in which oxygen
atoms only partially occupy the apical sites next to the CuO2 planes and act as
hole-dopants. We show that remarkable Tc enhancement up to 95K in this mono
CuO2 layered HTS is associated with the apical oxygen ordering, not to the hole
concentration change. The result points a route toward further enhancement of
Tc in cuprate superconductors.


  Taylor's Law (TL) relates the variance to the mean of a random variable via
power law. In ecology it applies to populationsand it is a common empirical
pattern shared among different ecosystems. Measurements give power law exponent
to be between 1 and 2, and more often to cluster around 2, whereas theoretical
models predict TL exponent can assume any real value. In this paper, adopting
the framework of multiplicative growth models in a Markovian environment, we
investigate the possibility of evolutionary strategies to be responsible for TL
exponent to be in a finite range. We implement three different strategies the
individuals can follow and for each strategy set two different optimization
investment objectives. In all the studied cases we find TL exponent can assume
any real value due to the existence of regions of the model parameters in which
the exponent can diverge. Furthermore, under natural hypothesis on the dynamics
of the environment, the shapes of these regions do not depend on different
strategies adopted and nor on the optimization objective. Thus the introduction
of strategies dose not affect the range of TL exponent in the model. In our
theoretical framework rare events are shaping the value of the TL exponent,
suggesting, as hinted by previous works, that empirical values may be a
statistical artifact following from under sampling.


  Recent advances in single macromolecule experiments have sparked interest in
the ensemble dependence of force-extension relations. The thermodynamic limit
may not be attainable for such systems, that leads to inequivalence of the
fixed-force and the fixed-extension ensemble. We consider an ideal Gaussian
chain described by the Edwards Hamiltonian with one end tethered to a rigid
planar substrate. We analytically calculate the force-extension relation in the
two ensembles and we show their inequivalence which is caused by the
confinement of the polymer to half space. The inequivalence is quite remarkable
for strong compressional forces. We also perform Monte-Carlo simulations of a
tethered wormlike chain with contour length 20 times its persistence length
which corresponds to experiments measuring the conformations of DNA tethered to
a wall. The simulations confirm the ensemble inequivalence and qualitatively
agree with the analytical predictions of the Gaussian model. Our analysis shows
that confinement due to tethering causes ensemble inequivalence, irrespective
of the polymer model.


  We report the discovery of a "dark area theorem," a new quantum optical
relation for propagation of unmatched pulses in thick three-level
$\Lambda$-type media. We define dark area and derive the dark area theorem for
a coherently prepared and inhomogeneously broadened lambda medium. We also
obtain the first equation for the spatial evolution of the dark state amplitude
prior to pulse-matching.


  We study the possibility of measuring neutrino Yukawa couplings in the
Next-to-Minimal Supersymmetric Standard Model with right-handed neutrinos
(NMSSMr) when the lightest Supersymmetric partner (a right-handed sneutrino) is
the Dark Matter (DM) candidate, by exploiting a `dijet + dilepton + Missing
Transverse Energy' (MET) signature. We show that, unlike the miminal
realisation of Supersymmetry (SUSY), i.e., the MSSM, for which the DM candidate
is a much heavier (fermionic) state (a neutralino), this non-minimal SUSY model
offers one with a much lighter (bosonic) state (a sneutrino) as DM, which can
be produced at future $e^+e^-$ colliders with energies up to about 500 GeV. The
emerging signal, from chargino pair production and subsequent decay, is
extremely pure so it allows for the possibility of extracting the Yukawa
parameters of the (s)neutrino sector. These results should then motivate
searches for light DM signals at such accelerators, where a DM candidate with
mass at the Electro-Weak (EW) scale can then be accessed.


  Given a locally compact group $G$ and $1\leq p<\infty$, a sufficient
condition ensuring the \emph{disjoint hypercyclicity} of finitely many weighted
translations on $L^p(G)$ was investigated in this paper.


  We propose a novel method of network detection that is robust against any
complex dependence structure. Our goal is to conduct exploratory network
detection, meaning that we attempt to detect a network composed of
``connectable'' edges that are worth investigating in detail for further
modelling or precise network analysis. For a reproducible network detection, we
pursuit high power while controlling the false discovery rate (FDR). In
particular, we formalize the problem as a multiple testing, and propose
p-variables that are used in the Benjamini-Hochberg procedure. We show that the
proposed method controls the FDR under arbitrary dependence structure with any
sample size, and has asymptotic power one. The validity is also confirmed by
simulations and a real data example.


  Hierarchical structure formation theory is based on the notion that mergers
drive galaxy evolution, so a considerable framework of semi-analytic models and
N-body simulations has been constructed to calculate how mergers transform a
growing galaxy. However, galaxy mergers are only one type of major dynamical
interaction between halos -- another class of encounter, a close flyby, has
been largely ignored. We analyze a 50 Mpc/h, $1024^3$ collisionless
cosmological simulation and find that the number of close flyby interactions is
comparable to, or even surpasses, the number of mergers for halo masses $\ga
10^{11}\,{h^{-1} M_\odot}$ at $z \la 2$. Halo flybys occur so frequently to
high mass halos that they are continually perturbed, unable to reach a
dynamical equilibrium. We also find tentative evidence that at high redshift,
$z \ga 14$, flybys are as frequent as mergers. Our results suggest that close
halo flybys can play an important role in the evolution of the earliest dark
matter halos and their galaxies, and can still influence galaxy evolution at
the present epoch.


  We describe a method to project photonic two-qubit states onto the symmetric
and antisymmetric subspaces of their Hilbert space. This device utilizes an
ancillary coherent state, together with a weak cross-Kerr non-linearity,
generated, for example, by electromagnetically induced transparency. The
symmetry analyzer is non-destructive, and works for small values of the
cross-Kerr coupling. Furthermore, this device can be used to construct a
non-destructive Bell state detector.


  Understanding biodiversity is a global challenge, in which DNA barcodes -
short snippets of DNA that cluster by species - play a pivotal role. In
particular, invertebrates, a highly diverse and under-explored group, pose
unique taxonomic complexities. We explore machine learning approaches,
comparing supervised CNNs, fine-tuned foundation models, and a DNA
barcode-specific masking strategy across datasets of varying complexity. While
simpler datasets and tasks favor supervised CNNs or fine-tuned transformers,
challenging species-level identification demands a paradigm shift towards
self-supervised pretraining. We propose BarcodeBERT, the first self-supervised
method for general biodiversity analysis, leveraging a 1.5 M invertebrate DNA
barcode reference library. This work highlights how dataset specifics and
coverage impact model selection, and underscores the role of self-supervised
pretraining in achieving high-accuracy DNA barcode-based identification at the
species and genus level. Indeed, without the fine-tuning step, BarcodeBERT
pretrained on a large DNA barcode dataset outperforms DNABERT and DNABERT-2 on
multiple downstream classification tasks. The code repository is available at
https://github.com/Kari-Genomics-Lab/BarcodeBERT


  Using the tight-binding method for the $\pi$-bands in MgB$_2$, the Hubbard
on-site Coulomb interaction on two inequivalent boron $p_z$-orbitals is
transformed into expressions in terms of $\pi$-band operators. For scattering
processes relevant to the problemin which a wave vector {\bf q} is parallel to
$\hat{z}$, it is found to take a relatively simple form consisting of
intra-band Coulomb scattering, interband pair scattering etc. with large
constant coupling constants. This allows to get a simple expression for the
amplitude of interband pair scattering between two $\pi$-bands, which diverges
if the interband polarization function in it becomes large enough.The latter
was approximately evaluated and found to be largely enhanced in the band
structure in MgB$_2$. These results lead to a divergent interband pair
scattering, meaning two-band-type superconducting instability with enhanced
$T_c$. Adding a subsidiary BCS attractive interaction in each band into
consideration, a semi-quantitative gap equation is given, and $T_c$ and isotope
exponent $\alpha$ are derived. The present instability is asserted to be the
origin of high $T_c$ in MgB$_2$.


  With the advancements in machine learning (ML) methods and compute resources,
artificial intelligence (AI) empowered systems are becoming a prevailing
technology. However, current AI technology such as deep learning is not
flawless. The significantly increased model complexity and data scale incur
intensified challenges when lacking trustworthiness and transparency, which
could create new risks and negative impacts. In this paper, we carve out AI
maintenance from the robustness perspective. We start by introducing some
highlighted robustness challenges in the AI lifecycle and motivating AI
maintenance by making analogies to car maintenance. We then propose an AI model
inspection framework to detect and mitigate robustness risks. We also draw
inspiration from vehicle autonomy to define the levels of AI robustness
automation. Our proposal for AI maintenance facilitates robustness assessment,
status tracking, risk scanning, model hardening, and regulation throughout the
AI lifecycle, which is an essential milestone toward building sustainable and
trustworthy AI ecosystems.


  Coupled backward and forward wave amplitudes of an electromagnetic field
propagating in a periodic and nonlinear medium at Bragg resonance are governed
by the nonlinear coupled mode equations (NLCME). This system of PDEs, similar
in structure to the Dirac equations, has gap soliton solutions that travel at
any speed between 0 and the speed of light. A recently considered strategy for
spatial trapping or capture of gap optical soliton light pulses is based on the
appropriate design of localized defects in the periodic structure. Localized
defects in the periodic structure give rise to defect modes, which persist as
{\it nonlinear defect modes} as the amplitude is increased. Soliton trapping is
the transfer of incoming soliton energy to {\it nonlinear} defect modes. To
serve as targets for such energy transfer, nonlinear defect modes must be
stable. We therefore investigate the stability of nonlinear defect modes.
Resonance among discrete localized modes and radiation modes plays a role in
the mechanism for stability and instability, in a manner analogous to the
nonlinear Schr\"odinger / Gross-Pitaevskii (NLS/GP) equation. However, the
nature of instabilities and how energy is exchanged among modes is considerably
more complicated than for NLS/GP due, in part, to a continuous spectrum of
radiation modes which is unbounded above and below. In this paper we (a)
establish the instability of branches of nonlinear defect states which, for
vanishing amplitude, have a linearization with eigenvalue embedded within the
continuous spectrum, (b) numerically compute, using Evans function, the
linearized spectrum of nonlinear defect states of an interesting multiparameter
family of defects, and (c) perform direct time-dependent numerical simulations
in which we observe the exchange of energy among discrete and continuum modes.


  To date, location privacy protection is a critical issue in Location-Based
Services (LBS). In this work, we propose a novel geometric framework based on
the classical discrete geometric structure, the Voronoi-Delaunay duality (VDD).
We utilize the fact that the user location cannot be recovered if only given an
irregular $n$-sided Voronoi cell around it, and the anonymity zone is the
intersection of all the parallel strips perpendicular to and bounded by $n$
Voronoi edges. The irregular Voronoi cell and its variations can be used as the
concealing space to hide the user location or the region of interest and
submitted to the LBS server. Within this framework, we propose multiple typical
anonymizing models by introducing irregularity to the convex regular VDD
structure by shifting the interior Voronoi cell, exterior Delaunay polygon,
sector rays, or their combinations. The proposed methods are efficient by
taking advantage of the VDD principle where main computations are linear
line-line intersections. Experiments with various parameters demonstrate the
efficiency and efficacy of the proposed $n$-VDD framework.


  Context-oriented programming (COP) is a new technique for programming that
allows changing the context in which commands execute as a program executes.
Compared to object-oriented programming (aspect-oriented programming), COP is
more flexible (modular and structured). This paper presents a precise
syntax-directed operational semantics for context-oriented programming with
layers, as realized by COP languages like ContextJ* and ContextL. Our language
model is built on Java enriched with layer concepts and activation and
deactivation of layer scopes. The paper also presents a static type system that
guarantees that typed programs do not get stuck. Using the means of the
proposed semantics, the mathematical correctness of the type system is
presented in the paper.


  Let $G$ be a simple algebraic group in defining characteristic $p>0$, and let
$V$ be an irreducible $G$-module which is the tensor product of exactly two
non-trivial modules. We obtain a criterion for $V$ to have the zero weight. In
addition, we provide a uniform criterion for an irreducible representation of a
simple Lie algebra over the complex numbers to have a multiple of a prescribed
fundamental weight.


  We conjecture that, in asymptotically anti-de Sitter space, two solutions of
the Wheeler-DeWitt equation that coincide asymptotically must also coincide in
the bulk. This suggests that the essential elements of holography are already
present in canonical gravity. Our argument sheds light on why holography works
only in gravitational theories, and also on the significance of anti-de Sitter
boundary conditions.


  Forty years ago, Apollo astronauts placed the first of several retroreflector
arrays on the lunar surface. Their continued usefulness for laser-ranging might
suggest that the lunar environment does not damage optical devices. However,
new laser ranging data reveal that the efficiency of the three Apollo reflector
arrays is now diminished by a factor of ten at all lunar phases and by an
additional factor of ten when the lunar phase is near full moon. These deficits
did not exist in the earliest years of lunar ranging, indicating that the lunar
environment damages optical equipment on the timescale of decades. Dust or
abrasion on the front faces of the corner-cube prisms may be responsible,
reducing their reflectivity and degrading their thermal performance when
exposed to face-on sunlight at full moon. These mechanisms can be tested using
laboratory simulations and must be understood before designing equipment
destined for the moon.


  Countermeasures to effectively fight the ever increasing hate speech online
without blocking freedom of speech is of great social interest. Natural
Language Generation (NLG), is uniquely capable of developing scalable
solutions. However, off-the-shelf NLG methods are primarily
sequence-to-sequence neural models and they are limited in that they generate
commonplace, repetitive and safe responses regardless of the hate speech (e.g.,
"Please refrain from using such language.") or irrelevant responses, making
them ineffective for de-escalating hateful conversations. In this paper, we
design a three-module pipeline approach to effectively improve the diversity
and relevance. Our proposed pipeline first generates various counterspeech
candidates by a generative model to promote diversity, then filters the
ungrammatical ones using a BERT model, and finally selects the most relevant
counterspeech response using a novel retrieval-based method. Extensive
Experiments on three representative datasets demonstrate the efficacy of our
approach in generating diverse and relevant counterspeech.


  Generalised regression estimation allows one to make use of available
auxiliary information in survey sampling. We develop three types of generalised
regression estimator when the auxiliary data cannot be matched perfectly to the
sample units, so that the standard estimator is inapplicable. The inference
remains design-based. Consistency of the proposed estimators is either given by
construction or else can be tested given the observed sample and links. Mean
square errors can be estimated. A simulation study is used to explore the
potentials of the proposed estimators.


  We present the identifications of a flux-limited sample of highly variable
X-ray sources on long time-scales from the second catalogue of the XMM$-$Newton
SLew survey (XMMSL2). The carefully constructed sample, comprising 265 sources
(2.5 per cent) selected from the XMMSL2 clean catalogue, displayed X-ray
variability of a factor of more than 10 in 0.2$-$2 keV compared to the ROSAT
All Sky Survey. Of the sample sources, 94.3 per cent are identified. The
identification procedure follows a series of cross-matches with astronomical
data bases and multiwavelength catalogues to refine the source position and
identify counterparts to the X-ray sources. Assignment of source type utilizes
a combination of indicators including counterparts offset, parallax
measurement, spectral colours, X-ray luminosity, and light-curve behaviour. We
identified 40 per cent of the variables with stars, 10 per cent with accreting
binaries, and at least 30.4 per cent with active galactic nuclei. The rest of
the variables are identified as galaxies. It is found that the mean effective
temperatures of the highly variable stars are lower than those of less variable
stars. Our sample of highly variable AGN tend to have lower black hole masses,
redshifts, and marginally lower soft X-ray luminosities compared to the less
variable ones, while no difference was found in the Eddington ratio
distributions. Five flaring events are tidal disruption events published
previously. This study has significantly increased the number of variable
sources in XMMSL2 with identifications and provides greater insight on the
nature of many of the sources, enabling further studies of highly variable
X-ray sources.


  The PHENIX experiment at RHIC measured K0S, eta and omega-meson production at
high pT in p+p, d+Au and Au+Au collisions at sqrt(s_NN)=200 GeV. Measurements
performed in different hadronic decay channels give consistent results. This
paper presents measured meson-to-pi0 ratios and Nuclear Modification factors in
the most central d+Au and Au+Au collisions. No suppression seen in d+Au
interactions is in contrast to a strong suppression of meson yields revealed in
central Au+Au collisions at the same energy.


  Mixing of the shell model (SM) eigenstates due to the coupling via the common
decay channel leads in many cases to the formation of a collective eigenstate
which carries many features of the nearby decay channel. This generic mechanism
in open quantum systems explains the phenomenological Ikeda diagram and
generalizes it for various clusters/correlations in the vicinity of the
respective cluster decay thresholds. The near-threshold collectivization of the
SM states may also influence their electromagnetic decays. We discuss this
phenomenon on the example of B(EL) decays of near-threshold 2+ states in 14C.


  Integrating intelligent systems, such as robots, into dynamic group settings
poses challenges due to the mutual influence of human behaviors and internal
states. A robust representation of social interaction dynamics is essential for
effective human-robot collaboration. Existing approaches often narrow their
focus to facial expressions or speech, overlooking the broader context. We
propose employing an adapted Temporal Graph Networks to comprehensively
represent social interaction dynamics while enabling its practical
implementation. Our method incorporates temporal multi-modal behavioral data
including gaze interaction, voice activity and environmental context. This
representation of social interaction dynamics is trained as a link prediction
problem using annotated gaze interaction data. The F1-score outperformed the
baseline model by 37.0%. This improvement is consistent for a secondary task of
next speaker prediction which achieves an improvement of 29.0%. Our
contributions are two-fold, including a model to representing social
interaction dynamics which can be used for many downstream human-robot
interaction tasks like human state inference and next speaker prediction. More
importantly, this is achieved using a more concise yet efficient message
passing method, significantly reducing it from 768 to 14 elements, while
outperforming the baseline model.


  We study the finite temperature Hartree-Fock-BCS approximation for selected
stable Sn nuclei with zero-range Skyrme forces. Hartree Fock BCS approximation
allows for a straightforward interpretation of the results since it involves u
and v's which are not matrices as in HFB. Pairing transitions from superfluid
to the normal state are studied with respect to the temperature. The
temperature dependence of the nuclear radii and neutron skin are also analyzed.
An increase of proton and neutron radii is obtained in neutron rich nuclei
especially above the critical temperature. Using different Skyrme energy
functionals, it is found that the correlation between the effective mass in
symmetric nuclear matter and the critical temperature depends on the pairing
prescription. The temperature dependence of the nucleon effective mass is also
investigated, showing that proton and neutron effective masses display
different behavior below and above the critical temperature, due to the small
temperature dependence of the density.


  We consider a regulator willing to drive individual choices towards
increasing social welfare by providing incentives to a large population of
individuals.
  For that purpose, we formalize and solve the problem of finding an optimal
personalized-incentive policy: optimal in the sense that it maximizes social
welfare under an incentive budget constraint, personalized in the sense that
the incentives proposed depend on the alternatives available to each
individual, as well as her preferences.
  We propose a polynomial time approximation algorithm that computes a policy
within few seconds and we analytically prove that it is boundedly close to the
optimum.
  We then extend the problem to efficiently calculate the Maximum Social
Welfare Curve, which gives the maximum social welfare achievable for a range of
incentive budgets (not just one value).
  This curve is a valuable practical tool for the regulator to determine the
right incentive budget to invest.
  Finally, we simulate a large-scale application to mode choice in a French
department (about 200 thousands individuals) and illustrate the effectiveness
of the proposed personalized-incentive policy in reducing CO2 emissions.


  We introduce a generic bosonic model exemplifying that (spin) Meissner
currents can persist in insulating phases of matter. We consider two species of
interacting bosons on a lattice. Our model exhibits separation of charge (total
density) and spin (relative density): The charge sector is gapped in a bosonic
Mott insulator phase with total density one, while the spin sector remains
superfluid due to interspecies conversion. Coupling the spin sector to the
gauge fields yields a spin Meissner effect reflecting the long-range spin
superfluid coherence. We investigate the resulting phase diagram and describe
other possible spin phases of matter in the Mott regime possessing chiral
currents as well as a spin-density wave phase. The model presented here is
realizable in Josephson junction arrays and in cold atom experiments.


  A hyperbolic 0-metric on a surface with boundary is a hyperbolic metric on
its interior, exhibiting the boundary behavior of the standard metric on the
Poincar\'e disk. Consider the infinite-dimensional Teichm\"uller spaces of
hyperbolic 0-metrics on oriented surfaces with boundary, up to diffeomorphisms
fixing the boundary and homotopic to the identity. We show that these spaces
have natural symplectic structures, depending only on the choice of an
invariant metric on sl(2,R). We prove that these Teichm\"uller spaces are
Hamiltonian Virasoro spaces for the action of the universal cover of the group
of diffeomorphisms of the boundary. We give an explicit formula for the Hill
potential on the boundary defining the moment map. Furthermore, using
Fenchel-Nielsen parameters we prove a Wolpert formula for the symplectic form,
leading to global Darboux coordinates on the Teichm\"uller space.


  Although the Hamiltonian in quantum physics has to be a linear operator, it
is possible to make quantum systems behave as if their Hamiltonians contained
antilinear (i.e., semilinear or conjugate-linear) terms. For any given quantum
system, another system can be constructed that is physically equivalent to the
original one. It can be designed, despite the Wightman reconstruction theorem,
so that antilinear operators in the original system become linear operators in
the new system. Under certain conditions, these operators can then be added to
the new Hamiltonian. The new quantum system has some unconventional features, a
hidden degeneracy of the vacuum and a subtle distinction between the
Hamiltonian and the observable of energy, but the physical equivalence
guarantees that its states evolve like those in the original system and that
corresponding measurements produce the same results. The same construction can
be used to make time-reversal linear.


  On November 4th, 2010, the Deep Impact eXtended Investigation (DIXI)
successfully encountered comet 103P/Hartley 2, when it was at a heliocentric
distance of 1.06 AU. Spatially resolved near-IR spectra of comet Hartley 2 were
acquired in the 1.05-4.83 micron wavelength range using the HRI-IR
spectrometer. We present spectral maps of the inner ~10 kilometers of the coma
collected 7 minutes and 23 minutes after closest approach. The extracted
reflectance spectra include well-defined absorption bands near 1.5, 2.0, and
3.0 micron consistent in position, bandwidth, and shape with the presence of
water ice grains. Using Hapke's radiative transfer model, we characterize the
type of mixing (areal vs. intimate), relative abundance, grain size, and
spatial distribution of water ice and refractories. Our modeling suggests that
the dust, which dominates the innermost coma of Hartley 2 and is at a
temperature of 300K, is thermally and physically decoupled from the
fine-grained water ice particles, which are on the order of 1 micron in size.
The strong correlation between the water ice, dust, and CO2 spatial
distribution supports the concept that CO2 gas drags the water ice and dust
grains from the nucleus. Once in the coma, the water ice begins subliming while
the dust is in a constant outflow. The derived water ice scale-length is
compatible with the lifetimes expected for 1-micron pure water ice grains at 1
AU, if velocities are near 0.5 m/s. Such velocities, about three order of
magnitudes lower than the expansion velocities expected for isolated 1-micron
water ice particles [Hanner, 1981; Whipple, 1951], suggest that the observed
water ice grains are likely aggregates.


  Let $\{a_i\}_{i=1}^\ell$ be a strongly unimodal positive integer sequence
with peak position $k$. The rank of such sequence is defined to be $\ell-2k+1$.
Let $u(m,n)$ denote the number of sequences $\{a_i\}_{i=1}^\ell$ with rank $m$
and $\sum_{i=1}^{\ell} a_i=n$. Bringmann, Jennings-Shaffer, Mahlburg and
Rhoades conjectured that $\{u(m,n)\}_m$ is strongly log-concave for any fixed
$n$. Motivated by this conjecture, in this paper we prove the strongly
unimodality of $\{u(m,n)\}_m$, that is $u(m,n)>u(m+1,n)$ for $m\ge 0$ and $n\ge
\max\{6,{m+2\choose 2}\}$. This result gives supportive evidence for the above
conjecture. Moreover, we find a combinatorial interpretation of $u(m,n)$, which
leads to a new combinatorial interpretation of ${\rm ospt}(n)$. Furthermore,
using this new combinatorial interpretation, a lower bound and an asymptotic
formula on ${\rm ospt}(n)$ will be presented.


  A range of nonlinear wave structures, including Langmuir waves, unipolar
electric fields and bipolar electric fields, are often observed in association
with whistler-mode chorus waves in the near-Earth space. We demonstrate that
the three seemingly different nonlinear wave structures originate from the same
nonlinear electron trapping process by whistler-mode chorus waves. The ratio of
the Landau resonant velocity to the electron thermal velocity controls the type
of nonlinear wave structures that will be generated.


  Finding solutions to the classical transportation problem is of great
importance, since this optimization problem arises in many engineering and
computer science applications. Especially the Earth Mover's Distance is used in
a plethora of applications ranging from content-based image retrieval, shape
matching, fingerprint recognition, object tracking and phishing web page
detection to computing color differences in linguistics and biology. Our
starting point is the well-known revised simplex algorithm, which iteratively
improves a feasible solution to optimality. The Shortlist Method that we
propose substantially reduces the number of candidates inspected for improving
the solution, while at the same time balancing the number of pivots required.
Tests on simulated benchmarks demonstrate a considerable reduction in
computation time for the new method as compared to the usual revised simplex
algorithm implemented with state-of-the-art initialization and pivot
strategies. As a consequence, the Shortlist Method facilitates the computation
of large scale transportation problems in viable time. In addition we describe
a novel method for finding an initial feasible solution which we coin Modified
Russell's Method.


  Turbulent mixing in the radiative regions of stars is usually either ignored
or crudely accounted for in most stellar evolution models. However, there is
growing theoretical and observational evidence that such mixing is present and
can affect various aspects of a star's life. In this work, we present a first
attempt at quantifying mixing by horizontal shear instabilities in stars using
Direct Numerical Simulations. The shear is driven by a body force, and rapidly
becomes unstable. At saturation, we find that several distinct dynamical
regimes exist, depending on the relative importance of stratification and
thermal diffusion (viscosity can in principle also matter, but is usually
negligible in most stellar applications). In each of the regimes identified, we
put forward a certain number of theoretically motivated scaling laws for the
turbulent vertical eddy scale, the typical turbulent diffusion coefficient, and
the typical amplitude of temperature fluctuations (among other quantities).
Based on our findings, we predict that the majority of stars should fall into
one of two categories: high P\'eclet number stratified turbulence, and low
P\'eclet number stratified turbulence. The latter is presented in detail in a
related paper by Cope et al. (2020), while the former is discussed here.
Applying our results to the best-known stellar shear layer, namely the solar
tachocline, we find that it should lie in the high P\'eclet number stratified
turbulence regime, and predict a substantial amount of vertical mixing for
temperature, momentum and composition. Taken as is, the new turbulence model
predictions are incompatible with the Spiegel & Zahn (1992) model of the solar
tachocline. However, we also show that rotation and magnetic fields are likely
to affect the turbulence, and need to be taken into account in future studies.


  We study the relaxation dynamics of a quantum dot with local Coulomb
correlations coupled to two noninteracting leads which are held in
grandcanonical equilibrium. Only charge degrees of freedom are considered and
the dot is described by a model which in the scaling limit becomes equivalent
to the interacting resonant level model. The time evolution of the current and
dot occupancy resulting out of changes of the dot-lead coupling, the dots
onsite energy, or the charging energy are studied. Abrupt and smooth parameter
changes as well as setups with and without driving bias voltage are considered.
For biased dots we investigate the often studied response after turning on the
dot-lead coupling but also the experimentally more relevant case in which the
voltage is turned on. We identify and explain a variety of interesting
many-body effects and clarify the role of initial correlations.


  The minimum time function $T(\cdot)$ of smooth control systems is known to be
locally semiconcave provided Petrov's controllability condition is satisfied.
Moreover, such a regularity holds up to the boundary of the target under an
inner ball assumption. We generalize this analysis to differential inclusions,
replacing the above hypotheses with the continuity of $T(\cdot)$ near the
target, and an inner ball property for the multifunction associated with the
dynamics. In such a weakened set-up, we prove that the hypograph of $T(\cdot)$
satisfies, locally, an exterior sphere condition. As is well-known, this
geometric property ensures most of the regularity results that hold for
semiconcave functions, without assuming $T(\cdot)$ to be Lipschitz.


  This is the report on new development of an automated precision load-based
measurement setup for thermoelectric power of different types of samples in the
temperature range 5 - 330 K. The problems in the old spring-based setup have
been solved by making load-based setup. This new setup takes nearly 4 h for
each run and typical error is within 5 %. A high quality calibration been
demonstrated using high purity platinum wires.


  High energy factorization predictions for F2c are derived using BFKL
resummations of leading logs for the proton structure functions at HERA. A
theoretical non-perturbative uncertainty on the factorization scheme is taken
into account by considering two different approaches for modelling the proton.
The parameters are fixed by a fit of F2 at small x. The resulting predictions
for F2c are in agreement with the data within the present error bars.


  Black holes are a recently observed theoretical prediction of General
Relativity, characterized by event horizons, from which information cannot
escape. Examined through the lenses of quantum mechanics, they can radiate at a
definite temperature inverse to their mass and horizon radius. Hawking
radiation, whose spectrum was calculated considering particles scattering off
black holes, is connected to the paradox of the loss of information falling
into them. Information can become non-fungible, due to scrambling. We
demonstrate this feature not to be restricted to curved space-times: soft
radiation scattering in a flat space-time does scramble information as well. To
this end, we compute the scrambling of information through the tripartite
mutual information in a scattering process off a black hole and compare it with
the flat space-time analog. We show that the scrambling power of the
gravitational field of a black hole is negligible with respect to the
scrambling power of flat space-time.


  I discuss the use of path integrals to study strong-interaction physics from
first principles. The underlying theory is cast into path integrals which are
evaluated numerically using Monte Carlo methods on a space-time lattice.
Examples are given on progress related to nuclear physics.


  We consider Hardy inequalities in $I R^n$, $n \geq 3$, with best constant
that involve either distance to the boundary or distance to a surface of
co-dimension $k<n$, and we show that they can still be improved by adding a
multiple of a whole range of critical norms that at the extreme case become
precisely the critical Sobolev norm.


  This paper proposes new derivations of three well-known sorting algorithms,
in their functional formulation. The approach we use is based on three main
ingredients: first, the algorithms are derived from a simpler algorithm, i.e.
the specification is already a solution to the problem (in this sense our
derivations are program transformations). Secondly, a mixture of inductive and
coinductive arguments are used in a uniform, algebraic style in our reasoning.
Finally, the approach uses structural invariants so as to strengthen the
equational reasoning with logical arguments that cannot be captured in the
algebraic framework.


  The problem of packing as many subgraphs isomorphic to $H \in \mathcal H$ as
possible in a graph for a class $\mathcal H$ of graphs is well studied in the
literature. Both vertex-disjoint and edge-disjoint versions are known to be
NP-complete for $H$ that contains at least three vertices and at least three
edges, respectively. In this paper, we consider ``list variants'' of these
problems: Given a graph $G$, an integer $k$, and a collection $\mathcal
L_{\mathcal H}$ of subgraphs of $G$ isomorphic to some $H \in \mathcal H$, the
goal is to compute $k$ subgraphs in $\mathcal L_{\mathcal H}$ that are pairwise
vertex- or edge-disjoint. We show several positive and negative results,
focusing on classes of sparse graphs, such as bounded-degree graphs, planar
graphs, and bounded-treewidth graphs.


  A periodic array of atomic sites, described within a tight binding formalism
is shown to be capable of trapping electronic states as it grows in size and
gets stubbed by an atom or an atomic clusters from a side in a deterministic
way. We prescribe a method based on a real space renormalization group method,
that unravels a subtle correlation between the positions of the side coupled
atoms and the energy eigenvalues for which the incoming particle finally gets
trapped. We discuss how, in such conditions, the periodic backbone gets
transformed into an array of infinite quantum wells in the thermodynamic limit.
We present a case here, where the wells have a hierarchically distribution of
widths, hosing standing wave solutions in the thermodynamic limit.


  Diffuse gamma rays are tracers of cosmic rays, providing information on their
origin, interaction and diffusion through a galaxy. M 31 (the Andromeda Galaxy)
is the closest spiral galaxy to the Milky Way (d = 780 kpc) and is very well
studied at all wavelengths. Thus it is a prime target for the study of diffuse
gamma-ray emission. The very-high-energy (VHE, E > 100 GeV) gamma-ray
observatory VERITAS has conducted 54 hours of observations of M 31 and an upper
limit on the VHE flux is presented along with an updated \Fermis (0.1 < E < 300
GeV) analysis. These observations will be compared with predictions of the
gamma-ray flux derived from models of the inelastic scattering of VHE cosmic
rays of the interstellar medium (ISM) and the interstellar radiation field. M
31 provides an ideal opportunity to probe this mechanism. Its proximity and
spatial extent, significantly larger than the VERITAS point spread function but
smaller than the field-of-view, potentially enables the star-forming ring, 10
kpc from the galaxy core, with its dense ISM and numerous supernova remnants to
be resolved.


  (abridged) Expanding the sample of directly imaged companions to nearby,
young stars that are amenable to detailed astrometric and spectroscopic studies
is critical for the continued development and validation of theories of their
evolution and atmospheric processes. The recent release of the {\it Gaia}
astrometric catalogue allows us to efficiently search for these elusive
companions by targeting those stars that exhibit the astrometric reflex motion
induced by an orbiting companion. The nearby (27 pc), young (24 Myr) star AF
Leporis (AF Lep) was targeted because of its astrometric acceleration,
consistent with a wide-orbit planetary companion detectable with high-contrast
imaging.
  We used the SPHERE instrument on the VLT to search for faint substellar
companions in the immediate vicinity of AF Lep. We used observations of a
nearby star interleaved with those of AF Lep to efficiently subtract the
residual point spread function. This provided sensitivity to faint
planetary-mass companions within 1 arcsec ($\sim$30 au) of the star. We
detected the companion AF Lep b at a separation of 339 mas (9 au), within the
inner edge of its unresolved debris disk. The measured $K$-band contrast and
the age of the star yield a model-dependent mass of 4 and 6 $M_{\rm Jup}$,
consistent with the mass derived from an orbital fit of $4.3_{-1.2}^{+2.9}$
$M_{\rm Jup}$. The near-infrared SED of the planet is consistent with an object
at the L--T spectral type transition, but under-luminous with respect to
field-gravity objects.
  AF Lep b joins a growing number of substellar companions imaged around stars
in the young $\beta$ Pic moving group. With a mass of between 3 and 7 $M_{\rm
Jup}$, it occupies a gap in this isochronal sequence between the hotter, more
massive companions like PZ~Tel~B and $\beta$~Pic~b, and the cooler 51~Eri~b,
which is sufficiently cool for methane to form within its photosphere.


  Vehicle-based mobile sensing (a.k.a drive-by sensing) is an important means
of surveying urban environment by leveraging the mobility of public or private
transport vehicles. Buses, for their extensive spatial coverage and reliable
operations, have received much attention in drive-by sensing. Existing studies
have focused on the assignment of sensors to a set of lines or buses with no
operational intervention, which is typically formulated as set covering or
subset selection problems. This paper aims to boost the sensing power of bus
fleets through active scheduling, by allowing instrumented buses to circulate
across multiple lines to deliver optimal sensing outcome. We consider a fleet
consisting of instrumented and normal buses, and jointly optimize sensor
assignment, bus dispatch, and intra- or inter-line relocations, with the
objectives of maximizing sensing quality and minimizing operational costs,
while serving all timetabled trips. By making general assumptions on the
sensing utility function, we formulate the problem as a nonlinear integer
program based on a time-expanded network. A batch scheduling algorithm is
developed following linearization techniques to solve the problem efficiently,
which is tested in a real-world case study in Chengdu, China. The results show
that the proposed scheme can improve the sensing objective by 12.0%-20.5%
(single-line scheduling) and 16.3%-32.1% (multi-line scheduling), respectively,
while managing to save operational costs by 1.0%. Importantly, to achieve the
same level of sensing quality, we found that the sensor investment can be
reduced by over 33% when considering active bus scheduling. Comprehensive
comparative and sensitivity analyses are presented to generate managerial
insights and recommendations for practice.


  New photometric series of BE Lyncis are presented. With template curve
fitting we re-determined the $O-C$ for BE Lyncis. The phase shift diagram is
apparently constant, disproving the suspected period variations of BE Lyn.


  Ulrich ideals in numerical semigroup rings of small multiplicity are studied.
If the semigroups are three-generated but not symmetric, the semigroup rings
are Golod, since the Betti numbers of the residue class fields of the semigroup
rings form an arithmetic progression; therefore, these semigroup rings are
G-regular, possessing no Ulrich ideals. Nevertheless, even in the
three-generated case, the situation is different, when the semigroups are
symmetric. We shall explore this phenomenon, describing an explicit system of
generators, that is the normal form of generators, for the Ulrich ideals in the
numerical semigroup rings of multiplicity at most 3. As the multiplicity is
greater than $3$, in general the task of determining all the Ulrich ideals
seems formidable, which we shall experience, analyzing one of the simplest
examples of semigroup rings of multiplicity $4$.


  We experimentally study a nonlinear optical approach to selective
manipulation and detection of structured images mixed with turbulent noise.
Unlike any existing adaptive-optics method by applying compensating modulation
directly on the images, here we account for the turbulence indirectly, by
modulating only the pump driving the nonlinear process but not the images
themselves. This indirect approach eliminates any signal modulation loss or
noise, while allowing more flexible and capable operations. Using specifically
sum frequency generation in a lithium niobate crystal, we demonstrate selective
upconversion of Laguerre-Gaussian spatial modes mixed with turbulent noise. The
extinction reaches $\sim$40 dB without turbulence, and maintains $\sim$20 dB in
the presence of strong turbulence. This technique could find utilities in
classical and quantum communications, compressive imaging, pattern recognition,
and so on.


  AI technology has a long history which is actively and constantly changing
and growing. It focuses on intelligent agents, which contain devices that
perceive the environment and based on which takes actions in order to maximize
goal success chances. In this paper, we will explain the modern AI basics and
various representative applications of AI. In the context of the modern
digitalized world, AI is the property of machines, computer programs, and
systems to perform the intellectual and creative functions of a person,
independently find ways to solve problems, be able to draw conclusions and make
decisions. Most artificial intelligence systems have the ability to learn,
which allows people to improve their performance over time. The recent research
on AI tools, including machine learning, deep learning and predictive analysis
intended toward increasing the planning, learning, reasoning, thinking and
action taking ability. Based on which, the proposed research intends towards
exploring on how the human intelligence differs from the artificial
intelligence. Moreover, we critically analyze what AI of today is capable of
doing, why it still cannot reach human intelligence and what are the open
challenges existing in front of AI to reach and outperform human level of
intelligence. Furthermore, it will explore the future predictions for
artificial intelligence and based on which potential solution will be
recommended to solve it within next decades.


  In this note we define circular k-successions in permutations in one-line
notation and count permutations that avoid substrings j(j+k) and j(j+k) (mod
n). We also count circular permutations that avoid such substrings, and show
that for substrings j(j+k) (mod n), the number of permutations depends on
whether n is prime, and more generally, on whether n and k are relatively
prime.


  We introduce TADA, a simple-yet-effective approach that takes textual
descriptions and produces expressive 3D avatars with high-quality geometry and
lifelike textures, that can be animated and rendered with traditional graphics
pipelines. Existing text-based character generation methods are limited in
terms of geometry and texture quality, and cannot be realistically animated due
to inconsistent alignment between the geometry and the texture, particularly in
the face region. To overcome these limitations, TADA leverages the synergy of a
2D diffusion model and an animatable parametric body model. Specifically, we
derive an optimizable high-resolution body model from SMPL-X with 3D
displacements and a texture map, and use hierarchical rendering with score
distillation sampling (SDS) to create high-quality, detailed, holistic 3D
avatars from text. To ensure alignment between the geometry and texture, we
render normals and RGB images of the generated character and exploit their
latent embeddings in the SDS training process. We further introduce various
expression parameters to deform the generated character during training,
ensuring that the semantics of our generated character remain consistent with
the original SMPL-X model, resulting in an animatable character. Comprehensive
evaluations demonstrate that TADA significantly surpasses existing approaches
on both qualitative and quantitative measures. TADA enables creation of
large-scale digital character assets that are ready for animation and
rendering, while also being easily editable through natural language. The code
will be public for research purposes.


  We show that the vector bundle associated to a smooth projective connected
finite covering of a simple complex abelian variety is ample (under a simple
necessary condition). This result is obtained by showing that this bundle is
M-regular in the sense of Pareschi-Popa, and that any M-regular sheaf is ample.


  We present a design of a stripline kicker for Integrable Optics Test
Accelerator (IOTA). For its experimental program IOTA needs two full-aperture
kickers, capable to create an arbitrary controllable kick in 2D. For that
reason their strengths are variable in a wide range of amplitudes up to 16
mrad, and the pulse length 100 ns is less than a revolution period for
electrons. In addition, the kicker should have a physical aperture of 40 mm for
a proposed operation with proton beam, and an outer size of 70 mm to fit inside
existing quadrupole magnets to save space in the ring. Computer simulations
using CST Microwave Studio show high field uniformity and wave impedance close
to 50 {\Omega}.


  Polyhedral circle packings are generalizations of the Apollonian packing. We
develop the theory of the Apollonian group, Descartes quadratic form, and
related objects for all polyhedral packings. We use these tools to determine
the domain of absolute convergence of a generating function that can be
associated to any polyhedral packing. This domain of convergence is the Tits
cone for an infinite root system.


  The purpose of this paper is to give two applications of Fourier transforms
and generic vanishing theorems:
  - we give a cohomological characterization of principal polarizations
  - we prove that if $X$ an abelian variety and $\Theta $ a polarization of
type $(1,...,1,2)$, then a general pair $(X,\Theta )$ is log canonical