  Slowing down phenomena occur in both deterministic and stochastic dynamical
systems at the vicinity of phase transitions or bifurcations. An example is
found in systems exhibiting a saddle-node bifurcation, which undergo a dramatic
time delay towards equilibrium. Specifically the duration of the transient,
$\tau$, close to this bifurcation in deterministic systems follows scaling laws
of the form $\tau \sim |\epsilon - \epsilon_c|^{-1/2}$, where $\epsilon$ is the
bifurcation or control parameter, and $\epsilon_c$ its critical value. For
systems undergoing a saddle-node bifurcation, the mechanism involves transients
getting trapped by a so-called ghost. In a recent article we explored how
intrinsic noise affected the deterministic picture. Extensive numerical
simulations showed that, although scaling behaviour persisted in the presence
of noise, the scaling law was more complicated than a simple power law. In
order to gain deeper insight into this scaling behaviour, we resort to the WKB
asymptotic approximation of the Master Equation. According to this
approximation, the behaviour of the system is given as the weighted sum of
\emph{trajectories} within the phase space of the Hamiltonian associated to the
corresponding Hamilton-Jacobi equation. By analysing the flight time of the
Hamilton equations, we show that the statistically significant paths follow a
scaling function that exactly matches the one observed in the stochastic
simulations. We therefore put forward that the properties of the flight times
of the Hamiltonian system underpin the scaling law of the underlying stochastic
system, and that the same properties should extend in a universal way to all
stochastic systems whose associated Hamiltonian exhibits the same behaviour.


  Price volatility in global food commodities is a critical signal indicating
potential disruptions in the food market. Understanding forthcoming changes in
these prices is essential for bolstering food security, particularly for
nations at risk. The Food and Agriculture Organization of the United Nations
(FAO) previously developed sophisticated statistical frameworks for the
proactive prediction of food commodity prices, aiding in the creation of global
early warning systems. These frameworks utilize food security indicators to
produce accurate forecasts, thereby facilitating preparations against potential
food shortages. Our research builds on these foundations by integrating robust
price security indicators with cutting-edge deep learning (DL) methodologies to
reveal complex interdependencies. DL techniques examine intricate dynamics
among diverse factors affecting food prices. Through sophisticated time-series
forecasting models coupled with a classification model, our approach enhances
existing models to better support communities worldwide in advancing their food
security initiatives.


  This paper focuses on a one-dimensional fourth-order nonlinear dispersive
partial differential equation for curve flows on a K\"ahler manifold. The
equation arises as a fourth-order extension of the one-dimensional
Schr\"odinger flow equation, with physical and geometrical backgrounds. First,
this paper presents a framework that can transform the equation into a system
of fourth-order nonlinear dispersive partial differential-integral equations
for complex-valued functions. This is achieved by developing the so-called
generalized Hasimoto transformation, which enables us to handle general
higher-dimensional compact K\"ahler manifolds. Second, this paper demonstrates
the computations to obtain the explicit expression of the derived system for
three examples of the compact K\"ahler manifolds, dealing with the complex
Grassmannian as an example in detail.


  The training paradigm for machine translation has gradually shifted, from
learning neural machine translation (NMT) models with extensive parallel
corpora to instruction finetuning on multilingual large language models (LLMs)
with high-quality translation pairs. In this paper, we focus on boosting
many-to-many multilingual translation of LLMs with an emphasis on zero-shot
translation directions. We demonstrate that prompt strategies adopted during
finetuning are crucial to zero-shot translation and introduce a cross-lingual
consistency regularization, XConST, to bridge the representation gap among
different languages and improve zero-shot translation performance. XConST is
not a new method, but a version of CrossConST (Gao et al., 2023a) adapted for
translation instruction finetuning with LLMs. Experimental results on ALMA (Xu
et al., 2023), Tower (Team, 2024), and LLaMA-2 (Touvron et al., 2023) show that
our approach consistently improves translation performance. Our implementations
are available at https://github.com/gpengzhi/CrossConST-LLM.


  Wireless sensor nodes are powered by batteries, for which replacement is very
difficult. That is why, optimization of energy consumption is a major objective
in the area of wireless sensor networks (WSNs).On the other hand, noisy channel
has a prominent influence on the reliability of data transmission. Therefore,
an energy efficient transmission strategy should be considered on the
communication process of wireless nodes in order to obtain optimal energy
network consumption. Indeed, the choice of suitable modulation format with the
proper Error Correcting code (ECC) played a great responsibility to obtain
better energy conservation.In this work, we aim to evaluate the performance
analysis of Gaussian Minimum Shift Keying (GMSK) modulation with several
combinations of coding strategies using various analysis metrics such as Bit
Error Rate (BER), energy consumption.Through extensive simulation, we disclose
that he gain achieved through GMSK modulation with suitable channel coding
mechanism is promising to obtain reliable communication and energy conservation
in WSN.


  In recent years, reinforcement learning (RL) has acquired a prominent
position in health-related sequential decision-making problems, gaining
traction as a valuable tool for delivering adaptive interventions (AIs).
However, in part due to a poor synergy between the methodological and the
applied communities, its real-life application is still limited and its
potential is still to be realized. To address this gap, our work provides the
first unified technical survey on RL methods, complemented with case studies,
for constructing various types of AIs in healthcare. In particular, using the
common methodological umbrella of RL, we bridge two seemingly different AI
domains, dynamic treatment regimes and just-in-time adaptive interventions in
mobile health, highlighting similarities and differences between them and
discussing the implications of using RL. Open problems and considerations for
future research directions are outlined. Finally, we leverage our experience in
designing case studies in both areas to showcase the significant collaborative
opportunities between statistical, RL, and healthcare researchers in advancing
AIs.


  The use of cellular networks for massive machine-type communications (mMTC)
is an appealing solution due to the wide availability of cellular
infrastructure. Estimating the number of devices (network load) is vital for
efficient allocation of the available resources, especially for managing the
random access channel (RACH) of the network. This paper considers a
two-priority RACH and proposes two network load estimators: a maximum
likelihood (ML) estimator and a reduced complexity (RCML) variant. The
estimators are based on a novel model of the random access behavior of the
devices coupled with a flexible analytical framework to calculate the involved
probabilities. Monte Carlo simulations demonstrate the accuracy of the proposed
estimators for different network configurations.


  Statistical modeling of spatiotemporal phenomena often requires selecting a
covariance matrix from a covariance class. Yet standard parametric covariance
families can be insufficiently flexible for practical applications, while
non-parametric approaches may not easily allow certain kinds of prior knowledge
to be incorporated. We propose instead to build covariance families out of
geodesic curves. These covariances offer more flexibility for problem-specific
tailoring than classical parametric families, and are preferable to simple
convex combinations. Once the covariance family has been chosen, one typically
needs to select a representative member by solving an optimization problem,
e.g., by maximizing the likelihood of a data set. We consider instead a
differential geometric interpretation of this problem: minimizing the geodesic
distance to a sample covariance matrix ("natural projection"). Our approach is
consistent with the notion of distance employed to build the covariance family
and does not require assuming a particular probability distribution for the
data. We show that natural projection and maximum likelihood estimation within
the covariance family are locally equivalent up to second order. We also
demonstrate that natural projection may yield more accurate estimates with
noise-corrupted data.


  Surgeon hand tremor limits human capability during microsurgical procedures
such as those that treat the eye. In contrast, elimination of hand tremor
through the introduction of microsurgical robots diminishes the surgeon's
tactile perception of useful and familiar tool-to-sclera forces. While the
large mass and inertia of eye surgical robot prevents surgeon microtremor, loss
of perception of small scleral forces may put the sclera at risk of injury. In
this paper, we have applied and compared two different methods to assure the
safety of sclera tissue during robot-assisted eye surgery. In the active
control method, an adaptive force control strategy is implemented on the
Steady-Hand Eye Robot in order to control the magnitude of scleral forces when
they exceed safe boundaries. This autonomous force compensation is then
compared to a passive force control method in which the surgeon performs manual
adjustments in response to the provided audio feedback proportional to the
magnitude of sclera force. A pilot study with three users indicate that the
active control method is potentially more efficient.


  In this paper, we constrain CP violation in the Higgs sector using the
measured signal strengths in the various Higgs search channels. To this end, we
introduce a general parameterization for a resonance which is an admixture of a
CP-even Higgs-like state and a CP-odd scalar. By performing a fit to the
available data from the Tevatron and LHC experiments one obtains constraints on
the mixing angle and the couplings of the resonance to Standard Model fields.
Depending on the couplings, sizable mixing angles are still compatible with the
data, but small mixing is in general preferred by the fit. In particular we
find that a pure CP-odd state is disfavored by the current data at the 3 sigma
level. Additionally we consider a mixed fermiophobic resonance and a model with
two degenerate mixed resonances and find that both scenarios can successfully
fit the data within current errors. Finally, we estimate that the mixing angle
can be constrained to \alpha < 1.1 (0.7) in the full 8 TeV (14 TeV) run of the
LHC.


  We investigate the phase diagram of a bilayer Kitaev honeycomb model with
Ising interlayer interactions, deriving effective models via perturbation
theory and performing Majorana mean-field theory calculations. We show that a
diverse array of magnetic and topological phase transitions occur, depending on
the direction of the interlayer Ising interaction and the relative sign of
Kitaev interactions. When two layers have the same sign of the Kitaev
interaction, a first-order transition from a Kitaev spin liquid to a
magnetically ordered state takes place. The magnetic order points along the
Ising axis and it is (anti)ferromagnetic for (anti)ferromagnetic Kitaev
interactions. However, when two layers have opposite sign of the Kitaev
interaction, we observe a notable weakening of magnetic ordering tendencies and
the Kitaev spin liquid survives up to a remarkably larger interlayer exchange.
Our mean-field analysis suggests the emergence of an intermediate gapped
$\mathbb{Z}_2$ spin liquid state, which eventually becomes unstable upon vison
condensation. The confined phase is described by a highly frustrated
$120^\circ$ compass model. We furthermore use perturbation theory to study the
model with the Ising axis pointing along $\hat{z}$-axis or lying in the
$xy$-plane. In both cases, our analysis reveals the formation of 1D Ising
chains, which remain decoupled in perturbation theory, resulting in a
subextensive ground-state degeneracy. Our results highlight the interplay
between topological order and magnetic ordering tendencies in bilayer quantum
spin liquids.


  We prove that the limit points of the bass notes of arithmetic hyperbolic
surfaces are the interval $\left[0,\frac{1}{4}\right]$.


  We develop a Bayesian non-parametric quantile panel regression model. Within
each quantile, the response function is a convex combination of a linear model
and a non-linear function, which we approximate using Bayesian Additive
Regression Trees (BART). Cross-sectional information at the pth quantile is
captured through a conditionally heteroscedastic latent factor. The
non-parametric feature of our model enhances flexibility, while the panel
feature, by exploiting cross-country information, increases the number of
observations in the tails. We develop Bayesian Markov chain Monte Carlo (MCMC)
methods for estimation and forecasting with our quantile factor BART model
(QF-BART), and apply them to study growth at risk dynamics in a panel of 11
advanced economies.


  Adapting pretrained large language models (LLMs) to various downstream tasks
in tens or hundreds of human languages is computationally expensive.
Parameter-efficient fine-tuning (PEFT) significantly reduces the adaptation
cost, by tuning only a small amount of parameters. However, common PEFT methods
LoRA (Hu et al., 2022) suffer from suboptimal performance on diverse dataset
mixtures, due to aggressive parameter tying and negative interference among
different datasets. In this work, we propose Featurized Low-rank Mixtures
(FLix), a novel PEFT method designed for effective multitask multilingual
adaptation. FLix associates each unique dataset feature, such as the dataset's
language or task, with its own low-rank weight update parameters. By composing
feature-specific parameters for each dataset, FLix can accommodate diverse
dataset mixtures and generalize better to unseen datasets. Our experiments show
that FLix leads to significant improvements over a variety of tasks for both
supervised learning and zero-shot settings with gains of up to $14.2$ inexact
match points in zero-shot semantic parsing.


  We apply a 3-dimensional approach to describe a new parametrization of the
L-operators for the 2-dimensional Bazhanov-Stroganov (BS) integrable spin model
related to the chiral Potts model. This parametrization is based on the
solution of the associated classical discrete integrable system. Using a
3-dimensional vertex satisfying a modified tetrahedron equation, we construct
an operator which generalizes the BS quantum intertwining matrix S. This
operator describes the isospectral deformations of the integrable BS model.


  We prove explicit formulas for certain first and second moment sums of
families of Gaussian hypergeometric functions $_{n+1}F_n$, $n\ge1$, over finite
fields with $q$ elements where $q$ is an odd prime. This enables us to find an
estimate for the value $_6F_5(1)$. In addition, we evaluate certain second
moments of traces of the family of Clausen elliptic curves in terms of the
value $_3F_2(-1)$. These formulas also allow us to express the product of
certain $_2F_1$ and $_{n+1}F_n$ functions in terms of finite field Appell
series which generalizes current formulas for products of $_2F_1$ functions. We
finally give closed form expressions for sums of Gaussian hypergeometric
functions defined using different multiplicative characters.


  Families of representations of suitable Banach algebras provide a powerful
tool in the study of the spectral theory of (pseudo)differential operators and
of their Fredholmness. We introduce the new concept of an exhausting family of
representations of a C*-algebra A. An {\em exhausting family} of
representations of a C*-algebra A is a set F of representations of A with the
property that every irreducible representation of A is weakly contained in some
\phi \in F. An exhausting family F of representations of A has the property
that `"a \in A is invertible if, and if, \phi(a) is invertible for any \phi \in
F." Consequently, the spectrum of a is given by \Spec(a) = \cup_{\phi \in F}
\Spec(\phi(a)). In other words, every exhausting family of representations is
invertibility sufficient, a concept introduced by Roch in 2003. We prove
several properties of exhausting families and we provide necessary and
sufficient conditions for a family of representations to be exhausting. Using
results of Ionescu and Williams (2009), we show that the regular
representations of amenable, second countable, locally compact groupoids with a
Haar system form an exhausting family of representations. If $A$ is a separable
C*-algebra, we show that a family F of representations of $A$ is exhausting if,
and only if, it is invertibility sufficient. However, this result is not true,
in general, for non-separable C*-algebras. With an eye towards applications, we
extend our results to the case of unbounded operators. A typical application of
our results is to parametric families of differential operators arising in the
analysis on manifolds with corners, in which case we recover the fact that a
parametric operator F is invertible if, and only if, its Mellin transform is
invertible. In view of possible applications, we have tried to make this paper
accessible to non-specialists in C*-algebras.


  The asymptotic properties of the solutions to the Einstein-Maxwell equations
with boost-rotation symmetry and Petrov type D are studied. We find series
solutions to the pertinent set of equations which are suitable for a late time
descriptions in coordinates which are well adapted for the description of the
radiative properties of spacetimes (Bondi coordinates). By calculating the
total charge, Bondi and NUT mass and the Newman-Penrose constants of the
spacetimes we provide a physical interpretation of the free parameters of the
solutions. Additional relevant aspects on the asymptotics and radiative
properties of the spacetimes considered, such as the possible polarization
states of the gravitational and electromagnetic field, are discussed through
the way.


  In the frame of Wave Universe Concept (WU Concept) it is presented the
alternative approach to the effective description of Elementar Objects of
Matter (EOM) of micro and megaworld hierarchy, in particular, of particles in
subatomic physics.
  According to the Wave Universe Concept (WU Concept), discrete spectrum of EOM
is close connected, generate by universal spectrum of physically preferable,
elite velocities in the Universe.
  The special attantion to analysis and precise description of central set of
EOM - stationary states (of EOM) is payed.
  In particular, sufficiently precise representations for mass values, cross
relations between masses of main important objects of particle physics (proton,
pion, main mesons, etc.) are obtained.
  Obtained representations for the hierarchy of characteristic dimensional
parameters, for instance, for the mass spectrum - mass formula are not
contained any divergencies - its are simple, compact, possess clear physical
sence and have not any kind of fitting parameters. With this, the competence
field of these representations is practically indefinitely - apparently, "all"
Wave Universe for wide set EOM of micro and megaworld.


  We have calculated elastic and state-resolved inelastic cross sections for
cold and ultracold collisions in the Rb($^1 S$) + OH($^2 \Pi_{3/2}$) system,
including fine-structure and hyperfine effects. We have developed a new set of
five potential energy surfaces for Rb-OH($^2 \Pi$) from high-level {\em ab
initio} electronic structure calculations, which exhibit conical intersections
between covalent and ion-pair states. The surfaces are transformed to a
quasidiabatic representation. The collision problem is expanded in a set of
channels suitable for handling the system in the presence of electric and/or
magnetic fields, although we consider the zero-field limit in this work.
Because of the large number of scattering channels involved, we propose and
make use of suitable approximations. To account for the hyperfine structure of
both collision partners in the short-range region we develop a
frame-transformation procedure which includes most of the hyperfine
Hamiltonian. Scattering cross sections on the order of $10^{-13}$ cm$^2$ are
predicted for temperatures typical of Stark decelerators. We also conclude that
spin orientation of the partners is completely disrupted during the collision.
Implications for both sympathetic cooling of OH molecules in an environment of
ultracold Rb atoms and experimental observability of the collisions are
discussed.


  Phase diagram of a spin-ice type Kondo lattice model, potentially relevant to
metallic pyrochlore oxides, is obtained by the Monte Carlo simulation
implementing the polynomial expansion technique up to the system size with 2048
sites. We identified a new 32-sublattice magnetic phase with concomitant charge
disproportionation, along with other phases such as two-in two-out and
all-in/all-out orders. The spin and charge pattern can be switched by external
magnetic field to a different one accompanied by a half magnetization plateau.


  In this study, we present a novel swarm-based approach for generating
optimized stress-aligned trajectories for 3D printing applications. The method
utilizes swarming dynamics to simulate the motion of virtual agents along the
stress produced in a loaded part. Agent trajectories are then used as print
trajectories. With this approach, the complex global trajectory generation
problem is subdivided into a set of sequential and computationally efficient
quadratic programs. Through comprehensive evaluations in both simulation and
experiments, we compare our method with state-of-the-art approaches. Our
results highlight a remarkable improvement in computational efficiency,
achieving a 115x faster computation speed than existing methods. This
efficiency, combined with the possibility to tune the trajectories spacing to
match the deposition process constraints, makes the potential integration of
our approach into existing 3D printing processes seamless. Additionally, the
open-hole tensile specimen produced on a conventional fused filament
fabrication set-up with our algorithm achieve a notable ~10% improvement in
specific modulus compared to existing trajectory optimization methods.


  By their very nature, Spin Waves (SWs) consume ultra-low amounts of energy,
which makes them suitable for ultra-low energy consumption applications. In
addition, a compressor can be utilized to further reduce the energy consumption
and enhance the speed of a multiplier. Therefore, we propose a novel energy
efficient SW based 4-2 compressor consisting of 4 XOR gates and 2 Majority
gates. The proposed compressor is validated by means of micromagnetic
simulations and compared with the state-of-the-art SW, 22nm CMOS, Magnetic
Tunnel Junction (MTJ), Domain Wall Motion (DWM), and Spin-CMOS technologies.
The performance evaluation shows that the proposed compressor consumes 2.5x
less and 1.25x less energy than the 22nm CMOS and the conventional SW
compressor, respectively, whereas it consumes at least 3 orders of magnitude
less energy than the MTJ, DWM, and Spin-CMOS designs. Furthermore, the
compressor achieves the smallest chip real-estate. In summary, the performance
evaluation of our proposed compressor shows that the SW technology has the
potential to progress the state-of-the-art circuit design in terms of energy
consumption and scalability.


  Long term exposure to biased content in literature or media can significantly
influence people's perceptions of reality, leading to the development of
implicit biases that are difficult to detect and address (Gerbner 1998). In
this study, we propose a novel method to analyze the differences in
representation between two groups and use it examine the representation of
African Americans and White Americans in books between 1850 to 2000 with the
Google Books dataset (Goldberg and Orwant 2013). By developing better tools to
understand differences in representation, we aim to contribute to the ongoing
efforts to recognize and mitigate biases. To improve upon the more common
phrase based (men, women, white, black, etc) methods to differentiate context
(Tripodi et al. 2019, Lucy; Tadimeti, and Bamman 2022), we propose collecting a
comprehensive list of historically significant figures and using their names to
select relevant context. This novel approach offers a more accurate and nuanced
method for detecting implicit biases through reducing the risk of selection
bias. We create group representations for each decade and analyze them in an
aligned semantic space (Hamilton, Leskovec, and Jurafsky 2016). We further
support our results by assessing the time adjusted toxicity (Bassignana,
Basile, and Patti 2018) in the context for each group and identifying the
semantic axes (Lucy, Tadimeti, and Bamman 2022) that exhibit the most
significant differences between the groups across decades. We support our
method by showing that our proposed method can capture known socio political
changes accurately and our findings indicate that while the relative number of
African American names mentioned in books have increased over time, the context
surrounding them remains more toxic than white Americans.


  Magnon-polarons are coherently mixed quasiparticles that originate from the
strong magnetoelastic coupling of lattice vibrations and spin waves in
magnetic-ordered materials. Recently, magnon-polarons have attracted a lot of
attention since they provide a powerful tool to manipulate magnons, which is
essential for magnon-based spintronic devices. In this work, we report the
experimental observation of facet-dependent magnon-polarons in epitaxial
ferrimagnetic Fe3O4 thin films via spin Seebeck effect measurement. The
critical magnetic fields for the magnon-polarons in the (110)- and
(100)-oriented Fe3O4 films are 1.5 T and 1.8 T, respectively, which arises from
the different phonon velocities along the [110] and [100] directions. As the
temperature decreases, the magnon-polarons-enhanced spin Seebeck voltage
decreases in both (110)- and (100)-oriented Fe3O4 films, which could be
attributed to the enhanced magnon-polarons scattering at elevated temperatures.
This work demonstrates the crystal structure engineering in epitaxial magnetic
films as a promising route to manipulate the magnon-polarons for future magnon
spintronic applications.


  We establish global well-posedness and scattering for the cubic Dirac
equation for small data in the critical space $H^1(\mathbb{R}^3)$. The main
ingredient is obtaining a sharp end-point Strichartz estimate for the
Klein-Gordon equation. In a classical sense this fails and it is related to the
failure of the endpoint Strichartz estimate for the wave equation in space
dimension three. In this paper, systems of coordinate frames are constructed in
which endpoint Strichartz estimates are recovered and energy estimates are
established.


  When a $\gamma$-ray interacts in a semiconductor detector, the resulting
electron-hole charge clouds drift towards their respective electrodes for
signal collection. These charge clouds will expand over time due to both
thermal diffusion and mutual electrostatic repulsion. Solutions to the
resulting charge profiles are well understood for the limiting cases accounting
for only diffusion and only repulsion, but the general solution including both
effects can only be solved numerically. Previous attempts to model these
effects have taken into account the broadening of the charge profile due to
both effects, but have simplified the shape of the profile by assuming Gaussian
distributions. However, the detailed charge profile can have important impacts
on charge sharing in multi-electrode strip detectors. In this work, we derive
an analytical approximation to the general solution, including both diffusion
and repulsion, that closely replicates both the width and the detailed shape of
the charge profiles. This analytical solution simplifies the modeling of charge
clouds in semiconductor strip detectors.


  We present our new, spatially-resolved, photometry in FUV and NUV from images
obtained by GALEX, and IRAC1 (3.6 $\mu$m) photometry obtained by the Spitzer
Space Telescope. We analyzed the surface brightness profiles $\mu_{\rm{FUV}}$,
$\mu_{\rm{NUV}}$, $\mu_{[3.6]}$, as well as the radial evolution of the
(FUV-NUV), (FUV - [3.6]), and (NUV - [3.6]) colors in the Spitzer Survey of
Stellar Structures in Galaxies (S$^{4}$G) galaxies (d$<$40 Mpc) sample. We
defined the GALEX Blue Sequence (GBS) and GALEX Red Sequence (GBR) from the
(FUV - NUV) versus (NUV - [3.6]) color-color diagram, populated by late-type
star forming galaxies and quiescent early-type galaxies respectively. While
most disk becomes radially bluer for GBS galaxies, and stay constant for GRS
galaxies, a large fraction ($>$50%) of intermediary GALEX Green Valley (GGV)
galaxies' outer disks are becoming redder. An outside-in quenching mechanism
such as environmentally-related mechanisms such as starvation or
ram-pressure-stripping could explain our results.


  We propose a novel study of generating unseen arbitrary viewpoints for
infrared imagery in the non-linear feature subspace . Current methods use
synthetic images and often result in blurry and distorted outputs. Our approach
on the contrary understands the semantic information in natural images and
encapsulates it such that our predicted unseen views possess good 3D
representations. We further explore the non-linear feature subspace and
conclude that our network does not operate in the Euclidean subspace but rather
in the Riemannian subspace. It does not learn the geometric transformation for
predicting the position of the pixel in the new image but rather learns the
manifold. To this end, we use t-SNE visualisations to conduct a detailed
analysis of our network and perform classification of generated images as a
low-shot learning task.


  We calculate the spin- and temperature-dependent local density of states for
ferromagnetic Ni in the presence of a core hole at a distinguished site in the
lattice. Correlations among the valence electrons and between valence and core
electrons are described within a multi-band Hubbard model which is treated by
means of second-order perturbation theory around the Hartree-Fock solution. The
core-hole potential causes strong screening effects in the Ni valence band. The
local magnetic moment is found to be decreased by a factor 5-6. The
consequences for the spin polarisation of CVV Auger electrons are discussed.


  Chemical separations are costly in terms of energy, time, and money.
Separation methods are optimized with inefficient trial-and-error approaches
that lack insight into the molecular dynamics that lead to the success or
failure of a separation and, hence, ways to improve the process. We perform
super-resolution imaging of fluorescent analytes in four different commercial
liquid chromatography materials. Surprisingly, we observe that chemical
functionalization can block over fifty percent of the porous interior of the
material, rendering it inaccessible to small molecule analytes. Only in situ
imaging unveils the inaccessibility when compared to the industry-accepted ex
situ characterization methods. Selectively removing some of the
functionalization with solvent restores pore access without significantly
altering the single-molecule kinetics that underlie the separation and agree
with bulk chromatography measurements. Our molecular results determine that
commercial stationary phases, marketed as fully porous, are over-functionalized
and provide a new avenue to characterize and direct separation material design
from the bottom-up.


  Let $T$ be an $m$-interval exchange transformation. By the rank of $T$ we
mean the dimension of the $\mathbb{Q}$-vector space spanned by the lengths of
the exchanged intervals. We prove that if $T$ is minimal and the rank of $T$ is
greater than $1+\lfloor m/2 \rfloor$, then $T$ cannot be written as a power of
another interval exchange. We also demonstrate that this estimate on the rank
cannot be improved. In the case that $T$ is a minimal 3-interval exchange
transformation, we prove a stronger result: $T$ cannot be written as a power of
another interval exchange if and only if $T$ satisfies Keane's infinite
distinct orbit condition. In the course of proving this result, we give a
classification (up to conjugacy) of those minimal IETs whose discontinuities
all belong to a single orbit.


  The Milky Way can act as a large-scale weak gravitational lens of the cosmic
microwave background (CMB). We study this effect using a photon ray-tracing
code and a Galactic mass distribution with disk, bulge and halo components. For
an observer at the Sun's coordinates in the Galaxy, the bending of CMB photon
paths is limited to less than one arcsecond, and only for rays that pass within
a few degrees of the Galactic Center. However, the entire sky is affected,
resulting in global distortions of the CMB on large angular scales. These
distortions can cause the low-order multipoles of a spherical harmonic
expansion of the CMB sky temperature to leak into higher-order modes. Thus the
component of the CMB dipole that results from the Local Group's motion relative
to the local cosmic frame of rest contributes to higher-order moments for an
observer in the solar system. With our ray-tracing code we show that the
phenomenon is not sensitive to the specific choice of Galactic potential. We
also quantitatively rule it out as a contributor to CMB anomalies such as power
asymmetry or correlated alignment of low-order multipole moments.


  Multi-messenger astronomy is a powerful tool to study the physical processes
driving the non-thermal Universe. A combination of observations in cosmic rays,
neutrinos, photons of all wavelengths and gravitational waves is expected. The
alert system of the Baikal-GVD detector under construction will allow for a
fast, on-line reconstruction of neutrino events recorded by the Baikal-GVD
telescope and - if predefined conditions are satisfied - for the formation of
an alert message to other communities. The preliminary results of searches for
high-energy neutrinos in coincidence with GW170817/GRB170817A using the cascade
mode of neutrino detection are discussed. Two Baikal-GVD clusters were
operating during 2017. The zenith angle of NGC 4993 at the detection time of
the GW170817 was 93.3 degrees. No events spatially coincident with GRB170817A
were found. Given the non-detection of neutrino events associated with
GW170817, upper limits on the neutrino fluence were established.


  Ultrasound (US) imaging is highly effective with regards to both cost and
versatility in real-time diagnosis; however, determination of fetal gender by
US scan in the early stages of pregnancy is also a cause of sex-selective
abortion. This work proposes a deep learning object detection approach to
accurately mask fetal gender in US images in order to increase the
accessibility of the technology. We demonstrate how the YOLOv5L architecture
exhibits superior performance relative to other object detection models on this
task. Our model achieves 45.8% AP[0.5:0.95], 92% F1-score and 0.006 False
Positive Per Image rate on our test set. Furthermore, we introduce a bounding
box delay rule based on frame-to-frame structural similarity to reduce the
false negative rate by 85%, further improving masking reliability.


  We summarize the new scaling algebra approach to the structural analysis of
the short distance behaviour of quantum field theories in the operator
algebraic formulation which has recently been proposed by D. Buchholz, R. Verch
(Rev. Math. Phys. 7(1995) 1195), and further studied by D. Buchholz (Ann. Inst.
H. Poincare' 64(1996) 433, Nucl. Phys. B469(1996) 333). We also report on an
extension of this framework to quantum field theory in curved spacetime.


  Let S be a compact Riemann surfaces of genus g >= 2 and G a conformal
automoprhism group of order n acting on S. In this paper we give the definition
of an adapted generating set and an adapted basis for the first homology group
of such a compact Riemann surface. This generating set and basis reflect the
action of G in as simple manner as possible. This can be seen in the matrix of
the action of G which we obtain. We prove the existence of such a generating
set and basis for any conformal group acting on such a surface and find the
matrix. This extends our earlier results on adapted bases and matrices for
automorphism groups of prime orders and other specific groups.


  We study the existence of quasistatic evolutions for a family of gradient
damage models which take into account fatigue, that is the process of weakening
in a material due to repeated applied loads. The main feature of these models
is the fact that damage is favoured in regions where the cumulation of the
elastic strain (or other relevant variables, depend on the model) is higher. To
prove the existence of a quasistatic evolution, we follow a vanishing viscosity
approach based on two steps: we first let the time-step $\tau$ of the
time-discretisation and later the viscosity parameter $\epsilon$ go to zero. As
$\tau \to 0$, we find $\epsilon$-approximate viscous evolutions; then, as
$\epsilon \to 0$, we find a rescaled approximate evolution satisfying an
energy-dissipation balance.


The paper has been withdraw by authors


  This paper introduces the first deep neural network-based estimation metric
for the jigsaw puzzle problem. Given two puzzle piece edges, the neural network
predicts whether or not they should be adjacent in the correct assembly of the
puzzle, using nothing but the pixels of each piece. The proposed metric
exhibits an extremely high precision even though no manual feature extraction
is performed. When incorporated into an existing puzzle solver, the solution's
accuracy increases significantly, achieving thereby a new state-of-the-art
standard.


  We present a study of the lensing properties of two-dimensional (2-D)
photonic quasicrystal (PQC) slabs made of dielectric cylinders arranged
according to a 12-fold-symmetric square-triangle aperiodic tiling. Our
full-wave numerical analysis confirms the results recently emerged in the
technical literature and, in particular, the possibility of achieving focusing
effects within several frequency regions. However, contrary to the original
interpretation, such focusing effects turn out to be critically associated to
local symmetry points in the PQC slab, and strongly dependent on its thickness
and termination. Nevertheless, our study reveals the presence of some peculiar
properties, like the ability to focus the light even for slabs with a reduced
lateral width, or beaming effects, which render PQC slabs potentially
interesting and worth of deeper investigation. Key words: Photonic
quasicrystals; negative refraction; superlensing.


  As artificial intelligence (AI) systems become increasingly integrated into
critical decision-making processes, the need for transparent and interpretable
models has become paramount. In this article we present a new ruleset creation
method based on surrogate decision trees (SRules), designed to improve the
interpretability of black-box machine learning models. SRules balances the
accuracy, coverage, and interpretability of machine learning models by
recursively creating surrogate interpretable decision tree models that
approximate the decision boundaries of a complex model. We propose a systematic
framework for generating concise and meaningful rules from these surrogate
models, allowing stakeholders to understand and trust the AI system's
decision-making process. Our approach not only provides interpretable rules,
but also quantifies the confidence and coverage of these rules. The proposed
model allows to adjust its parameters to counteract the lack of
interpretability by precision and coverage by allowing a near perfect fit and
high interpretability of some parts of the model . The results show that SRules
improves on other state-of-the-art techniques and introduces the possibility of
creating highly interpretable specific rules for specific sub-parts of the
model.


  We report mathematical results on the process by which quantum order by
disorder takes place for spin systems. The selection rules follow the influence
of several competing contributions. Moreover there is no link between quantum
selection and thermal selection. We present work in the general setting as well
as toy models and examples for which quantum selection has an interesting
behaviour.


  We present a general picture of the exciton properties of layered materials
in terms of the excitations of their single-layer building blocks. To this end,
we derive a model excitonic hamiltonian by drawing an analogy with molecular
crystals, which are other prototypical van der Waals materials. We employ this
simplified model to analyse in detail the excitation spectrum of hexagonal
boron nitride (hBN) that we have obtained from the {\it ab initio} solution of
the many-body Bethe-Salpeter equation as a function of momentum. In this way we
identify the character of the lowest-energy excitons in hBN, discuss the
effects of the interlayer hopping and the electron-hole exchange interaction on
the exciton dispersion, and illustrate the relation between exciton and plasmon
excitations in layered materials.


  Genuine multipartite entanglement (GME) is considered a powerful form of
entanglement since it corresponds to those states that are not biseparable,
i.e.\ a mixture of partially separable states across different bipartitions of
the parties. In this work we study this phenomenon in the multiple-copy regime,
where many perfect copies of a given state can be produced and controlled. In
this scenario the above definition leads to subtle intricacies as biseparable
states can be GME-activatable, i.e.\ several copies of a biseparable state can
display GME. We show that the set of GME-activatable states admits a simple
characterization: a state is GME-activatable if and only if it is not partially
separable across one bipartition of the parties. This leads to the second
question of whether there is a general upper bound in the number of copies that
needs to be considered in order to observe the activation of GME, which we
answer in the negative. In particular, by providing an explicit construction,
we prove that for any number of parties and any number $k\in\mathbb{N}$ there
exist GME-activatable multipartite states of fixed (i.e.\ independent of $k$)
local dimensions such that $k$ copies of them remain biseparable.


  Kagome metals with charge density wave (CDW) order exhibit a broad spectrum
of intriguing quantum phenomena. The recent discovery of the novel kagome CDW
compound ScV$_6$Sn$_6$ has spurred significant interest. However, understanding
the interplay between CDW and the bulk electronic structure has been obscured
by a profusion of surface states and terminations in this quantum material.
Here, we employ photoemission spectroscopy and potassium dosing to elucidate
the complete bulk band structure of ScV$_6$Sn$_6$, revealing multiple van Hove
singularities near the Fermi level. We surprisingly discover a robust
spin-polarized topological Dirac surface resonance state at the M point within
the two-fold van Hove singularities. Assisted by the first-principle
calculations, the temperature dependence of the $k_z$- resolved ARPES spectrum
provides unequivocal evidence for the proposed
$\sqrt{3}$$\times$$\sqrt{3}$$\times3$ charge order over other candidates. Our
work not only enhances the understanding of the CDW-dependent bulk and surface
states in ScV$_6$Sn$_6$ but also establishes an essential foundation for
potential manipulation of the CDW order in kagome materials.


  Intense field quantum field theory (IFQFT) is used to determine new
phenomenological predictions arising from Compton scattering and pair
production in a strong laser field. This theory utilizes exact solutions of
fermions embedded in external plane waves which carry over to a strong field
fermion propagator. When these strong field fermions also interact with probe
photons, the transition probability is enhanced in a series of resonances when
the kinematics allow the virtual fermion to go on-shell. An analysis of
parameters shows that contemporary experiments could already produce these
predicted resonances. With appropriate tuning, resonances can be made
arbitrarily sharp, leading to precision calculations of resonance locations and
widths, and the runing of coupling constants in strong background fields. New
tests of QED could be performed leading to ramifications for our understanding
of the quantum vacuum. Such tests extend to QFT in background potentials in
general, which may throw light on BSM theories such as QFT in curved
space-times.


  Classical designs and their (projective) q-analogs can both be viewed as
designs in matroids, using the matroid of all subsets of a set and the matroid
of linearly independent subsets of a vector space, respectively. Another
natural matroid is given by the point sets in general position of an affine
space, leading to the concept of an affine design. Accordingly, a t-(n, k,
$\lambda$) affine design of order q is a collection B of (k-1)-dimensional
spaces in the affine geometry A = AG(n-1, q) such that each (t-1)-dimensional
space in A is contained in exactly $\lambda$ spaces of B. In the case $\lambda$
= 1, as usual, one also refers to an affine Steiner system S(t, k, n).
  In this work we examine the relationship between the affine and the
projective q-analogs of designs. The existence of affine Steiner systems with
various parameters is shown, including the affine q-analog S(2, 3, 7) of the
Fano plane. Moreover, we consider various distances in matroids and geometries,
and we discuss the application of codes in affine geometry for error-control in
a random network coding scenario.


  This paper addresses analytical aspects of deterministic, continuous-time
dynamical systems defined on networks. The goal is to model and analyze certain
phenomena which must be framed beyond the context of networked dynamical
systems, understood as a set of interdependent dynamical systems defined on the
nodes of a (possibly evolving) graph. In order to advocate for a more flexible
approach to the study of network dynamics, we tackle some qualitative problems
which do not fall in this working scenario. First, we address a stability
problem on a network of heterogeneous agents, some of which are of dynamic
nature while others just impose restrictions on the system behavior. Our second
context assumes that the network is clustered, and we address a two-level
stability problem involving the dynamics of both individual agents and groups.
The aforementioned problems exhibit lines of non-isolated equilibria, and the
analysis implicitly assumes a positiveness condition on the edge weights; the
removal of this restriction complicates matters, and our third problem concerns
a graph-theoretic characterization of the equilibrium set in the dynamics of
certain networks with positive and negative weights, the results applying in
particular to signed graphs. Our approach combines graph theory and dynamical
systems theory, but also uses specific tools coming from linear algebra,
including e.g. Gersgorin discs or Maxwell-type determinantal expansions. The
results are of application in social, economic, and flow networks, among
others, and are also aimed at motivating further research.


  We study the problems of distributed online and bandit convex optimization
against an adaptive adversary. We aim to minimize the average regret on $M$
machines working in parallel over $T$ rounds with $R$ intermittent
communications. Assuming the underlying cost functions are convex and can be
generated adaptively, our results show that collaboration is not beneficial
when the machines have access to the first-order gradient information at the
queried points. This is in contrast to the case for stochastic functions, where
each machine samples the cost functions from a fixed distribution. Furthermore,
we delve into the more challenging setting of federated online optimization
with bandit (zeroth-order) feedback, where the machines can only access values
of the cost functions at the queried points. The key finding here is
identifying the high-dimensional regime where collaboration is beneficial and
may even lead to a linear speedup in the number of machines. We further
illustrate our findings through federated adversarial linear bandits by
developing novel distributed single and two-point feedback algorithms. Our work
is the first attempt towards a systematic understanding of federated online
optimization with limited feedback, and it attains tight regret bounds in the
intermittent communication setting for both first and zeroth-order feedback.
Our results thus bridge the gap between stochastic and adaptive settings in
federated online optimization.


  We discuss the BFKL approach to processes with large momentum transferred
through a rapidity gap. The Mueller and Tang scheme to the BFKL non-forward
parton-parton elastic scattering amplitude at large $t$, is extended to include
higher conformal spins. The new contributions are found to decrease with
increasing energy, as follows from the gluon reggeisation phenomenon, and to
vanish for asymptotically high energies. However, at moderate energies and high
$|t|$, the higher conformal spins dominate the amplitude. We illustrate the
effects by studying the production of two high $E_T$ jets separated by a
rapidity gap at HERA energies. In a simplified framework, we find excellent
agreement with the HERA photoproduction data once we incorporate the rapidity
gap survival probability against soft rescattering effects. We emphasize that
measurements of the analogous process in electroproduction may probe different
summations over conformal spins.


  We study the non-equilibrium dynamics of two coupled mechanical oscillators
with general linear couplings to two uncorrelated thermal baths at temperatures
$T_1$ and $T_2$, respectively. We obtain the complete solution of the
Heisenberg-Langevin equations, which reveal a coherent mixing among the normal
modes of the oscillators as a consequence of their off-diagonal couplings to
the baths. Unique renormalization aspects resulting from this mixing are
discussed. Diagonal and off-diagonal (coherence) correlation functions are
obtained analytically in the case of strictly Ohmic baths with different
couplings in the strong and weak coupling regimes. An asymptotic
non-equilibrium stationary state emerges for which we obtain the complete
expressions for the correlations and coherence. Remarkably the coherence
survives in the high temperature, classical limit for $T_1 \neq T_2$. In the
case of vanishing detuning between the oscillator normal modes both coupling to
one and the same bath the coherence retains memory of the initial conditions at
long time. A perturbative expansion of the early time evolution reveals that
the emergence of coherence is a consequence of the entanglement between the
normal modes of the oscillators \emph{mediated} by their couplings to the
baths. This \emph{suggests} the survival of entanglement in the high
temperature limit for different temperatures of the baths which is essentially
a consequence of the non-equilibrium nature of the asymptotic stationary state.
An out of equilibrium setup with small detuning and large $|T_1- T_2|$ produces
non-vanishing steady-state coherence and entanglement in the high temperature
limit of the baths.


  Plagiarism detection is one of the most researched areas among the Natural
Language Processing(NLP) community. A good plagiarism detection covers all the
NLP methods including semantics, named entities, paraphrases etc. and produces
detailed plagiarism reports. Detection of Cross Lingual Plagiarism requires
deep knowledge of various advanced methods and algorithms to perform effective
text similarity checking. Nowadays the plagiarists are also advancing
themselves from hiding the identity from being catch in such offense. The
plagiarists are bypassed from being detected with techniques like paraphrasing,
synonym replacement, mismatching citations, translating one language to
another. Image Content Plagiarism Detection (ICPD) has gained importance,
utilizing advanced image content processing to identify instances of plagiarism
to ensure the integrity of image content. The issue of plagiarism extends
beyond textual content, as images such as figures, graphs, and tables also have
the potential to be plagiarized. However, image content plagiarism detection
remains an unaddressed challenge. Therefore, there is a critical need to
develop methods and systems for detecting plagiarism in image content. In this
paper, the system has been implemented to detect plagiarism form contents of
Images such as Figures, Graphs, Tables etc. Along with statistical algorithms
such as Jaccard and Cosine, introducing semantic algorithms such as LSA, BERT,
WordNet outperformed in detecting efficient and accurate plagiarism.


  The Gamma Factory (GF) is an ambitious proposal, currently explored within
the CERN Physics Beyond Colliders program, for a source of photons with
energies up to $\approx 400\,$MeV and photon fluxes (up to $\approx 10^{17}$
photons per second) exceeding those of the currently available gamma sources by
orders of magnitude. The high-energy (secondary) photons are produced via
resonant scattering of the primary laser photons by highly relativistic
partially-stripped ions circulating in the accelerator. The secondary photons
are emitted in a narrow cone and the energy of the beam can be monochromatized,
eventually down to the $\approx1$ ppm level, via collimation, at the expense of
the photon flux. This paper surveys the new opportunities that may be afforded
by the GF in nuclear physics and related fields.


  Structural and superfluid properties of para-Hydrogen clusters of size up to
N=40 molecules, are studied at low temperature (0.5 K < T < 4 K) by Path
Integral Monte Carlo simulations. The superfluid fraction displays an
interesting, non-monotonic behavior for 22 < N < 30. We interpret this
dependence in terms of variations with N of the cluster structure.
Superfluidity is observed at low T in clusters of as many as 27 molecules; in
the temperature range considered here, quantum melting is observed in some
clusters, which freeze at high temperature.


  The growth of para-sexiphenyl (6P) thin films as a function of substrate
temperature on Ir{111} supported graphene flakes has been studied in real-time
with Low Energy Electron Microscopy (LEEM). Micro Low Energy Electron
Diffraction (\mu LEED) has been used to determine the structure of the
different 6P features formed on the surface. We observe the nucleation and
growth of a wetting layer consisting of lying molecules in the initial stages
of growth. Graphene defects -- wrinkles -- are found to be preferential sites
for the nucleation of the wetting layer and of the 6P needles that grow on top
of the wetting layer in the later stages of deposition. The molecular structure
of the wetting layer and needles is found to be similar. As a result, only a
limited number of growth directions are observed for the needles. In contrast,
on the bare Ir{111} surface 6P molecules assume an upright orientation. The
formation of ramified islands is observed on the bare Ir{111} surface at 320 K
and 352 K, whereas at 405 K the formation of a continuous layer of upright
standing molecules growing in a step flow like manner is observed.


  We employ singular value decomposition (SVD) to study the eigenvalue spectra
of random spin systems. By SVD, eigenvalue spectrum is decomposed into
orthonormal modes $W_k$ with weight $\lambda_k$. We show that the scree plot
($\lambda_k$ with respect to $k$) in the ergodic phase contains two branches
that both follow power-law $\lambda_k\sim k^{-\alpha}$ but with different
exponents $\alpha$. By evaluating $W_k$, it's verified the part of $\lambda_k $
with $k>k_{\text{Th}}$ is universal that follows random matrix theory, where
$k_{\text{Th}}$ is related to the Thouless energy. We further demonstrate that
$\alpha$ corresponds only to the exponential part of the level spacing
distribution while being insensitive to the level repulsion, or equivalently
the system's symmetry. Consequently, $\alpha$ gives an underestimation for the
many-body localization transition point, which suggests a non-ergodic behavior
that may be attributed to the Griffiths regime.


  Longitudinal control signals used to keep gravitational wave detectors at a
stable operating point are often affected by modulations from test mass
misalignments leading to an elevated noise floor ranging from 50 to 500 Hz.
Nonstationary noise of this kind results in modulation sidebands and increases
the number of glitches observed in the calibrated strain data. These artifacts
ultimately affect the data quality and decrease the efficiency of the data
analysis pipelines looking for astrophysical signals from continuous waves as
well as the transient events. In this work, we develop a scheme to subtract one
such bilinear noise from the gravitational wave strain data and demonstrate it
at the GEO 600 observatory. We estimate the coupling by making use of
narrow-band signal injections that are already in place for noise projection
purposes and construct a coherent bilinear signal by a two-stage system
identification process. We improve upon the existing filter design techniques
by employing a Bayesian adaptive directed search strategy that optimizes across
the several key parameters that affect the accuracy of the estimated model. The
scheme takes into account the possible nonstationarities in the coupling by
periodically updating the involved filter coefficients. The resulting
postoffline subtraction leads to a suppression of modulation sidebands around
the calibration lines along with a broadband reduction of the midfrequency
noise floor. The observed increase in the astrophysical range and a reduction
in the occurrence of nonastrophysical transients suggest that the above method
is a viable data cleaning technique for current and future generation
gravitational wave observatories.


  An omitted value of a transcendental meromorphic function $f$ is called a
Baker omitted value, in short \textit{bov} if there is a disk $D$ centered at
the bov such that each component of the boundary of $f^{-1}(D)$ is bounded.
Assuming that the bov is in the Fatou set of $f$, this article investigates the
dynamics of the function. Firstly, the connectivity of all the Fatou components
are determined. If $U$ is the Fatou component containing the bov then it is
proved that a Fatou component $U'$ is infinitely connected if and only if it
lands on $U$, i.e. $f^{k}(U') \subset U$ for some $k \geq 1$. Every other Fatou
component is either simply connected or lands on a Herman ring. Further,
assuming that the number of critical points in the Fatou set whose forward
orbits do not intersect $U$ is finite, we have shown that the connectivity of
each Fatou component belongs to a finite set. This set is independent of the
Fatou components. It is proved that the Fatou component containing the bov is
completely invariant whenever it is forward invariant. Further, if the
invariant Fatou component is an attracting domain and compactly contains all
the critical values of the function then the Julia set is totally disconnected.
Baker domains are shown to be non-existent whenever the bov is in the Fatou
set. It is also proved that, if there is a $2$-periodic Baker domain (these are
not ruled out when the bov is in the Julia set), or a $2$-periodic attracting
or parabolic domain containing the bov then the function has no Herman ring.
Some examples exhibiting different possibilities for the Fatou set are
discussed. This includes the first example of a meromorphic function with an
omitted value which has two infinitely connected Fatou components.


  We studied the marginal deformation of the $c=0$ topological conformal field
theories (TCFT). We showed that topological $SL(2)$ Wess-Zumino-Witten (WZW)
model, topological superconformal ghost system, TCFT constructed from the $N=2$
superconformal system and two dimensional topological gravity belong to the
same one parameter family (moduli space) of the $c=0$ TCFT's. We conjectured
that the $N=2$ TCFT constructed from the Wolf space realization of $N=4$
superconformal algebra belongs to another family.


  We exploit EAGLE, a cosmological hydrodynamical simulation, to reproduce the
selection of the observed sub-millimeter (submm) galaxy population by selecting
the model galaxies at $z \geq 1$ with mock submm fluxes $S_{850} \geq 1$ mJy.
There is a reasonable agreement between the galaxies within this sample and the
properties of the observed submm population, such as their star formation rates
(SFRs) at $z<3$, redshift distribution and many integrated galaxy properties.
We find that the bulk of the $S_{850} \geq 1$ mJy model population is at $z =
2.5$, and that they are massive galaxies ($M_* \sim 10^{11}$ Msol) with high
dust masses ($M_{\mathrm{dust}} \sim 10^{8}$ Msol), gas fractions
($f_{\mathrm{gas}} \approx 50$%) and SFRs ($\dot M_* \approx 100$ Msol/yr).
They have major and minor merger fractions similar to the general population,
suggesting that mergers are not the primary driver of the model submm galaxies.
Instead, the $S_{850} \geq 1$ mJy model galaxies yield high SFRs primarily
because they maintain a significant gas reservoir as a result of hosting an
undermassive black hole. In addition, we find that not all highly star-forming
EAGLE galaxies have submm fluxes $S_{850} > 1$ mJy. Thus, we investigate the
nature of $z \geq 1$ highly star-forming Submm-Faint galaxies (i.e., $\dot M_*
\geq 80$ Msol/yr but $S_{850}< 1$ mJy). We find they are similar to the model
submm galaxies; being gas rich and hosting undermassive black holes, however
they are typically lower mass ($M_* \sim 10^{10}$ Msol) and are at higher
redshifts ($z>4$). These typically higher-$z$ galaxies show stronger evidence
for having been triggered by major mergers, and critically, they are likely
missed by current submm surveys due to their higher dust temperatures. This
suggests a potentially even larger contribution to the SFR density at $z > 3$
from dust-obscured systems than implied by current observations.


  Distributed training of deep neural networks faces three critical challenges:
privacy preservation, communication efficiency, and robustness to fault and
adversarial behaviors. Although significant research efforts have been devoted
to addressing these challenges independently, their synthesis remains less
explored. In this paper, we propose TernaryVote, which combines a ternary
compressor and the majority vote mechanism to realize differential privacy,
gradient compression, and Byzantine resilience simultaneously. We theoretically
quantify the privacy guarantee through the lens of the emerging f-differential
privacy (DP) and the Byzantine resilience of the proposed algorithm.
Particularly, in terms of privacy guarantees, compared to the existing
sign-based approach StoSign, the proposed method improves the dimension
dependence on the gradient size and enjoys privacy amplification by mini-batch
sampling while ensuring a comparable convergence rate. We also prove that
TernaryVote is robust when less than 50% of workers are blind attackers, which
matches that of SIGNSGD with majority vote. Extensive experimental results
validate the effectiveness of the proposed algorithm.


  We present a systematic study of interaction induced dipole electric
properties of all molecular dimers in the S66 set, relying on
CCSD(T)-F12b/aug-cc-pVDZ-F12 as reference level of theory. For field strengths
up to $\approx$5 GV m$^{-1}$ the interaction induced electric response beyond
second order is found to be insignificant. Large interaction dipole moments
(i.e. dipole moment changes due to van der Waals binding) are observed in the
case of hydrogen bonding oriented along the intermolecular axis, and mostly
small interaction dipole moments are found in dimers bonded by $\pi$-stacking
or London dispersion. The interaction polarizabilities (i.e. polarizability
changes due to van der Waals binding) were generally found to be small but
always with a positive-valued principal component approximately aligned with
the intermolecular axis, and two other negative-valued components. Energy
decompositions according to symmetry adapted perturbation theory
(SAPT0/jun-cc-pVDZ) suggest that electrostatics dominates the interaction
dipole moment. First-order SAPT0 decompositions into monomer-resolved
contributions establish a quantitative link between electric properties of
monomers and dimers. Using the aug-cc-pVQZ basis and non-empirical PBE
semilocal exchange-correlation kernels, we also assess how density functional
approximations in the nonlocal exchange and correlation parts affect the
predictive accuracy: While dRPA@PBE0 based predictions are in excellent overall
agreement with coupled cluster results, the computationally more affordable
LC-$\omega$PBE0-D3 level of theory also yields reliable results with relative
errors below 5\%. PBE alone, even when dispersion corrected, produces larger
errors in interaction dipole moments and polarizabilities.


  Icosoku is a challenging and interesting puzzle that exhibits highly
symmetrical and combinatorial nature. In this paper, we pose the questions
derived from the puzzle, but with more difficulty and generality. In addition,
we also present a constraint programming model for the proposed questions,
which can provide the answers to our first two questions. The purpose of this
paper is to share our preliminary result and problems to encourage researchers
in both group theory and constraint communities to consider this topic further.


  BIP is a component framework for constructing systems by superposing three
layers of modeling: Behavior, Interaction, and Priority. Behavior is
represented by labeled transition systems communicating through ports.
Interactions are sets of ports. A synchronization between components is
possible through the interactions specified by a set of connectors. When
several interactions are possible, priorities allow to restrict the
non-determinism by choosing an interaction, which is maximal according to some
given strict partial order.
  The BIP component framework has been implemented in a language and a
tool-set. The execution of a BIP program is driven by a dedicated engine, which
has access to the set of connectors and priority model of the program. A key
performance issue is the computation of the set of possible interactions of the
BIP program from a given state.
  Currently, the choice of the interaction to be executed involves a costly
exploration of enumerative representations for connectors. This leads to a
considerable overhead in execution times. In this paper, we propose a symbolic
implementation of the execution model of BIP, which drastically reduces this
overhead. The symbolic implementation is based on computing boolean
representation for components, connectors, and priorities with an existing BDD
package.


  We consider a modification of the Brans-Dicke gravitational Action Integral
inspired by the existence of a minimum length uncertainty for the scalar field.
In particular, the kinetic part of the Brans-Dicke scalar field is modified
such that the equation of motion for the scalar field be modified according to
the quadratic Generalized Uncertainty Principle (GUP). For the background
geometry, we assume the homogeneous and isotropic
Friedmann--Lema\^{\i}tre--Robertson--Walker metric. We investigate the dynamics
and the cosmological evolution for the dynamical variables of the theory and we
compare the results with the unmodified Brans-Dicke theory. It follows that in
consideration because of the additional degrees of freedom in the
energy-momentum tensor the dynamical variables describe various aspects of the
cosmological history. This is one of the first studies on the effects of GUP in
a Machian gravitational theory.


  The energy of a simple graph $G$, denoted by $E(G)$, is defined as the sum of
the absolute values of all eigenvalues of its adjacency matrix. Let $C_n$
denote the cycle of order $n$ and $P^{6,6}_n$ the graph obtained from joining
two cycles $C_6$ by a path $P_{n-12}$ with its two leaves. Let $\mathscr{B}_n$
denote the class of all bipartite bicyclic graphs but not the graph $R_{a,b}$,
which is obtained from joining two cycles $C_a$ and $C_b$ ($a, b\geq 10$ and $a
\equiv b\equiv 2\, (\,\textmd{mod}\, 4)$) by an edge. In [I. Gutman, D.
Vidovi\'{c}, Quest for molecular graphs with maximal energy: a computer
experiment, {\it J. Chem. Inf. Sci.} {\bf41}(2001), 1002--1005], Gutman and
Vidovi\'{c} conjectured that the bicyclic graph with maximal energy is
$P^{6,6}_n$, for $n=14$ and $n\geq 16$. In [X. Li, J. Zhang, On bicyclic graphs
with maximal energy, {\it Linear Algebra Appl.} {\bf427}(2007), 87--98], Li and
Zhang showed that the conjecture is true for graphs in the class
$\mathscr{B}_n$. However, they could not determine which of the two graphs
$R_{a,b}$ and $P^{6,6}_n$ has the maximal value of energy. In [B. Furtula, S.
Radenkovi\'{c}, I. Gutman, Bicyclic molecular graphs with the greatest energy,
{\it J. Serb. Chem. Soc.} {\bf73(4)}(2008), 431--433], numerical computations
up to $a+b=50$ were reported, supporting the conjecture. So, it is still
necessary to have a mathematical proof to this conjecture. This paper is to
show that the energy of $P^{6,6}_n$ is larger than that of $R_{a,b}$, which
proves the conjecture for bipartite bicyclic graphs. For non-bipartite bicyclic
graphs, the conjecture is still open.


  In this paper, we incorporate the realistic scenario of key protection into
link privacy preserving and propose the target-link privacy preserving (TPP)
model: target links referred to as targets are the most important and sensitive
objectives that would be intentionally attacked by adversaries, in order that
need privacy protections, while other links of less privacy concerns are
properly released to maintain the graph utility. The goal of TPP is to limit
the target disclosure by deleting a budget limited set of alternative
non-target links referred to as protectors to defend the adversarial link
predictions for all targets. Traditional link privacy preserving treated all
links as targets and concentrated on structural level protections in which
serious link disclosure and high graph utility loss is still the bottleneck of
graph releasing today, while TPP focuses on the target level protections in
which key protection is implemented on a tiny fraction of critical targets to
achieve better privacy protection and lower graph utility loss. Currently there
is a lack of clear TPP problem definition, provable optimal or near optimal
protector selection algorithms and scalable implementations on large-scale
social graphs. Firstly, we introduce the TPP model and propose a dissimilarity
function used for measuring the defense ability against privacy analyzing for
the targets. We consider two different problems by budget assignment settings:
1) we protect all targets and to optimize the dissimilarity of all targets with
a single budget; 2) besides the protections of all targets, we also care about
the protection of each target by assigning a local budget to every target,
considering two local protector selections. We also implement scalable
implementations and experiments to demonstrate the effectiveness and efficiency
of the proposed algorithms.


  The piezoelectric optomechanical devices supply a promising experimental
platform to realize the coherent and effective control and measurement of
optical circuits working in Terahertz (THz) frequencies via superconducting
electron devices typically working in Radio (MHz) frequencies. However, quantum
fluctuations are unavoidable when the size of mechanical oscillators enters
into the nanoscale. The consequences of the noisy environment are still
challenging due to the lack of analytical tools. In this paper, a
semi-classical and full-quantum model of piezoelectric optomechanical systems
coupled to a noisy bosonic quantum environment are introduced and solved in
terms of quantum-state diffusion (QSD) trajectories in the non-Markovian
regime. We show that the noisy environment, particularly the central frequency
of the environment, can enhance the entanglement generation between optical
cavities and LC circuits in some parameter regimes. Moreover, we observe the
critical points in the coefficient functions, which can lead the different
behaviors in the system. Besides, we also witness the entanglement transfers
between macroscopic objects due to the memory effect of the environment. Our
work can be applied in the fields of electric/ optical switches, and
long-distance distribution in a large-scale quantum network.


  Recent Couette-cell shear experiments of carbopol gels have revealed the
formation of a transient shear band before reaching the steady state, which is
characterized by homogeneous flow. This shear band is observed in the small-gap
limit where the shear stress is spatially uniform. An effective-temperature
model of the transient shear banding and solid-fluid transition is developed
for the small-gap limit. The small-gap model demonstrates the ability of a
continuum-constitutive law that is based solely on microstructural
rearrangements of the gel to account for this transient behavior, and
identifies that it proceeds via two distinct processes. A shear band nucleates
and gradually broadens via disordering at the interface of the band.
Simultaneously, spatially homogeneous fluidization is induced outside of the
shear band where the disorder of the gel grows uniformly. Experimental data are
used to determine the physical parameters of the theory, and direct,
quantitative comparison is made to measurements of the structural evolution of
the gel, its fluidization time, and its mechanical response under plastic flow.


  To determine Euler numbers modulo powers of two seems to be a difficult task.
In this paper we achieve this and apply the explicit congruence to give a new
proof of a classical result due to M. A. Stern.


  A Peer-to-Peer (P2P) network can boost its performance if peers are provided
with underlying network-layer routing topology. The task of inferring the
network-layer routing topology and link performance from an end host to a set
of other hosts is termed as network tomography, and it normally requires host
computers to send probing messages. We design a passive network tomography
method that does not requires any probing messages and takes a free ride over
data flows in P2P networks. It infers routing topology based on end-to-end
delay correlation estimation (DCE) without requiring any synchronization or
cooperation from the intermediate routers. We implement and test our method in
the real world Internet environment and achieved the accuracy of 92% in
topology recovery. We also perform extensive simulation in OMNet++ to evaluate
its performance over large scale networks, showing that its topology recovery
accuracy is about 95% for large networks.


  Many unexpected charmonium-like states have recently been observed above the
$D\overline{D}$ threshold, which features can't be explained by the
conventional quark models. These states are known as XYZ mesons. The study of
the radiative transition among these states can provide the important features
of XYZ states. This study has recently been performed by the BESIII using the
large data samples collected at different center-of-mass energies above 3.8
GeV. This report summarizes the recent results of XYZ radiative transitions at
BESIII.


  In the two-dimensional isotropic parabolic potential barrier $V(x, y)=V_0
-m\gamma^2 (x^2+y^2)/2$, though it is a model of an unstable system in quantum
mechanics, we can obtain the stationary states corresponding to the real energy
eigenvalue $V_0$. Further, they are infinitely degenerate. For the first few
eigenstates, we will find the stationary flows round a right angle that are
expressed by the complex velocity potentials $W=\pm\gamma z^2/2$.


  We propose a method for measuring the magnetic dipole (M1) transition moment
of the $6S_{1/2} \big(\mathrm{m}=-1/2\big)\leftrightarrow
5D_{3/2}\big(\mathrm{m}=-1/2\big)$ transition in single trapped Ba$^{+}$ by
exploiting different symmetries in the electric quadrupole (E2) and M1
couplings between the states. The technique is adapted from a previously
proposed method for measuring atomic parity nonconservation in a single trapped
ion [Norval Fortson, Phys. Rev. Lett. \textbf{70}, 17 (1993)]. Knowledge of M1
is crucial for any parity nonconservation measurement in Ba$^{+}$, as laser
coupling through M1 can mimic the parity-violating signal. The magnetic moment
for the transition has been calculated by atomic theory and found to be
dominated by electron-electron correlation effects [B.K. Sahoo et. al., Phys.
Rev. A \textbf{74}, 6 (2006)]. To date the value has not been verified
experimentally. This proposed measurement is therefore an essential step toward
a parity nonconservation experiment in the ion that will also test current
many-body theory. The technique can be adapted for similar parity
nonconservation experiments using other atomic ions, where the magnetic dipole
moment could present similar complications.


  In this work, we explore a well motivated beyond the Standard Model scenario,
namely, R-parity violating Supersymmetry, in the context of light neutrino
masses and mixing. We assume that the R-parity is only broken by the lepton
number violating bilinear term. We try to fit two non-zero neutrino mass square
differences and three mixing angle values obtained from the global $\chi^2$
analysis of neutrino oscillation data. We have also taken into account the
updated data of the standard model (SM) Higgs mass and its coupling strengths
with other SM particles from LHC Run-II along with low energy flavor violating
constraints like rare b-hadron decays. We have used a Markov Chain Monte Carlo
(MCMC) analysis to constrain the new physics parameter space. While doing so,
we ensure that all the existing collider constraints are duly taken into
account. Through our analysis, we have derived the most stringent constraints
possible to date with existing data on the 9 bilinear R-parity violating
parameters along with $\mu$ and $\tan\beta$. We further explore the possibility
of explaining the anomalous muon~(g~-~2) measurement staying within the
parameter space allowed by neutrino, Higgs and flavor data while satisfying the
collider constraints as well. We find that there still remains a small sub-TeV
parameter space where the required excess can be obtained.


  The production of neutron-rich isotopes and the occurrence of neutron capture
cascades via laser-driven (pulsed) neutron sources are investigated
theoretically. The considered scenario involves the interaction of a
laser-driven neutron beam with a target made of a single type of seed nuclide.
We present a comprehensive study over $95$ seed nuclides in the range $3\le Z
\le 100$ from $^7_3$Li to $^{255}_{100}$Fm. For each element, the heaviest
sufficiently-long-lived (half life $> 1$ h) isotope whose data is available in
the recent ENDF-B-VIII.0 neutron sublibrary is considered. We identify
interesting seed nuclides with good performance in the production of
neutron-rich isotopes where neutron capture cascades may occur. The effects of
the neutron number per pulse, the neutron-target interaction size and the
number of neutron pulses are also analyzed. Our results show the possibility of
observing up to $4$ successive neutron capture events leading to neutron-rich
isotopes with $4$ more neutrons than the original seed nuclide. This hints at
new experimental possibilities to produce neutron-rich isotopes and simulate
neutron capture nucleosynthesis in the laboratory. With several selected
interesting seed nuclides in the region of the branching point of the
$s$-process ($^{126}_{51}$Sb, $^{176}_{71}$Lu and $^{187}_{75}$Re) or the
waiting point of the $r$-process (Lu, Re, Os, Tm, Ir and Au), we expect that
laser-driven experiments can shed light on our understanding of
nucleosynthesis.


  Asymptotic forms of the Hilbert-Scmidt and Hilbert norms of positive definite
Toeplitz matrices $Q_{N}=(b(j-k))_{j,k=0}^{N-1}$ as $N\to \infty $ are
determined. Here $b(j)$ are consequent trigonometric moments of a generating
non-negative mesure $d\sigma (\theta)$ on $[ -\pi ,\pi ] $. It is proven that
$\sigma (\theta)$ is continuous if and only if any of those contributions is
$o(N)$. Analogous criteria are given for positive integral operators with
difference kernels.
  Obtained results are applied to processing of stationary random signals, in
particular, neutron signals emitted by boiling water nuclear reactors.


  Experimental refinements and technical innovations in the field of extensive
air shower telescopes have enabled measurements of Galactic cosmic-ray
interactions in the sub-PeV range, providing new avenues for the search for new
physics and dark matter. For the first time, we exploit sub-PeV (1 TeV -- 1
PeV) observations of Galactic diffuse gamma rays by HAWC and Tibet AS$\gamma$
to search for an axion-like-particle (ALP) induced gamma-ray signal directly
linked to the origin of the IceCube extragalactic high-energy neutrino flux.
Indeed, the production of high-energy neutrinos in extragalactic sources
implies the concomitant production of gamma rays at comparable energies. Within
the magnetic field of the neutrino emitting sources, gamma rays may efficiently
convert into ALPs, escape their host galaxy un-attenuated, propagate through
intergalactic space, and reconvert into gamma rays in the magnetic field of the
Milky Way. Such a scenario creates an all-sky diffuse high-energy gamma-ray
signal in the sub-PeV range. Accounting for the guaranteed Galactic
astrophysical gamma-ray contributions from cosmic-ray interactions with gas and
radiation and from sub-threshold sources, we set competitive upper limits on
the photon-ALP coupling constant $g_{a\gamma\gamma}$. We find
$g_{a\gamma\gamma} < 2.1\times10^{-11}$ GeV$^{-1}$ for ALP masses $m_a \leq
2\times10^{-7}$ eV at a 95\% confidence level. Our results are comparable to
previous limits on ALPs derived from the TeV gamma-ray domain and progressively
close the mass gap towards ADMX limits. The code and data to reproduce the
results of this study are available on GitHub
\url{https://github.com/ceckner/subPeVALPs}.


  Derived from the concentration-compactness principle, the concept of
generalized minimizer can be used to define generalized solutions of
variational problems which may have components ``infinitely'' distant from each
other. In this article and under mild assumptions we establish existence and
density estimates of generalized minimizers of perturbed isoperimetric
problems. Our hypotheses encapsulate a wide class of functionals including the
classical, anisotropic and fractional perimeter. The perturbation term may for
instance take the form of a potential, a translation invariant kernel or a
nonlocal term involving the Wasserstein distance.


  Abstract This short paper investigates the harmonic behavior of a
general-relativistic thin-shell wormhole supported by a particular type of
exotic fluid. The exotic fluid obeys a never-studied-before metric-dependent
equation of state. This equation of state is tailored such that the wormhole's
throat undergoes a harmonic-like behavior before damping to an equilibrium
radius. Eventually, the mirror-symmetric Schwarzschild thin-shell wormhole is
studied in this framework as an example.


  We describe a scanning device where a single spin is used as an
ultrasensitive, nanoscale magnetic field sensor. As this "probe spin" we
consider a single nitrogen-vacancy defect center in a diamond nanocrystal,
attached to the tip of the scanning device. Changes in the local field seen by
the probe spin are detected by optically monitoring its electron paramagnetic
resonance transition. The room-temperature scanning device may be useful for
performing nanoscale magnetic resonance imaging and spectroscopy, and for the
characterization of magnetic nanostructures down to the single atom level.


  We present a general criterion for the existence of open book structures
defined by real map germs $(\bR^m, 0) \to (\bR^p, 0)$, where $m> p \ge 2$, with
isolated critical point. We show that this is satisfied by weighted-homogeneous
maps. We also derive sufficient conditions in case of map germs with isolated
critical value.


  In this research, we introduce RefineNet, a novel architecture designed to
address resolution limitations in text-to-image conversion systems. We explore
the challenges of generating high-resolution images from textual descriptions,
focusing on the trade-offs between detail accuracy and computational
efficiency. RefineNet leverages a hierarchical Transformer combined with
progressive and conditional refinement techniques, outperforming existing
models in producing detailed and high-quality images. Through extensive
experiments on diverse datasets, we demonstrate RefineNet's superiority in
clarity and resolution, particularly in complex image categories like animals,
plants, and human faces. Our work not only advances the field of image-to-text
conversion but also opens new avenues for high-fidelity image generation in
various applications.


  We show that a combined analysis of $B\to K\nu\bar\nu$ and $B\to Kl^+l^-$
allows for new physics tests practically free of form factor uncertainties.
Residual theory errors are at the level of several percent. Our study
underlines the excellent motivation for measuring these modes at a Super
Flavour Factory.


  The sliced Wasserstein barycenter (SWB) is a widely acknowledged method for
efficiently generalizing the averaging operation within probability measure
spaces. However, achieving marginal fairness SWB, ensuring approximately equal
distances from the barycenter to marginals, remains unexplored. The uniform
weighted SWB is not necessarily the optimal choice to obtain the desired
marginal fairness barycenter due to the heterogeneous structure of marginals
and the non-optimality of the optimization. As the first attempt to tackle the
problem, we define the marginal fairness sliced Wasserstein barycenter (MFSWB)
as a constrained SWB problem. Due to the computational disadvantages of the
formal definition, we propose two hyperparameter-free and computationally
tractable surrogate MFSWB problems that implicitly minimize the distances to
marginals and encourage marginal fairness at the same time. To further improve
the efficiency, we perform slicing distribution selection and obtain the third
surrogate definition by introducing a new slicing distribution that focuses
more on marginally unfair projecting directions. We discuss the relationship of
the three proposed problems and their relationship to sliced multi-marginal
Wasserstein distance. Finally, we conduct experiments on finding 3D
point-clouds averaging, color harmonization, and training of sliced Wasserstein
autoencoder with class-fairness representation to show the favorable
performance of the proposed surrogate MFSWB problems.


  Braid Floer homology is an invariant of proper relative braid classes. Closed
integral curves of 1-periodic Hamiltonian vector fields on the 2-disc may be
regarded as braids. If the Braid Floer homology of associated proper relative
braid classes is non-trivial, then additional closed integral curves of the
Hamiltonian equations are forced via a Morse type theory. In this article we
show that certain information contained in the braid Floer homology - the
Euler-Floer characteristic - also forces closed integral curves and periodic
points of arbitrary vector fields and diffeomorphisms and leads to a
Poincar\'e-Hopf type Theorem. The Euler-Floer characteristic for any proper
relative braid class can be computed via a finite cube complex that serves as a
model for the given braid class. The results in this paper are restricted to
the 2-disc, but can be extend to two-dimensional surfaces (with or without
boundary).


  Paleo-Sciences including palaeoclimatology and palaeoecology have accumulated
numerous records related to climatic changes. The researchers have usually
tried to identify periodic and quasi-periodic processes in these
paleoscientific records. In this paper, we show that this analysis is
incomplete. As follows from our results, random processes, namely processes
with a single-time-constant (noise with a Lorentzian noise spectrum), play a
very important and, perhaps, a decisive role in numerous natural phenomena. For
several of very important natural phenomena the characteristic time constants
are very similar and equal to (5-8)x10^3 years. However, this value is not
universal. For example, the spectral density fluctuations of the atmospheric
radiocarbon 14C are characterized by a Lorentzian with time constant 300 years.
The frequency dependence of spectral density fluctuations for benthic 18O
records contains two Lorentzians with time constans 8000 years and > 105 years.


  The Teichmueller polynomial of a fibered 3-manifold plays a useful role in
the construction of mapping class having small stretch factor. We provide an
algorithm that computes this polynomial of the fibered face associated to a
pseudo-Anosov mapping class of a disc homeomorphism. As a byproduct, our
algorithm allows us to derive all the relevant informations on the topology of
the different fibers that belong to the fibered face.


  We define, for any group $G$, finite approximations ; with this tool, we give
a new presentation of the profinite completion $\hat{\pi} : G \to \hat{G}$ of
an abtract group $G$. We then prove the following theorem : if $k$ is a finite
prime field and if $V$ is a $k$-vector space, then, there is a natural
isomorphism between $\hat{V}$ (for the underlying additive group structure) and
the additive group of the double-dual $V^{**}$. This theorem gives
counter-examples concerning the iterated profinite completions of a group.
These phenomena don't occur in the topological case.


  We present a report of the MEG II experiment, the upgrade of MEG, whose goal
is to search for the forbidden decay \megc\ with increased precision. After
having briefly reviewed the motivation for such a search and the current limit
due to MEG, we present the conceptual design of the detector detailing for each
subdetector the motivations and the extent of the upgrade and the expected
resolution improvements. Novel subdetectors and calibration hardware are
introduced. We conclude with the expected sensitivity of the MEGII experiment.


  An iterative construction of higher order Einstein tensors for a maximally
Gauss-Bonnet extended gravitational Lagrangian was introduced in a previous
paper. Here the formalism is extended to non-factorisable metrics in arbitrary
($d+1$) dimensions in the presence of superposed Gauss-Bonnet terms. Such a
generalisation turns out to be remarkably convenient and elegant. Having thus
obtained the variational equations we first construct bulk solutions, with
nonzero and zero cosmological constant. It is also pointed out that in the
absence of Gauss-Bonnet terms a Schwarzschild type solution can be obtained in
the non-factorisable case. Two positive tension branes are then inserted and
their tensions are obtained in terms of parameters in the warp factor.
Relations to recent studies of several authors are pointed out.


  The well-known theorem of Ax and Katz gives a p-divisibility bound for the
number of rational points on an algebraic variety V over a finite field of
characteristic p in terms of the degree and number of variables of defining
polynomials of V. It was strengthened by Adolphson-Sperber in terms of Newton
polytope of the support set G of V. In this paper we prove that for every
generic algebraic variety over a number field supported on G the
Adolphson-Sperber bound can be achieved on special fibre at p for a set of
prime p of positive density in SpecZ. Moreover we show that if G has certain
combinatorial conditional number nonzero then the above bound is achieved at
special fiber at p for all but finitely many primes p.


  Establishing the origin of the short-lived radionuclide (SLR) 26-Al, which
was present in refractory inclusions in primitive meteorites, has profound
implications for the astrophysical context of solar system formation. Recent
observations that 26-Al was homogeneously distributed in the inner solar system
prove that this SLR has a stellar origin. In this Letter, we address the issue
of the incorporation of hot 26-Al-rich stellar ejecta into the cold protosolar
nebula. We first show that the 26-Al atoms produced by a population of massive
stars in an OB association cannot be injected into protostellar cores with
enough efficiency. We then show that this SLR likely originated in a Wolf-Rayet
star that escaped from its parent cluster and interacted with a neighboring
molecular cloud. The explosion of this runaway star as a supernova probably
triggered the formation of the solar system. This scenario also accounts for
the meteoritic abundance of 41-Ca.


  We study the Boltzmann equation with external forces, not necessarily
deriving from a potential, in the incompressible Navier-Stokes perturbative
regime. On the torus, we establish local-in-time, for any time, Cauchy theories
that are independent of the Knudsen number in Sobolev spaces. The existence is
proved around a time-dependent Maxwellian that behaves like the global
equilibrium both as time grows and as the Knudsen number decreases. We combine
hypocoercive properties of linearized Boltzmann operators with linearization
around a time-dependent Maxwellian that catches the fluctuations of the
characteristics trajectories due to the presence of the force. This uniform
theory is sufficiently robust to derive the incompressible
Navier-Stokes-Fourier system with an external force from the Boltzmann
equation. Neither smallness, nor time-decaying assumption is required for the
external force, nor a gradient form, and we deal with general hard potential
and cut-off Boltzmann kernels. As a by-product the latest general theories for
unit Knudsen number when the force is sufficiently small and decays in time are
recovered.


  Looking for sparsity is nowadays crucial to speed up the training of
large-scale neural networks. Projections onto the $\ell_{1,2}$ and
$\ell_{1,\infty}$ are among the most efficient techniques to sparsify and
reduce the overall cost of neural networks. In this paper, we introduce a new
projection algorithm for the $\ell_{1,\infty}$ norm ball. The worst-case time
complexity of this algorithm is $\mathcal{O}\big(nm+J\log(nm)\big)$ for a
matrix in $\mathbb{R}^{n\times m}$. $J$ is a term that tends to 0 when the
sparsity is high, and to $nm$ when the sparsity is low. Its implementation is
easy and it is guaranteed to converge to the exact solution in a finite time.
Moreover, we propose to incorporate the $\ell_{1,\infty}$ ball projection while
training an autoencoder to enforce feature selection and sparsity of the
weights. Sparsification appears in the encoder to primarily do feature
selection due to our application in biology, where only a very small part
($<2\%$) of the data is relevant. We show that both in the biological case and
in the general case of sparsity that our method is the fastest.


  Story Ending Prediction is a task that needs to select an appropriate ending
for the given story, which requires the machine to understand the story and
sometimes needs commonsense knowledge. To tackle this task, we propose a new
neural network called Diff-Net for better modeling the differences of each
ending in this task. The proposed model could discriminate two endings in three
semantic levels: contextual representation, story-aware representation, and
discriminative representation. Experimental results on the Story Cloze Test
dataset show that the proposed model siginificantly outperforms various systems
by a large margin, and detailed ablation studies are given for better
understanding our model. We also carefully examine the traditional and
BERT-based models on both SCT v1.0 and v1.5 with interesting findings that may
potentially help future studies.


  We report results of our precise reduction of the high signal-to-noise VRI
observations of the optical afterglow of the gamma-ray burst GRB 020813
obtained by Gladders & Hall with the Magellan 6.5-m telescope 3.9-4.9 hours
after the burst. These observations are very well fitted locally by a power-law
curve, providing the tightest constraints yet on how smooth the afterglows can
be in some cases: the rms deviations range from 0.005 mag (0.5%) for the R-band
to 0.007 mag for the I-band, only marginally larger than the rms scatter for
nearby non-variable stars. This scatter is a factor of several smaller then the
smallest reported rms of 0.02 mag for GRB 990510 (Stanek et al). These
observations are in strong contrast to those of afterglows of GRB 011211 and
GRB 021004, for which large > 10% variability has been observed on timescales
from ~20 minutes to several hours. If interstellar medium (ISM) density
fluctuations near the GRB are indeed causing the bumps and wiggles observed in
some bursts, very uniform regions of ISM near some bursts must be present as
well. This result also constrains the intrinsic smoothness of the afterglow
itself.