  Monolayers of ReS2 were grown by a chemical vapor deposition technique on
SiO2/Si substrates and investigated at room temperature by using micro-Raman,
micro-photoluminescence (PL) and absorbance spectroscopies. The Raman
scattering spectrum exhibits several phonon modes that were confirmed by the
computation analysis based on the density functional theory. The ReS2
structural integrity was confirmed by using the XRD and the energy dispersion
spectroscopy that was obtained by the scanning electron microscopy.
Photoluminescence spectra show excitons related to interband transition in thin
monolayer flakes and bulk-like structures. Additionally, a sharp PL line
located at 1.2620 eV with a second harmonic peak at 2.5420 eV were observed and
explained in terms of interband excitonic transitions originated within the
rhenium 5d orbit. An optical absorbance spectrum with an exciton peak around
1.4660 eV was obtained for an assembly of ReS2 flakes grown on silica
substrate.


  This paper presents a method to interpolate a periodic band-limited signal
from its samples lying at nonuniform positions in a regular grid, which is
based on the FFT and has the same complexity order as this last algorithm. This
kind of interpolation is usually termed "the missing samples problem" in the
literature, and there exists a wide variety of iterative and direct methods for
its solution. The one presented in this paper is a direct method that exploits
the properties of the so-called erasure polynomial, and it provides a
significant improvement on the most efficient method in the literature, which
seems to be the burst error recovery (BER) technique of Marvasti's et al. The
numerical stability and complexity of the method are evaluated numerically and
compared with the pseudo-inverse and BER solutions.


  Various performance characteristics of distributed file systems have been
well studied. However, the performance efficiency of distributed file systems
on small-file problems with complex machine learning algorithms scenarios is
not well addressed. In addition, demands for unified storage of big data
processing and high-performance computing have been crucial. Hence, developing
a solution combining high-performance computing and big data with shared
storage is very important. This paper focuses on the performance efficiency of
distributed file systems with small-file datasets. We propose an architecture
combining both high-performance computing and big data with shared storage and
perform a series of experiments to investigate the performance of these
distributed file systems. The result of the experiments confirms the
applicability of the proposed architecture in terms of complex machine learning
algorithms.


  We generalize Zwanziger's pairwise little group to include a boost subgroup.
We do so by working in the celestial sphere representation of scattering
amplitudes. We propose that due to late time soft photon and graviton
exchanges, matter particles in the asymptotic states in massless QED and
gravity transform under the Poincare group with an additional pair of pairwise
celestial representations for each pair of matter particles. We demonstrate
that the massless abelian and gravitational exponentiation theorems are
consistent with the proposed pairwise Poincare transformation properties. For
massless QED we demonstrate that our results are consistent with the effects of
the Faddeev-Kulish dressing and the abelian exponentiation theorem for
celestial amplitudes found in [2012.04208]. We discuss electric and magnetic
charges simultaneously as it is especially natural to do so in this formalism.


  Virtual machines have been widely adapted for high-level programming language
implementations and for providing a degree of platform neutrality. As the
overall use and adaptation of virtual machines grow, the overall performance of
virtual machines has become a widely-discussed topic. In this paper, we present
a survey on the performance differences of the two most widely adapted types of
virtual machines - the stack-based virtual machine and the register-based
virtual machine - using various benchmark programs. Additionally, we adopted a
new approach of measuring performance by measuring the overall dispatch time,
amount of dispatches, fetch time, and execution time while running benchmarks
on custom-implemented, lightweight virtual machines. Finally, we present two
lightweight, custom-designed, Turing-equivalent virtual machines that are
specifically designed in benchmarking virtual machine performance - the
"Conceptum" stack-based virtual machine, and the "Inertia" register-based
virtual machine. Our result showed that while on average the register machine
spends 20.39% less time in executing benchmarks than the stack machine, the
stack-based virtual machine is still faster than the virtual machine regarding
the instruction fetch time.


  We report on measurements of interstellar O VI, H2, P II, Si II, Ar I, and Fe
II absorption along the line of sight to Sk -67 05, a B0 Ia star in a diffuse H
II region in the western edge of the Large Magellanic Cloud (LMC). We find log
N(O VI) = 14.40 +/- 0.04 in the Milky Way (MW) component and, using the C IV
column density from previous IUE observations, N(C IV) / N(O VI) = 1.00 +/-
0.16, a value similar to other halo measurements made with FUSE. In the LMC
component, log N(O VI) = 13.89 +/- 0.05, and N(C IV) / N(O VI) < 0.4 (3 sigma),
since only an upper limit on N(C IV) is available. Along this sightline the LMC
is rich in molecular hydrogen, log N(H2) = 19.50 +/- 0.08; in the MW log N(H2)
= 14.95 +/- 0.08. A two-component fit for the excitation temperature of the
molecular gas in the LMC gives T_01 = 59 +/- 5 K for J=0,1 and T_ex = 800 +/-
330 K for J=3,4,5. For the MW, T_01 = 99 (+30/-20) K; no excitation temperature
could be determined for the higher rotational states. The MW and LMC gas-phase
[Fe/P] abundances are ~0.6 and ~0.7 dex lower, respectively, than solar system
abundances. These values are similar to [Fe/Zn] measurements for the MW and LMC
towards SN 1987A.


  Observations suggest that twisted magnetic flux tubes are ubiquitous in the
Sun's atmosphere. The main aim of this work is to advance the study of
axisymmetric modes of magnetic flux tubes by modeling both twisted internal and
external magnetic field, when the magnetic twist is weak. In this work, we
solve the derived wave equations numerically assuming twist outside the tube is
inversely proportional to the distance from its boundary. We also study the
case of constant magnetic twist outside the tube and solve these equations
analytically. We show that the solution for a constant twist outside the tube
is a good approximation to the case where the magnetic twist is proportional to
$1/r$, namely the error is in all cases less than $5.4\%$.The solution is in
excellent agreement with solutions to simpler models of twisted magnetic flux
tubes, i.e. without external magnetic twist. It is shown that axisymmetric
Alfv\'{e}n waves are naturally coupled with magnetic twist as the azimuthal
component of the velocity perturbation is nonzero. We compared our theoretical
results with observations and comment on what the Doppler signature of these
modes is expected to be. Lastly, we argue that the character of axisymmetric
waves in twisted magnetic flux tubes can lead to false positives in identifying
observations with axisymmetric Alfv\'{e}n waves.


  This paper gives a survey of a diagrammatic approach for fermionic pairing
fluctuations, which are relevant to the BCS-BEC crossover realized with
ultracold Fermi gases. Emphasis will be given to the physical intuition about
the relevant physical processes that can be associated with this approach.
Specific results will be presented for thermodynamic and dynamical quantities,
where a critical comparison with alternative diagrammatic approaches will also
be attempted.


  We briefly indicate some implications of [1] for the second Lie algebra
cohomology of equivariant map algebras and (twisted multi) loop algebras.


  We report a novel mechanism for the formation of chimera states, a peculiar
spatiotemporal pattern with coexisting synchronized and incoherent domains
found in ensembles of identical oscillators. Considering Stuart-Landau
oscillators we demonstrate that a nonlinear global coupling can induce this
symmetry breaking. We find chimera states also in a spatially extended system,
a modified complex Ginzburg-Landau equation. This theoretical prediction is
validated with an oscillatory electrochemical system, the electrooxidation of
silicon, where the spontaneous formation of chimeras is observed without any
external feedback control.


  The main goal of this work is to answer a question of P. D`ebes and D. Haran
by relaxing the condition for Hilbertianity. Namely we prove that for a field K
to be Hilbertian it suffices that K has the irreducible specialization property
merely for absolutely irreducible polynomials.


  Machine translation (MT) systems are now able to provide very accurate
results for high resource language pairs. However, for many low resource
languages, MT is still under active research. In this paper, we develop and
share a dataset to automatically evaluate the quality of MT systems for
Amharic. We compare two commercially available MT systems that support
translation of Amharic to and from English to assess the current state of MT
for Amharic. The BLEU score results show that the results for Amharic
translation are promising but still low. We hope that this dataset will be
useful to the research community both in academia and industry as a benchmark
to evaluate Amharic MT systems.


  Previous work has given proof and evidence that BPS states in local
Calabi-Yau 3-folds can be described and counted by exponential networks on the
punctured plane, with the help of a suitable non-abelianization map to the
mirror curve. This provides an appealing elementary depiction of moduli of
special Lagrangian submanifolds, but so far only a handful of examples have
been successfully worked out in detail. In this note, we exhibit an explicit
correspondence between torus fixed points of the Hilbert scheme of points on
$\mathbb C^2\subset\mathbb C^3$ and anomaly free exponential networks attached
to the quadratically framed pair of pants. This description realizes an
interesting, and seemingly novel, "age decomposition" of linear partitions. We
also provide further details about the networks' perspective on the full
D-brane moduli space.


  We consider finite-dimensional real vector spaces $X$ ordered by a closed
cone $X_+$ with non-empty interior and study eventual nonnegativity of matrix
semigroups $(e^{tA})_{t \ge 0}$ with respect to this cone.
  Our first contribution is the observation that, for general cones, one needs
to distinguish between different notions of eventual nonnegativity: (i) uniform
eventual nonnegativity means that $e^{tA}$ maps $X_+$ into $X_+$ for all
sufficiently large times $t$; (ii) individual eventual nonnegativity means that
for each $x \in X_+$ the vector $e^{tA}x$ is in $X_+$ for all $t$ larger than
an $x$-dependent time $t_0$; and (iii) weak eventual nonnegativity means that
for each $x \in X_+$ and each functional $x'$ in the dual cone $X'_+$ the value
$\langle x', e^{tA} x \rangle$ is in $[0,\infty)$ for all $t$ larger than an
$x$- and $x'$-dependent time $t_0$. Until now, only the first of these notions
has been studied in the literature. We demonstrate by examples that, somewhat
surprisingly for finite-dimensional spaces, all three notions are different.
  Our second contribution is to show that typical Perron-Frobenius like
properties remain valid under the weakest of the above notions.
  Third, we study a strengthened form of the above mentioned concepts, namely
eventual positivity. We prove that uniform, individual and weak versions of
this property are - in contrast to the nonnegative case - equivalent, and that
they can be characterized by spectral properties.


  Although repulsive effects have been predicted for quantum vacuum forces
between bodies with nontrivial electromagnetic properties, such as between a
perfect electric conductor and a perfect magnetic conductor, realistic
repulsion seems difficult to achieve. Repulsion is possible if the medium
between the bodies has a permittivity in value intermediate to those of the two
bodies, but this may not be a useful configuration. Here, inspired by recent
numerical work, we initiate analytic calculations of the Casimir-Polder
interaction between an atom with anisotropic polarizability and a plate with an
aperture. In particular, for a semi-infinite plate, and, more generally, for a
wedge, the problem is exactly solvable, and for sufficiently large anisotropy,
Casimir-Polder repulsion is indeed possible, in agreement with the previous
numerical studies. In order to achieve repulsion, what is needed is a
sufficiently sharp edge (not so very sharp, in fact) so that the directions of
polarizability of the conductor and the atom are roughly normal to each other.
The machinery for carrying out the calculation with a finite aperture is
presented. As a motivation for the quantum calculation, we carry out the
corresponding classical analysis for the force between a dipole and a metallic
sheet with a circular aperture, when the dipole is on the symmetry axis and
oriented in the same direction.


  We analyze a hybrid method that enriches coarse grid finite element solutions
with fine scale fluctuations obtained from a neural network. The idea stems
from the Deep Neural Network Multigrid Solver (DNN-MG), (Margenberg et al., J
Comput Phys 460:110983, 2022; A neural network multigrid solver for the
Navier-Stokes equations) which embeds a neural network into a multigrid
hierarchy by solving coarse grid levels directly and predicting the corrections
on fine grid levels locally (e.g. on small patches that consist of several
cells) by a neural network. Such local designs are quite appealing, as they
allow a very good generalizability. In this work, we formalize the method and
describe main components of the a-priori error analysis. Moreover, we
numerically investigate how the size of training set affects the solution
quality.


  This study presents a deep learning based methodology for both remote sensing
and design of acoustic scatterers. The ability to determine the shape of a
scatterer, either in the context of material design or sensing, plays a
critical role in many practical engineering problems. This class of inverse
problems is extremely challenging due to their high-dimensional, nonlinear, and
ill-posed nature. To overcome these technical hurdles, we introduce a geometric
regularization approach for deep neural networks (DNN) based on non-uniform
rational B-splines (NURBS) and capable of predicting complex 2D scatterer
geometries in a parsimonious dimensional representation. Then, this geometric
regularization is combined with physics-embedded learning and integrated within
a robust convolutional autoencoder (CAE) architecture to accurately predict the
shape of 2D scatterers in the context of identification and inverse design
problems. An extensive numerical study is presented in order to showcase the
remarkable ability of this approach to handle complex scatterer geometries
while generating physically-consistent acoustic fields. The study also assesses
and contrasts the role played by the (weakly) embedded physics in the
convergence of the DNN predictions to a physically consistent inverse design.


  New exact asymptotically flat solutions of five-dimensional Einstein
equations with horizon are found to describe multidimensional black stars
generated by matter on the brane, conceivably on high energy colliders. The
five-dimensional space-time is realized as an orbifold against reflection of a
special extra-space coordinate and matter on the brane is induced by tailoring
of the five-dimensional Schwarzschild-Tangherlini black hole metric.


  Distributed optimization has been widely used as one of the most efficient
approaches for model training with massive samples. However, large-scale
learning problems with both massive samples and high-dimensional features
widely exist in the era of big data. Safe screening is a popular technique to
speed up high-dimensional models by discarding the inactive features with zero
coefficients. Nevertheless, existing safe screening methods are limited to the
sequential setting. In this paper, we propose a new distributed dynamic safe
screening (DDSS) method for sparsity regularized models and apply it on
shared-memory and distributed-memory architecture respectively, which can
achieve significant speedup without any loss of accuracy by simultaneously
enjoying the sparsity of the model and dataset. To the best of our knowledge,
this is the first work of distributed safe dynamic screening method.
Theoretically, we prove that the proposed method achieves the linear
convergence rate with lower overall complexity and can eliminate almost all the
inactive features in a finite number of iterations almost surely. Finally,
extensive experimental results on benchmark datasets confirm the superiority of
our proposed method.


  A vortex molecule is predicted in rotating two-component Bose-Einstein
condensates whose internal hyperfine states are coupled coherently by an
external field. A vortex in one component and that in the other are connected
by a domain wall of the relative phase, constituting a "vortex molecule", which
features a nonaxisymmetric (pseudo)spin texture with a pair of merons. The
binding mechanism of the vortex molecule is discussed based on a generalized
nonlinear sigma model and a variational ansatz. The anisotropy of vortex
molecules is caused by the difference in the scattering lengths, yielding a
distorted vortex-molecule lattice in fast rotating condensates.


  It is proved that, according to Classical Mechanics and Electrodynamics, the
trajectory of the center of mass of a neutral system of electrical charges can
be deflected by an inhomogeneous magnetic field, even if its internal angular
momentum is zero. This challenges the common view about the function of the
Stern-Gerlach apparatus, as resolving the eigen-states of an intrinsic angular
momentum. Doubts are cast also on the supposed failure of Schrodinger's theory
to explain the properties of atoms in presence of magnetic fields without
introducing spin variables.


  The differential cross section for the process p(e,e'p)eta has been measured
at Q^2 = 2.4 and 3.6 (GeV/c)^2 at center-of-mass energies encompassing the
S11(1535) resonance. The latter point is the highest-Q^2 exclusive measurement
of this process to date. The resonance width and the helicity-1/2 transition
amplitude are extracted from the data, and evidence for the possible onset of
scaling in this reaction is shown. A lower bound of approximately 0.45 is
placed on the S11(1535) to eta branching fraction.


  We investigate selective patterning of ultra-thin 20 nm Indium Tin Oxide
(ITO) thin films on glass substrates, using 343, 515, and 1030 nm femtosecond
(fs), and 1030 nm picoseconds (ps) laser pulses. An ablative removal mechanism
is observed for all wavelengths at both femtosecond and picoseconds
time-scales. The absorbed threshold fluence values were determined to be 12.5
mJ/cm2 at 343 nm, 9.68 mJ/cm2 at 515 nm, and 7.50 mJ/cm2 at 1030 nm for
femtosecond and 9.14 mJ/cm2 at 1030 nm for picosecond laser exposure. Surface
analysis of ablated craters using atomic force microscopy confirms that the
selective removal of the film from the glass substrate is dependent on the
applied fluence. Film removal is shown to be primarily through ultrafast
lattice deformation generated by an electron blast force. The laser absorption
and heating process was simulated using a two temperature model (TTM). The
predicted surface temperatures confirm that film removal below 1 J/cm2 to be
predominately by a non-thermal mechanism.


  Abstract. This article determines relations between two notions concerning
monoids: factorability structure, introduced to simplify the bar complex; and
quadratic normalisation, introduced to generalise quadratic rewriting systems
and normalisations arising from Garside families. Factorable monoids are
characterised in the axiomatic setting of quadratic normalisations.
Additionally, quadratic normalisations of class (4,3) are characterised in
terms of factorability structures and a condition ensuring the termination of
the associated rewriting system.


  We study the rotational properties of an attractively interacting Bose gas in
a quadratic + quartic potential. The low-lying modes of both rotational ground
state configurations, namely the vortex and the center of mass rotating states,
are solved. The vortex excitation spectrum is positive for weak interactions
but the lowest modes decrease rapidly to negative values when the interactions
become stronger. The broken rotational symmetry involved in the center of mass
rotating state induces the appearance of an extra zero-energy mode in the
Bogoliubov spectrum. The excitations of the center of mass rotational state
also demonstrate the coupling between the center of mass and relative motions.


  The chiral anomaly is a striking signature of quantum effects which lead to
the non-conservation of a classically conserved current, specifically the
chiral currents in systems of fermions. In condensed matter systems, the chiral
anomaly can be realized in Weyl semimetals, which then exhibit a signature
electromagnetic response associated to anomaly due to the separation of the
Weyl points in momentum space. In the presence of strong interactions however,
a Weyl semimetal phase can give rise to an ordered phase, and spontaneously
break the chiral symmetry. This then leads to a Goldstone mode which can have
intrinsic dynamics and fluctuations, leading to a dynamical chiral anomaly
response -- a situation known as a dynamical axion insulator. Here we consider
a simple model of this dynamical axion insulator and calculate the equations of
motion for the Goldstone mode. Surprisingly, we find that the Goldstone mode
appears to exhibit a negative phase stiffness, signalling a further instability
of the system towards finite momentum. This is expected to lead to very strong
fluctuations of the anomalous response. We suggest a long-wavelength theory of
Lifschitz type which may govern the axion dynamics in this system and comment
on possible signatures of this model.


  Prochter et al. 2006 recently found that the number density of strong
intervening 0.5<z<2 MgII absorbers detected in gamma-ray burst (GRB) afterglow
spectra is nearly 4 times larger than in QSO spectra. We have conducted a
similar study using CIV absorbers. Our CIV sample, consisting of a total of 20
systems, is drawn from 3 high resolution and high to moderate S/N VLT/UVES
spectra of 3 long-duration GRB afterglows, covering the redshift interval 1.6<
z<3.1. The column density distribution and number density of this sample do not
show any statistical difference with the same quantities measured in QSO
spectra. We discuss several possibilities for the discrepancy between CIV and
MgII absorbers and conclude that a higher dust extinction in the MgII QSO
samples studied up to now would give the most straightforward solution.
However, this effect is only important for the strong MgII absorbers.
Regardless of the reasons for this discrepancy, this result confirms once more
that GRBs can be used to detect a side of the universe that was unknown before,
not necessarily connected with GRBs themselves, providing an alternative and
fundamental investigative tool of the cosmic evolution of the universe.


  We prove a general theorem that the
$L_{\rho}^2({\mathbb{R}^{d}};{\mathbb{R}^{1}})\otimes
L_{\rho}^2({\mathbb{R}^{d}};{\mathbb{R}^{d}})$ valued solution of an infinite
horizon backward doubly stochastic differential equation, if exists, gives the
stationary solution of the corresponding stochastic partial differential
equation. We prove the existence and uniqueness of the
$L_{\rho}^2({\mathbb{R}^{d}};{\mathbb{R}^{1}})\otimes
L_{\rho}^2({\mathbb{R}^{d}};{\mathbb{R}^{d}})$ valued solutions for backward
doubly stochastic differential equations on finite and infinite horizon with
linear growth without assuming Lipschitz conditions, but under the monotonicity
condition. Therefore the solution of finite horizon problem gives the solution
of the initial value problem of the corresponding stochastic partial
differential equations, and the solution of the infinite horizon problem gives
the stationary solution of the SPDEs according to our general result.


  We show that after generic filling along a torus boundary component of a
3-manifold, no two closed, 2-sided, essential surfaces become isotopic, and no
closed, 2-sided, essential surface becomes inessential. That is, the set of
essential surfaces (considered up to isotopy) survives unchanged in all
suitably generic Dehn fillings. Furthermore, for all but finitely many
non-generic fillings, we show that two essential surfaces can only become
isotopic in a constrained way.


  The increasing prevalence of rich sources of data and the availability of
electronic medical record databases and electronic registries opens tremendous
opportunities for enhancing medical research. For example, controlled trials
are ubiquitously used to investigate the effect of a medical treatment, perhaps
dependent on a set of patient covariates, and traditional approaches have
relied primarily on randomized patient sampling and allocation to treatment and
control group. However, when covariate data for a large cohort group of
patients have already been collected and are available in a database, one can
potentially design a treatment/control sample and allocation that provides far
better estimates of the covariate-dependent effects of the treatment. In this
paper, we develop a new approach that uses optimal design of experiments (DOE)
concepts to accomplish this objective. The approach selects the patients for
the treatment and control samples upfront, based on their covariate values, in
a manner that optimizes the information content in the data. For the optimal
sample selection, we develop simple guidelines and an optimization algorithm
that provides solutions that are substantially better than random sampling.
Moreover, our approach causes no sampling bias in the estimated effects, for
the same reason that DOE principles do not bias estimated effects. We test our
method with a simulation study based on a testbed data set containing
information on the effect of statins on low-density lipoprotein (LDL)
cholesterol.


  In this paper we report preliminary results of a simulation study on an
energy-efficient time synchronization scheme based on source clock frequency
recovery (SCFR) at sensor nodes in asymmetric wireless sensor networks (WSNs),
where a head node --- serving as a gateway between wired and wireless networks
--- is equipped with a powerful processor and supplied power from outlet, and
sensor nodes --- connected only through wireless channels --- are limited in
processing and battery-powered. In the SCFR-based WSN time synchronization
scheme, we concentrate on battery-powered sensor nodes and reduce their energy
consumption by minimizing the number of message transmissions from sensor nodes
to the head node. Through simulation experiments we analyze the performance of
the SCFR-based WSN time synchronization scheme, including the impact of SCFR on
time synchronization based on two-way message exchange, and demonstrate the
feasibility of the proposed time synchronization scheme.


  In laboratory experiments we demonstrate that protoplasmic tubes of acellular
slime mould \emph{Physarum polycephalum} show current versus voltage profiles
consistent with memristive systems and that the effect is due to the living
protoplasm of the mould. This complements previous findings on memristive
properties of other living systems (human skin and blood) and contributes to
development of self-growing bio-electronic circuits. Distinctive asymmetric
$V$-$I$ curves which were occasionally observed when the internal current is on
the same order as the driven current, are well-modelled by the concept of
active memristors.


  This paper investigates the resource allocation algorithm design for
intelligent reflecting surface (IRS) aided multiple-input single-output (MISO)
orthogonal frequency division multiple access (OFDMA) multicell networks, where
a set of base stations cooperate to serve a set of ultra-reliable low-latency
communication (URLLC) users. The IRS is deployed to enhance the communication
channel and increase reliability by creating a virtual line of sight for URLLC
users with unfavorable propagation conditions. This is the first study on
IRS-enhanced OFDMA-URLLC systems. The resource allocation algorithm design is
formulated as an optimization problem for the maximization of the weighted
system sum throughput while guaranteeing the quality of service of the URLLC
users. The optimization problem is non-convex and finding the globally optimal
solution entails a high computational complexity which is not desirable for
real-time applications. Therefore, a suboptimal iterative algorithm is proposed
which \textit{jointly} optimizes all optimization variables in each iteration
using a new iterative rank minimization approach. The algorithm is guaranteed
to converge to a locally optimal solution of the formulated optimization
problem. Our simulation results show that the proposed IRS design facilitates
URLLC and yields large performance gains compared to two baseline schemes.


  We show that the (1,0) tensor and hypermultiplet supersymmetry variations can
be uplifted to loop space. Upon dimensional reduction we make contact with
abelian five-dimensional super Yang-Mills, which has a nonabelian
generalization that we subsequently uplift back to loop space where we
conjecture a nonabelian generalization of the (1,0) supersymmetry variations
and demonstrate their on-shell closure.


  Algorithms for rare event complex systems simulations are proposed.
Compressed Sensing (CS) has {\it revolutionized} our understanding of limits in
signal recovery and has forced us to re-define Shannon-Nyquist sampling theorem
for sparse recovery. A formalism to reconstruct trajectories and transition
paths via CS is illustrated as proposed algorithms. The implication of
under-sampling is quite important. This formalism could increase the tractable
time-scales {\it immensely} for simulation of statistical mechanical systems
and rare event simulations. While, long time-scales are known to be a major
hurdle and a challenge for realistic complex simulations for rare events. The
outline of how to implement, test and possible challenges on the proposed
approach are discussed in detail.


  In session-based recommendation settings, a recommender system has no access
to long-term user profiles and thus has to base its suggestions on the user
interactions that are observed in an ongoing session. Since such sessions can
consist of only a small set of interactions, various approaches based on Graph
Neural Networks (GNN) were recently proposed, as they allow us to integrate
various types of side information about the items in a natural way.
Unfortunately, a variety of evaluation settings are used in the literature,
e.g., in terms of protocols, metrics and baselines, making it difficult to
assess what represents the state of the art. In this work, we present the
results of an evaluation of eight recent GNN-based approaches that were
published in high-quality outlets. For a fair comparison, all models are
systematically tuned and tested under identical conditions using three common
datasets. We furthermore include k-nearest-neighbor and sequential rules-based
models as baselines, as such models have previously exhibited competitive
performance results for similar settings. To our surprise, the evaluation
showed that the simple models outperform all recent GNN models in terms of the
Mean Reciprocal Rank, which we used as an optimization criterion, and were only
outperformed in three cases in terms of the Hit Rate. Additional analyses
furthermore reveal that several other factors that are often not deeply
discussed in papers, e.g., random seeds, can markedly impact the performance of
GNN-based models. Our results therefore (a) point to continuing issues in the
community in terms of research methodology and (b) indicate that there is ample
room for improvement in session-based recommendation.


  The automatic development of phenotype algorithms from Electronic Health
Record data with machine learning (ML) techniques is of great interest given
the current practice is very time-consuming and resource intensive. The
extraction of design patterns from phenotype algorithms is essential to
understand their rationale and standard, with great potential to automate the
development process. In this pilot study, we perform network visualization on
the design patterns and their associations with phenotypes and sites. We
classify design patterns using the fragments from previously annotated
phenotype algorithms as the ground truth. The classification performance is
used as a proxy for coherence at the attribution level. The bag-of-words
representation with knowledge-based features generated a good performance in
the classification task (0.79 macro-f1 scores). Good classification accuracy
with simple features demonstrated the attribution coherence and the feasibility
of automatic identification of design patterns. Our results point to both the
feasibility and challenges of automatic identification of phenotyping design
patterns, which would power the automatic development of phenotype algorithms.


  In this paper we present the problem of saturation of a given morphism in the
database category DB, which is the base category for the functiorial semantics
of the database schema mapping systems used in Data Integration theory. This
phenomena appears in the case when we are using the Second-Order
tuple-generating dependencies (SOtgd) with existentially quantified
non-built-in functions, for the database schema mappings. We provide the
algorithm of the saturation for a given morphism, which represents a mapping
between two relational databases, and show that the original morphism in DB can
be equivalently substituted by its more powerful saturated version in any
commutative diagram in DB.


  In this paper we examine the potential of computer-assisted proof methods to
be applied much more broadly than commonly recognized. More specifically, we
contend that there are vast opportunities to derive useful mathematical results
and properties that are extremely narrow in scope, and of practical relevance
only to highly-specialized engineering applications, that are presently
overlooked because they have characteristics atypical of those that are
conventionally pursued in the areas of pure and applied mathematics. As a
concrete example, we demonstrate use of automated methods for certifying
polynomial nonnegativity as a part of a dimension-pinning strategy to prove
that the inverse of the relative gain array (RGA) of a d-dimensional
positive-definite matrix is doubly-stochastic for $d\leq 4$.


  Ultra high-energy (UHE) cosmic rays (CRs) from distant sources interact with
intergalactic radiation fields, leading to their spallation and attenuation.
They are also deflected in intergalactic magnetic fields (IGMFs), particularly
those associated with Mpc-scale structures. These deflections extend the
propagation times of CR particles, forming a magnetic horizon for each CR
species. The cumulative cooling and interactions of a CR ensemble also modifies
their spectral shape and composition observed on Earth. We construct a
transport formulation to calculate the observed UHE CR spectral composition for
4 classes of source population. The effects on CR propagation brought about by
IGMFs are modeled as scattering processes during transport, by centers
associated with cosmic filaments. Our calculations demonstrate that IGMFs can
have a marked effect on observed UHE CRs, and that source population models are
degenerate with IGMF properties. Interpretation of observations, including the
endorsement or rejection of any particular source classes, thus needs careful
consideration of the structural properties and evolution of IGMFs. Future
observations providing tighter constraints on IGMF properties will
significantly improve confidence in assessing UHE CR sources and their
intrinsic CR production properties.


  Reference-based video object segmentation is an emerging topic which aims to
segment the corresponding target object in each video frame referred by a given
reference, such as a language expression or a photo mask. However, language
expressions can sometimes be vague in conveying an intended concept and
ambiguous when similar objects in one frame are hard to distinguish by
language. Meanwhile, photo masks are costly to annotate and less practical to
provide in a real application. This paper introduces a new task of sketch-based
video object segmentation, an associated benchmark, and a strong baseline. Our
benchmark includes three datasets, Sketch-DAVIS16, Sketch-DAVIS17 and
Sketch-YouTube-VOS, which exploit human-drawn sketches as an informative yet
low-cost reference for video object segmentation. We take advantage of STCN, a
popular baseline of semi-supervised VOS task, and evaluate what the most
effective design for incorporating a sketch reference is. Experimental results
show sketch is more effective yet annotation-efficient than other references,
such as photo masks, language and scribble.


  When a self-gravitating spherical gas cloud collapses or accretes onto a
central mass, the inner region of the cloud develops a density profile
$\rho\propto r^{-3/2}$ and the velocity approaches free-fall. We show that in
this region, nonspherical perturbations grow with decreasing radius. In the
linear regime, the tangential velocity perturbation increases as $r^{-1}$,
while the Lagrangian density perturbation, $\Delta\rho/\rho$, grows as
$r^{-1/2}$. Faster growth occurs if the central collapsed object maintains a
finite multiple moment, in which case $\Delta\rho/\rho$ increases as $r^{-l}$,
where $l$ specifies the angular degree of the perturbation. These scaling
relations are different from those obtained for the collapse of a homogeneous
cloud. Our numerical calculations indicate that nonspherical perturbations are
damped in the subsonic region, and that they grow and approach the asymptotic
scalings in the supersonic region. The implications of our results to
asymmetric supernova collapse and to black hole accretion are briefly
discussed.


  We use time-independent incomplete Hamiltonian flows to excise interesting
closed subsets of positive codimension from symplectic manifolds. Examples of
such subsets include what we call a "Cantor brush", a "box with a tail", and --
more generally -- epigraphs of lower semicontinuous functions. This answers a
question of Alan Weinstein about excision of a ray, and it generalizes a result
of Bernd Stratmann about excision of the product of a ray with a manifold.


  A new mechanism for pressure profile relaxations in an edge tokamak plasma is
derived from simulations within the two-fluid three-dimensional turbulence code
EMEDGE3D. The relaxation is due to diamagnetic coupling in the resistive
ballooning/drift wave dynamics: unstable modes experience explosive growth at
high pressure gradients after a phase in which they are stabilized by the
diamagnetic coupling leading to the onset of a transport barrier. The sheared
$E\times B$ flow does not play any significant role. After relaxation the
transport barrier forms again and it sets the conditions for a novel
relaxation, resulting in an oscillatory behavior. We find that energy flux into
the scrape of layer decreases with increasing oscillation frequency and that
the oscillations are tamed by increasing plasma temperature. This behavior is
reminiscent of so-called type III Edge Localized Modes. A one-dimensional model
reproducing the relaxations is also derived.


  In this paper, we first provide a spanning tree (ST)-based centralized group
key agreement protocol for unbalanced mobile Ad Hoc networks (MANETs). Based on
the centralized solution, a local spanning tree (LST)-based distributed
protocol for general MANETs is subsequently presented. Both protocols follow
the basic features of the HSK scheme: 1) H means that a hybrid approach, which
is the combination of key agreement and key distribution via symmetric
encryption, is exploited; 2) S indicates that a ST or LSTs are adopted to form
a connected network topology; and 3) K implies that the extended Kruskal
algorithm is employed to handle dynamic events. It is shown that the HSK scheme
is a uniform approach to handle the initial key establishment process as well
as all kinds of dynamic events in group key agreement protocol for MANETs.
Additionally, the extended Kruskal algorithm enables to realize the reusability
of the precomputed secure links to reduce the overhead. Moreover, some other
aspects, such as the network topology connectivity and security, are well
analyzed.


  Currently available quantum computing hardware platforms have limited 2-qubit
connectivity among their addressable qubits. In order to run a generic quantum
algorithm on such a platform, one has to transform the initial logical quantum
circuit describing the algorithm into an equivalent one that obeys the
connectivity restrictions.
  In this work we construct a circuit synthesis scheme that takes as input the
qubit connectivity graph and a quantum circuit over the gate set generated by
$\{\text{CNOT},R_{Z}\}$ and outputs a circuit that respects the connectivity of
the device. As a concrete application, we apply our techniques to Google's
Bristlecone 72-qubit quantum chip connectivity, IBM's Tokyo 20-qubit quantum
chip connectivity, and Rigetti's Acorn 19-qubit quantum chip connectivity. In
addition, we also compare the performance of our scheme as a function of
sparseness of randomly generated quantum circuits.
  Note: Recently, the authors of arXiv:1904.00633 independently presented a
similar optimization scheme. Our work is independent of arXiv:1904.00633, being
a longer version of the seminar presented by Beatrice Nash at the Dagstuhl
Seminar 18381: Quantum Programming Languages, pg. 120, September 2018,
Dagstuhl, Germany, slide deck available online at
https://materials.dagstuhl.de/files/18/18381/18381.BeatriceNash.Slides.pdf.


  We prove a conjecture by A. Pnueli and strengthen it showing a sequence of
"counting modalities" none of which is expressible in the temporal logic
generated by the previous modalities, over the real line, or over the positive
reals. Moreover, there is no finite temporal logic that can express all of them
over the real line, so that no finite metric temporal logic is expressively
complete.


  Existing video super-resolution methods often utilize a few neighboring
frames to generate a higher-resolution image for each frame. However, the
redundant information between distant frames has not been fully exploited in
these methods: corresponding patches of the same instance appear across distant
frames at different scales. Based on this observation, we propose a video
super-resolution method with long-term cross-scale aggregation that leverages
similar patches (self-exemplars) across distant frames. Our model also consists
of a multi-reference alignment module to fuse the features derived from similar
patches: we fuse the features of distant references to perform high-quality
super-resolution. We also propose a novel and practical training strategy for
referenced-based super-resolution. To evaluate the performance of our proposed
method, we conduct extensive experiments on our collected CarCam dataset and
the Waymo Open dataset, and the results demonstrate our method outperforms
state-of-the-art methods. Our source code will be publicly available.


  The pressure-dependence of the hidden order phase transition of URu2Si2 is
shown to depend sensitively upon the quality of hydrostatic pressure conditions
during electrical resistivity measurements. Hysteresis in pressure is
demonstrated for two choices of pressure medium: the commonly-used mixture of
1:1 Fluorinert FC70/FC77 and pure FC75. In contrast, no hysteresis is observed
when the pressure medium is a 1:1 mixture of n-pentane/isoamyl alcohol, as it
remains hydrostatic over the entire studied pressure range. Possible
ramifications for the interpretation of the temperature-pressure phase diagram
of URu2Si2 are discussed.


  We present the Dirac equation in a geometry with torsion and non-metricity
balancing generality and simplicity as much as possible. In doing so, we use
the vielbein formalism and the Clifford algebra. We also use an index-free
formalism which allows us to construct objects that are totally invariant. It
turns out that the previous apparatuses not only make possible a simple
deduction of the Dirac equation but also allow us to exhibit some details that
is generally obscure in the literature.


  A genome, composed of a precisely ordered sequence of four nucleotides
(ATCG), encompasses a multitude of specific genome features like AAA motif.
Mutations occurring within a genome disrupt the sequential order and
composition of these features, thereby influencing the evolutionary
trajectories and yielding variants. The evolutionary relatedness between a
variant and its ancestor can be estimated by assessing evolutionary distances
across a spectrum of genome features. This study develops a novel,
alignment-free algorithm that considers both the sequential order and
composition of genome features, enabling computation of the Fr\'echet distance
(Fr) across multiple genome features to quantify the evolutionary status of a
variant. Integrating this algorithm with an artificial recurrent neural network
(RNN) reveals the quantitative evolutionary trajectory and origin of
SARS-CoV-2, a puzzle unsolved by alignment-based phylogenetics. The RNN
generates the evolutionary trajectory from Fr data at two levels: genome
sequence mutations and organism variants. At the genome sequence level,
SARS-CoV-2 evolutionarily shortens its genome to enhance its infectious
capacity. Mutating signature features, such as TTA and GCT, increases its
infectious potential and drives its evolution. At the organism level, variants
mutating a single biomarker possess low infectious potential. However, mutating
multiple markers dramatically increases their infectious capacity, propelling
the COVID-19 pandemic. SARS-CoV-2 likely originates from mink coronavirus
variants, with its origin trajectory traced as follows: mink, cat, tiger,
mouse, hamster, dog, lion, gorilla, leopard, bat, and pangolin. Together,
mutating multiple signature features and biomarkers delineates the evolutionary
trajectory of mink-origin SARS-CoV-2, leading to the COVID-19 pandemic. Full
text and detailed on https://combai.org/ai/covidgenome/


  The PANDA detector at FAIR aims to conduct an antiproton-proton experiment
with a very high rate capability. It is expected to feature high mass
resolution, more than 20 times better than achieved at B-factories. PANDA is in
a unique position to perform highly resolved mass scan, and to measure the
width of very narrow charm and charmonium-like states, whose nature is still
unknown, 12 years after their discovery. In this report, we present a method to
determine the width of the $D_{s0}^*(2317)^+$. We discuss the future
perspectives of PANDA, based on our present simulations, in relation with the
recent measurements performed by LHCb and the performances in this field at the
B factories.


  The prediction of a stock price has always been a challenging issue, as its
volatility can be affected by many factors such as national policies, company
financial reports, industry performance, and investor sentiment etc.. In this
paper, we present a prediction model based on deep CNN and the candle charts,
the continuous time stock information is processed. According to different
information richness, prediction time interval and classification method, the
original data is divided into multiple categories as the training set of CNN.
In addition, the convolutional neural network is used to predict the stock
market and analyze the difference in accuracy under different classification
methods.
  The results show that the method has the best performance when the forecast
time interval is 20 days. Moreover, the Moving Average Convergence Divergence
and three kinds of moving average are added as input. This method can
accurately predict the stock trend of the US NDAQ exchange for 92.2%.
Meanwhile, this article distinguishes three conventional classification methods
to provide guidance for future research.


  We study the steady state structure and dynamics of an interface in a pure
Ising system on a square lattice placed in an inhomogeneous external field. The
field has a profile with a fixed shape designed to stabilize a flat interface,
and is translated with velocity v_e. For small v_e, the interface is stuck to
the profile, is macroscopically smooth, and is rippled with a periodicity in
general incommensurate with the lattice parameter. For arbitrary orientations
of the profile, the local slope of the interface locks in to one of infinitely
many rational values (devil's staircase) which most closely approximates the
profile. These ``lock-in'' structures and ripples dissappear as v_e increases.
For still larger v_e the profile detaches from the interface which is now
characterized by standard Kardar-Parisi-Zhang (KPZ) exponents.


  The time-dependent non-crossing approximation is utilized to determine the
effects of the crystal planes of gold contacts on time dependent current
through a quantum dot suddenly shifted into the Kondo regime via a gate
voltage. For an asymmetrically coupled system, instantaneous conductance
exhibits complex fluctuations. We identify the frequencies participating in
these fluctuations and they turn out to be proportional to the separation
between the sharp features in the density of states and the Fermi level in
agreement with previous studies. Based on this observation, we predict that
using different crystal planes as electrodes would give rise to drastically
different transient currents which can be accessed with ultrafast pump-probe
techniques.


  Time-series anomaly detection deals with the problem of detecting anomalous
timesteps by learning normality from the sequence of observations. However, the
concept of normality evolves over time, leading to a "new normal problem",
where the distribution of normality can be changed due to the distribution
shifts between training and test data. This paper highlights the prevalence of
the new normal problem in unsupervised time-series anomaly detection studies.
To tackle this issue, we propose a simple yet effective test-time adaptation
strategy based on trend estimation and a self-supervised approach to learning
new normalities during inference. Extensive experiments on real-world
benchmarks demonstrate that incorporating the proposed strategy into the
anomaly detector consistently improves the model's performance compared to the
baselines, leading to robustness to the distribution shifts.


  The operator-Schmidt decomposition is useful in quantum information theory
for quantifying the nonlocality of bipartite unitary operations. We construct a
family of unitary operators on C^n tensor C^n whose operator-Schmidt
decompositions are computed using the discrete Fourier transform. As a
corollary, we produce unitaries on C^3 tensor C^3 with operator-Schmidt number
S for every S in {1,...,9}. This corollary was unexpected, since it
contradicted reasonable conjectures of Nielsen et al [Phys. Rev. A 67 (2003)
052301] based on intuition from a striking result in the two-qubit case. By the
results of Dur, Vidal, and Cirac [Phys. Rev. Lett. 89 (2002) 057901
quant-ph/0112124], who also considered the two-qubit case, our result implies
that there are nine equivalence classes of unitaries on C^3 tensor C^3 which
are probabilistically interconvertible by (stochastic) local operations and
classical communication. As another corollary, a prescription is produced for
constructing maximally-entangled operators from biunimodular functions.
Reversing tact, we state a generalized operator-Schmidt decomposition of the
quantum Fourier transform considered as an operator C^M_1 tensor C^M_2 -->
C^N_1 tensor C^N_2, with M_1 x M_2 = N_1 x N_2. This decomposition shows (by
Nielsen's bound) that the communication cost of the QFT remains maximal when a
net transfer of qudits is permitted. In an appendix, a canonical procedure is
given for removing basis-dependence for results and proofs depending on the
"magic basis" introduced in [S. Hill and W. Wootters, "Entanglement of a pair
of quantum bits," Phys Rev. Lett 78 (1997) 5022-5025, quant-ph/9703041 (and
quant-ph/9709029)].


  We propose an extension of the standard model where quarks are viewed as
fermions with a ``bare'' integer (weak) hypercharge which is normalized with a
fractional part created by a quantized topological Chern-Simons configuration
of the weak gauge fields. Consistency with hypercharge patterns not included in
the standard model is shown.


  Adversarial decision making is a particular type of decision making problem
where the gain a decision maker obtains as a result of his decisions is
affected by the actions taken by others. Representation of alternatives'
evaluations and methods to find the optimal alternative are two important
aspects in the adversarial decision making. The aim of this study is to develop
a general framework for solving the adversarial decision making issue under
uncertain environment. By combining fuzzy set theory, game theory and D numbers
theory (DNT), a DNT based game-theoretic framework for adversarial decision
making under fuzzy environment is presented. Within the proposed framework or
model, fuzzy set theory is used to model the uncertain evaluations of decision
makers to alternatives, the non-exclusiveness among fuzzy evaluations are taken
into consideration by using DNT, and the conflict of interests among decision
makers is considered in a two-person non-constant sum game theory perspective.
An illustrative application is given to demonstrate the effectiveness of the
proposed model. This work, on one hand, has developed an effective framework
for adversarial decision making under fuzzy environment; One the other hand, it
has further improved the basis of DNT as a generalization of Dempster-Shafer
theory for uncertainty reasoning.


  Outlier detection for high-dimensional (HD) data is a popular topic in modern
statistical research. However, one source of HD data that has received
relatively little attention is functional magnetic resonance images (fMRI),
which consists of hundreds of thousands of measurements sampled at hundreds of
time points. At a time when the availability of fMRI data is rapidly
growing---primarily through large, publicly available grassroots
datasets---automated quality control and outlier detection methods are greatly
needed. We propose PCA leverage and demonstrate how it can be used to identify
outlying time points in an fMRI run. Furthermore, PCA leverage is a measure of
the influence of each observation on the estimation of principal components,
which are often of interest in fMRI data. We also propose an alternative
measure, PCA robust distance, which is less sensitive to outliers and has
controllable statistical properties. The proposed methods are validated through
simulation studies and are shown to be highly accurate. We also conduct a
reliability study using resting-state fMRI data from the Autism Brain Imaging
Data Exchange and find that removal of outliers using the proposed methods
results in more reliable estimation of subject-level resting-state networks
using ICA.


  We analyse the stability of linear dynamical systems defined on sparse,
random graphs with predator-prey, competitive, and mutualistic interactions.
These systems are aimed at modelling the stability of fixed points in large
systems defined on complex networks, such as, ecosystems consisting of a large
number of species that interact through a food-web. We develop an exact theory
for the spectral distribution and the leading eigenvalue of the corresponding
sparse Jacobian matrices. This theory reveals that the nature of local
interactions have a strong influence on system's stability. We show that, in
general, linear dynamical systems defined on random graphs with a prescribed
degree distribution of unbounded support are unstable if they are large enough,
implying a tradeoff between stability and diversity. Remarkably, in contrast to
the generic case, antagonistic systems that only contain interactions of the
predator-prey type can be stable in the infinite size limit. This qualitatively
feature for antagonistic systems is accompanied by a peculiar oscillatory
behaviour of the dynamical response of the system after a perturbation, when
the mean degree of the graph is small enough. Moreover, for antagonistic
systems we also find that there exist a dynamical phase transition and critical
mean degree above which the response becomes non-oscillatory.


  Reflexive polygons have been extensively studied in a variety of contexts in
mathematics and physics. We generalize this programme by looking at the 45
different lattice polygons with two interior points up to SL(2,$\mathbb{Z}$)
equivalence. Each corresponds to some affine toric 3-fold as a cone over a
Sasaki-Einstein 5-fold. We study the quiver gauge theories of D3-branes probing
these cones, which coincide with the mesonic moduli space. The minimum of the
volume function of the Sasaki-Einstein base manifold plays an important role in
computing the R-charges. We analyze these minimized volumes with respect to the
topological quantities of the compact surfaces constructed from the polygons.
Unlike reflexive polytopes, one can have two fans from the two interior points,
and hence give rise to two smooth varieties after complete resolutions, leading
to an interesting pair of closely related geometries and gauge theories.


  Metal electrodes are a universal element of all electronic devices.
Conducting SrRuO3 (SRO) epitaxial thin films have been extensively used as
electrodes in complex-oxide heterostructures due to good lattice mismatches
with perovskite substrates. However, when compared to SRO single crystals, SRO
thin films have shown reduced conductivity and Curie temperatures (T_C), which
can lead to higher Joule heating and energy loss in the devices. Here, we
report that high-quality SRO thin films can be synthesized by controlling the
plume dynamics and growth rate of pulsed laser epitaxy (PLE) with real-time
optical spectroscopic monitoring. The SRO thin films grown under the
kinetically controlled conditions, down to ca. 16 nm in thickness, exhibit both
enhanced conductivity and T_C as compared to bulk values, due to their improved
stoichiometry and a strain-mediated increase of the bandwidth of Ru 4d
electrons. This result provides a direction for enhancing the physical
properties of PLE-grown thin films and paves a way for improved device
applications.


  We present a cross-correlation between the ELAIS 15$\mu$m ISO survey with the
{\it ROSAT} (0.1-2 keV) all-sky survey and the pointed observations WGACAT
source catalogue.
  The resulting sample contains 15 objects.
  Optical spectroscopic identifications exist for 13 objects: 6 broad-line
QSOs, 4 narrow line galaxies or type-2 AGN (NLG) and 3 stars. We have used both
the X-ray to IR luminosity flux ratio $f_{x}/f_{IR}$ and the X-ray hardness
ratios diagnostics to estimate the amount of obscuration in these objects.
  The X-ray spectrum of the narrow-line galaxies does not present strong
evidence for obscuration; however, the low $f_{x}/f_{IR}$ ratio combined with
the high X-ray luminosities suggest that at least one of the narrow line
galaxies is associated with an obscured Seyfert nucleus. 4 out of 6 QSOs
present high $f_{x}/f_{IR}$ ratios and steep X-ray spectra with $\Gamma>2$. One
QSO (ELAISC15-J133442+375736) at a redshift of z=1.89, has an abnormally low
X-ray/IR flux ratio, with its infrared luminosity approaching that of an
hyperluminous galaxy ($\sim10^{12.98} h^{-2} L_\odot$). Finally, one radio-loud
QSO is the hardest X-ray source in our sample, presenting strong evidence for a
high absorbing column ($N_H\sim10^{22}\rm cm^{-2}$).


  Despite the promising high-data rate features of visible light communications
(VLC), they still suffer from unbalanced services due to blockages and channel
fluctuation among users. This paper introduces and evaluates a new transmission
scheme which adopts cooperative non-orthogonal multiple access (Co-NOMA) in
hybrid VLC/radio-frequency (RF) systems, so as to improve both system sum-rate
and fairness. Consider a network consisting of one VLC access point (AP) and
multiple strong and weak users, where each weak user is paired with a strong
user. Each weak user can be served either directly by the VLC AP, or via the
strong user which converts light information received through the VLC link, and
forwards the information to the weak user via the RF link. The paper then
maximizes a network-wide weighted sum-rate, so as to jointly determine the
strong-weak user-pairs, the serving link of each weak user (i.e., either direct
VLC or hybrid VLC/RF), and the power of each user message, subject to user
connectivity and transmit power constraints. The paper tackles such a
mixed-integer non-convex optimization problem using an iterative approach.
Simulations show that the proposed scheme significantly improves the VLC
network performance (i.e., sum-rate and fairness) as compared to the
conventional NOMA scheme.


  We study the spectrum of quasinormal mode frequencies for a Proca field on a
rotating black hole spacetime. First, we review how the introduction of field
mass modifies the spectrum in the scalar-field case, leading to evanescent
modes and to quasiresonance. Next, we examine the three physical polarizations
of the Proca field and their relation to the electromagnetic field modes in the
massless limit. Exploiting a separation of variables, we obtain a five-term
recurrence relation from an appropriate ansatz for the radial function.
Gaussian elimination and the modified Lentz algorithm are applied, and the
quasinormal frequencies are computed from the roots of a continued fraction. We
validate our method by calculating quasibound state frequencies, which are
complementary to quasinormal modes, and which can be calculated using the same
method. We present a selection of results for the low-lying overtones of all
three polarizations, across a range of black hole spins and field masses.


  We establish duality for monogamy of entanglement: whereas monogamy of
entanglement inequalities provide an upper bound for bipartite sharability of
entanglement in a multipartite system, we prove that the same quantity provides
a \emph{lower} bound for distribution of bipartite entanglement in a
multipartite system.
  Our theorem for monogamy of entanglement is used to establish relations
between bipartite entanglement that separate one qubit from the rest vs
separating two qubits from the rest.


  A novel information theoretic approach is proposed to solve the secret
sharing problem, in which a dealer distributes one or multiple secrets among a
set of participants that for each secret only qualified sets of users can
recover it by pooling their shares together while non-qualified sets of users
obtain no information about the secret even if they pool their shares together.
While existing secret sharing systems (implicitly) assume that communications
between the dealer and participants are noiseless, this paper takes a more
practical assumption that the dealer delivers shares to the participants via a
noisy broadcast channel. An information theoretic approach is proposed, which
exploits the channel as additional resources to achieve secret sharing
requirements. In this way, secret sharing problems can be reformulated as
equivalent secure communication problems via wiretap channels, and can be
solved by employing powerful information theoretic security techniques. This
approach is first developed for the classic secret sharing problem, in which
only one secret is to be shared. This classic problem is shown to be equivalent
to a communication problem over a compound wiretap channel. The lower and upper
bounds on the secrecy capacity of the compound channel provide the
corresponding bounds on the secret sharing rate. The power of the approach is
further demonstrated by a more general layered multi-secret sharing problem,
which is shown to be equivalent to the degraded broadcast multiple-input
multiple-output (MIMO) channel with layered decoding and secrecy constraints.
The secrecy capacity region for the degraded MIMO broadcast channel is
characterized, which provides the secret sharing capacity region. Furthermore,
these secure encoding schemes that achieve the secrecy capacity region provide
an information theoretic scheme for sharing the secrets.


  We investigate the effect of the interlayer spin-flip tunneling for the
interlayer magnetoresistance under magnetic fields in alpha-(BEDT-TTF)2I3,
which is a multilayer massless Dirac fermion system under pressure. The mean
field of the spin-flip correlation associated with the interlayer Coulomb
interaction enables the interlayer spin-flip tunneling. Assuming the
non-vertical interlayer spin-flip tunneling, we calculate the interlayer
magnetoresistance using the Kubo formula. The crossover magnetic field, at
which the interlayer magnetoresistance changes from positive to negative is
shifted by the Zeeman energy and in good agreement with the experiment.


  We investigate the transitions induced by external current fluctuations on a
small probe quantum system. The rates for the transitions between the energy
states are calculated using the real-time Keldysh formalism for the density
matrix evolution. We especially detail the effects of the third cumulant of
current fluctuations inductively coupled to a quantum bit and propose a setup
for detecting the frequency-dependent third cumulant through the transitions it
induces.


  The self-excitation of plasma series resonance (PSR) oscillations is a
prominent feature in the current of low pressure capacitive radio frequency
(RF) discharges. This resonance leads to high frequency oscillations of the
charge in the sheaths and enhances electron heating. Up to now, the phenomenon
has only been observed in asymmetric discharges. There, the nonlinearity in the
voltage balance, which is necessary for the self-excitation of resonance
oscillations with frequencies above the applied frequencies, is caused
predominantly by the quadratic contribution to the charge-voltage relation of
the plasma sheaths. Using PIC/MCC simulations of single- and multi- frequency
capacitive discharges and an equivalent circuit model, we demonstrate that
other mechanisms such as a cubic contribution to the charge-voltage relation of
the plasma sheaths and the time dependent bulk electron plasma frequency can
cause the self-excitation of PSR oscillations, as well. These mechanisms have
been neglected in previous models, but are important for the theoretical
description of the current in symmetric or weakly asymmetric discharges.


  Multimodality has recently gained attention in the medical domain, where
imaging or video modalities may be integrated with biomedical signals or health
records. Yet, two challenges remain: balancing the contributions of modalities,
especially in cases with a limited amount of data available, and tackling
missing modalities. To address both issues, in this paper, we introduce the
AnchoreD multimodAl Physiological Transformer (ADAPT), a multimodal, scalable
framework with two key components: (i) aligning all modalities in the space of
the strongest, richest modality (called anchor) to learn a joint embedding
space, and (ii) a Masked Multimodal Transformer, leveraging both inter- and
intra-modality correlations while handling missing modalities. We focus on
detecting physiological changes in two real-life scenarios: stress in
individuals induced by specific triggers and fighter pilots' loss of
consciousness induced by $g$-forces. We validate the generalizability of ADAPT
through extensive experiments on two datasets for these tasks, where we set the
new state of the art while demonstrating its robustness across various modality
scenarios and its high potential for real-life applications.


  Core-collapse theory brings together many facets of high-energy and nuclear
astrophysics and the numerical arts to present theorists with one of the most
important, yet frustrating, astronomical questions: "What is the mechanism of
core-collapse supernova explosions?" A review of all the physics and the
fifty-year history involved would soon bury the reader in minutiae that could
easily obscure the essential elements of the phenomenon, as we understand it
today. Moreover, much remains to be discovered and explained, and a complicated
review of an unresolved subject in flux could grow stale fast. Therefore, in
this paper I describe what I think are various important facts and perspectives
that may have escaped the attention of those interested in this puzzle.
Furthermore, I attempt to describe the modern theory's physical underpinnings
and briefly summarize the current state of play. In the process, I identify a
few myths (as I see them) that have crept into modern discourse. However, there
is much more to do and humility in the face of this age-old challenge is
clearly the most prudent stance as we seek its eventual resolution.


  By using the dark-field real-space imaging technique of transmission electron
microscopy (TEM), we have observed slow 200 A-scale fluctuations of
charge-ordered (CO) phase in mixed-valent manganites under a strong electron
beam irradiation. In addition to these unusual fluctuations of the CO phase, we
observed the switching-type fluctuations of electrical resistivity in the same
sample, which were found to be as large as several percents. Systematic
analysis indicates that these two different types of fluctuations with a
similar time scale of the order of seconds are interconnected through a
meta-stable insulating charge-disordered state. Current dependence of the
fluctuations suggests a non-equilibrium nature of this slow dynamics.


  We study various properties of the vibrational normal modes for
Coulomb-interacting particles in two-dimensional irregular confinement using
numerical simulations. By analyzing the participation ratio and spectral
statistics, we characterize the vibrational modes for Coulomb clusters as
localized, quasi-localized and delocalized. We also study a novel correlation
function to understand the spatial structure of these different kinds of modes
and subsequently extract the associated characteristic length scales. We
further demonstrate that, at any given temperature, particles exhibiting larger
displacement over a time interval comparable to the structural relaxation time,
are strongly correlated with the low-frequency quasi-localized modes of the
inherent structure corresponding to the initial configuration. Establishing
this correlation for Coulomb clusters paves the path to identify the particular
feature of the initial configuration that determines the previously observed
heterogeneous dynamics of the particles at low temperatures in these systems.


  We show that all $p$-adic quintic forms in at least $n>4562911$ variables
have a non-trivial zero. We also derive new result concerning systems of cubic
and quadratic forms.


  The ratio set of a set of positive integers $A$ is defined as $R(A) := \{a /
b : a, b \in A\}$. The study of the denseness of $R(A)$ in the set of positive
real numbers is a classical topic and, more recently, the denseness in the set
of $p$-adic numbers $\mathbb{Q}_p$ has also been investigated. Let $A_1,
\ldots, A_k$ be a partition of $\mathbb{N}$ into $k$ sets. We prove that for
all prime numbers $p$ but at most $\lfloor \log_2 k \rfloor$ exceptions at
least one of $R(A_1), \ldots, R(A_k)$ is dense in $\mathbb{Q}_p$. Moreover, we
show that for all prime numbers $p$ but at most $k - 1$ exceptions at least one
of $A_1, \ldots, A_k$ is dense in $\mathbb{Z}_p$. Both these results are
optimal in the sense that there exist partitions $A_1, \ldots, A_k$ having
exactly $\lfloor \log_2 k \rfloor$, respectively $k - 1$, exceptional prime
numbers; and we give explicit constructions for them. Furthermore, as a
corollary, we answer negatively a question raised by Garcia et al.


  Theory of the Casimir effect for a flat graphene layer interacting with a
parallel flat material is presented in detail. The high-temperature asymptotics
of a free energy in a graphene-metal system coincides with a Drude
high-temperature asymptotics of the metal-metal system. High-temperature
behavior in the graphene-metal system is expected at separations of the order
of 100 nm at temperature T=300K.


  A real time trace gas detector for benzene is demonstrated. The measurement
system takes an advantage of modest enrichment through short adsorption periods
to reach a ppt-level detection limit with a sampling cycle of 90 s, which
includes sample adsorption, desorption and a spectroscopic measurement. Benzene
is collected on Tenax TA sorbent for 30 s and then detected from the enriched
samples with photoacoustic spectroscopy. A high sensitivity is achieved using
cantilever-enhanced photoacoustic spectroscopy and a continuous-wave quantum
cascade laser emitting at the wavelength 14.8 $\mu$m, which corresponds to the
absorption wavelength of the strongest benzene infrared band. We reach a
detection limit of 150 ppt of benzene, over one sampling cycle. Interference
from humidity and other common petrochemicals is evaluated.


  Non-negative matrix and tensor factorisations are a classical tool for
finding low-dimensional representations of high-dimensional datasets. In
applications such as imaging, datasets can be regarded as distributions
supported on a space with metric structure. In such a setting, a loss function
based on the Wasserstein distance of optimal transportation theory is a natural
choice since it incorporates the underlying geometry of the data. We introduce
a general mathematical framework for computing non-negative factorisations of
both matrices and tensors with respect to an optimal transport loss. We derive
an efficient computational method for its solution using a convex dual
formulation, and demonstrate the applicability of this approach with several
numerical illustrations with both matrix and tensor-valued data.


  The classes PPA-$p$ have attracted attention lately, because they are the
main candidates for capturing the complexity of Necklace Splitting with $p$
thieves, for prime $p$. However, these classes were not known to have complete
problems of a topological nature, which impedes any progress towards settling
the complexity of the Necklace Splitting problem. On the contrary, topological
problems have been pivotal in obtaining completeness results for PPAD and PPA,
such as the PPAD-completeness of finding a Nash equilibrium [Daskalakis et al.,
2009, Chen et al., 2009b] and the PPA-completeness of Necklace Splitting with 2
thieves [Filos-Ratsikas and Goldberg, 2019].
  In this paper, we provide the first topological characterization of the
classes PPA-$p$. First, we show that the computational problem associated with
a simple generalization of Tucker's Lemma, termed $p$-polygon-Tucker, as well
as the associated Borsuk-Ulam-type theorem, $p$-polygon-Borsuk-Ulam, are
PPA-$p$-complete. Then, we show that the computational version of the
well-known BSS Theorem [Barany et al., 1981], as well as the associated
BSS-Tucker problem are PPA-$p$-complete. Finally, using a different
generalization of Tucker's Lemma (termed $\mathbb{Z}_p$-star-Tucker), which we
prove to be PPA-$p$-complete, we prove that $p$-thief Necklace Splitting is in
PPA-$p$. This latter result gives a new combinatorial proof for the Necklace
Splitting theorem, the only proof of this nature other than that of Meunier
[2014].
  All of our containment results are obtained through a new combinatorial proof
for $\mathbb{Z}_p$-versions of Tucker's lemma that is a natural generalization
of the standard combinatorial proof of Tucker's lemma by Freund and Todd
[1981]. We believe that this new proof technique is of independent interest.


  Many recent activities of IEEE 802.11 Working group have been focused on
improving power efficiency of Wi-Fi to make it favorable for massive Internet
of Things scenarios, in which swarms of battery supplied sensors rarely
communicate with remote servers. The latest step towards this direction is the
work on a new IEEE 802.11ba amendment to the Wi-Fi standard, which introduces
Wake-Up Radio. This radio is an additional interface with extremely low power
consumption that is used to transmit control information from the access point
to stations while their primary radio is switched off. This paper describes the
IEEE 802.11ba protocol, discusses its open issues, investigates several
approaches to provide energy efficient data transmission with 802.11ba, and
evaluates how much 802.11ba improves energy efficiency and even reduces channel
time consumption.


  This paper, which is the natural continuation of a previous paper by the same
authors, studies a class of optimal control problems with state constraints
where the state equation is a differential equation with delays. This class
includes some problems arising in economics, in particular the so-called models
with time to build. The problem is embedded in a suitable Hilbert space H and
the regularity of the associated Hamilton-Jacobi-Bellman (HJB) equation is
studied. Therein the main result is that the value function V solves the HJB
equation and has continuous classical derivative in the direction of the
present. The goal of the present paper is to exploit such result to find
optimal feedback strategies for the problem. While it is easy to define
formally a feedback strategy in classical sense the proof of its existence and
of its optimality is hard due to lack of full regularity of V and to the
infinite dimension. Finally, we show some approximation results that allow us
to apply our main theorem to obtain epsilon-optimal strategies for a wider
class of problems.


  These are the lecture notes from a five-hour mini-course given at the Winter
School on Galois Theory held at the University of Luxembourg in February 2012.
Their aim is to give an overview of Serre's modularity conjecture and of its
proof by Khare, Wintenberger, and Kisin, as well as of the results of other
mathematicians that played an important role in the proof. Along the way we
remark on some recent (as of 2012) work concerning generalizations of the
conjecture.


  In atomic vapor cells, atoms collide with the inner surface, causing their
spin to randomize on the walls. This wall-depolarizing effect is diffusive, and
it becomes more pronounced in smaller vapor cells under high temperatures. In
this work, we investigate the polarization of optically-pumped alkali-metal
atoms in a millimeter-sized cell heated to $% 150 $ Celsius. We consider two
extreme boundary conditions: fully depolarizing and nondepolarizing boundaries,
and we provide an analytical estimation of the polarization difference between
them. In the nondepolarizing case, the pump beam's absorption is proportional
to the average atomic polarization. However, for fully depolarizing walls, the
absorption peak may correspond to a polarization minimum. To mitigate the wall
effect, we propose reducing the pump beam's diameter while maintaining the pump
power to prevent illumination of the cell wall and increase the pump intensity
in the central area. This is crucial for compact vapor-cell devices where the
laser frequency can not be detuned since it is locked to the absorption peaks.
Additionally, we analyze the wall-depolarizing effect on the performance of an
alkali-metal atomic magnetometer operating in the spin-exchange relaxation-free
regime. We show that the signal strength is highly limited by wall collisions,
and we provide an upper bound for it.


  This seems to be the first English translation of this paper from the French
original, ``Sur les rentes viageres''. In the paper, Euler gives a general
formula for calculating the price of a life annuity that yields a certain
amount per year, assuming the annuity manager can get a 5 percent return, for
people of different ages. He also gives formulas to calculate the price of
annuities that only start to pay out a certain number of years after they are
purchased. He gives many numerical examples, giving tables for the prices of
annuities for annuitants up to 90 years old.


  The ability to timely process significant amounts of continuously updated
spatial data is mandatory for an increasing number of applications. In this
paper we focus on a specific data-intensive problem concerning the repeated
processing of huge amounts of k nearest neighbours (k-NN) queries over massive
sets of moving objects, where the spatial extents of queries and the position
of objects are continuously modified over time. In particular, we propose a
novel hybrid CPU/GPU pipeline that significantly accelerate query processing
thanks to a combination of ad-hoc data structures and non-trivial memory access
patterns. To the best of our knowledge this is the first work that exploits
GPUs to efficiently solve repeated k-NN queries over massive sets of
continuously moving objects, even characterized by highly skewed spatial
distributions. In comparison with state-of-the-art sequential CPU-based
implementations, our method highlights significant speedups in the order of
10x-20x, depending on the datasets, even when considering cheap GPUs.


  A new term in the p-adic world-sheet action is proposed, which couples a
constant B-field to the boundary of the world-sheet at disk level. The induced
deformation of tachyon scattering amplitudes by star-products is derived. This
is in agreement with the deformation of effective action postulated in recent
investigations of noncommutative solitons in p-adic string theory.


  We study on weakly-supervised object detection (WSOD) which plays a vital
role in relieving human involvement from object-level annotations. Predominant
works integrate region proposal mechanisms with convolutional neural networks
(CNN). Although CNN is proficient in extracting discriminative local features,
grand challenges still exist to measure the likelihood of a bounding box
containing a complete object (i.e., "objectness"). In this paper, we propose a
novel WSOD framework with Objectness Distillation (i.e., WSOD^2) by designing a
tailored training mechanism for weakly-supervised object detection. Multiple
regression targets are specifically determined by jointly considering bottom-up
(BU) and top-down (TD) objectness from low-level measurement and CNN
confidences with an adaptive linear combination. As bounding box regression can
facilitate a region proposal learning to approach its regression target with
high objectness during training, deep objectness representation learned from
bottom-up evidences can be gradually distilled into CNN by optimization. We
explore different adaptive training curves for BU/TD objectness, and show that
the proposed WSOD^2 can achieve state-of-the-art results.


  A simple statistical mechanical model proposed by Wako and Sait$\hat{\rm o}$
has explained the aspects of protein folding surprisingly well. This model was
systematically applied to multiple proteins by Mu$\tilde{\rm n}$oz and Eaton
and has since been referred to as the Wako-Sait$\hat{\rm o}$-Mu$\tilde{\rm
n}$oz-Eaton (WSME) model. The success of the WSME model in explaining the
folding of many proteins has verified the hypothesis that the folding is
dominated by native interactions, which makes the energy landscape globally
biased toward native conformation. Using the WSME and other related models,
Sait$\hat{\rm o}$ emphasized the importance of the hierarchical pathway in
protein folding; folding starts with the creation of contiguous segments having
a native-like configuration and proceeds as growth and coalescence of these
segments. The $\phi$-values calculated for barnase with the WSME model
suggested that segments contributing to the folding nucleus are similar to the
structural modules defined by the pattern of native atomic contacts. The WSME
model was extended to explain folding of multi-domain proteins having a complex
topology, which opened the way to comprehensively understanding the folding
process of multi-domain proteins. The WSME model was also extended to describe
allosteric transitions, indicating that the allosteric structural movement does
not occur as a deterministic sequential change between two conformations but as
a stochastic diffusive motion over the dynamically changing energy landscape.
Statistical mechanical viewpoint on folding, as highlighted by the WSME model,
has been renovated in the context of modern methods and ideas, and will
continue to provide insights on equilibrium and dynamical features of proteins.


  Radar detects stable, long-range objects under variable weather and lighting
conditions, making it a reliable and versatile sensor well suited for
ego-motion estimation. In this work, we propose a radar-only odometry pipeline
that is highly robust to radar artifacts (e.g., speckle noise and false
positives) and requires only one input parameter. We demonstrate its ability to
adapt across diverse settings, from urban UK to off-road Iceland, achieving a
scan matching accuracy of approximately 5.20 cm and 0.0929 deg when using GPS
as ground truth (compared to visual odometry's 5.77 cm and 0.1032 deg). We
present algorithms for keypoint extraction and data association, framing the
latter as a graph matching optimization problem, and provide an in-depth system
analysis.


  The sources of ultrahigh-energy cosmic rays (UHECRs) have been stubbornly
elusive. However, the latest report of the Pierre Auger Observatory provides a
compelling indication for a possible correlation between the arrival directions
of UHECRs and nearby starburst galaxies. We argue that if starbursts are
sources of UHECRs, then particle acceleration in the large-scale terminal shock
of the superwind that flows from the starburst engine represents the best known
concept model in the market. We investigate new constraints on the model and
readjust free parameters accordingly. We show that UHECR acceleration above
about 10^{11} GeV remains consistent with observation. We also show that the
model could accommodate hard source spectra as required by Auger data. We
demonstrate how neutrino emission can be used as a discriminator among
acceleration models.


  Bundles of strings which interact via short-ranged pair potentials are
studied in two dimensions. The corresponding transfer matrix problem is solved
analytically for arbitrary string number N by Bethe ansatz methods. Bundles
consisting of N identical strings exhibit a unique unbinding transition. If the
string bundle interacts with a hard wall, the bundle may unbind from the wall
via a unique transition or a sequence of N successive transitions. In all
cases, the critical exponents are independent of N and the density profile of
the strings exhibits a scaling form that approaches a mean-field profile in the
limit of large N.


  Convolutional neural networks are the most widely used deep learning
algorithms for traffic signal classification till date but they fail to capture
pose, view, orientation of the images because of the intrinsic inability of max
pooling layer.This paper proposes a novel method for Traffic sign detection
using deep learning architecture called capsule networks that achieves
outstanding performance on the German traffic sign dataset.Capsule network
consists of capsules which are a group of neurons representing the
instantiating parameters of an object like the pose and orientation by using
the dynamic routing and route by agreement algorithms.unlike the previous
approaches of manual feature extraction,multiple deep neural networks with many
parameters,our method eliminates the manual effort and provides resistance to
the spatial variances.CNNs can be fooled easily using various adversary attacks
and capsule networks can overcome such attacks from the intruders and can offer
more reliability in traffic sign detection for autonomous vehicles.Capsule
network have achieved the state-of-the-art accuracy of 97.6% on German Traffic
Sign Recognition Benchmark dataset (GTSRB).


  We present a model-independent description of the exclusive rare decays B->
K* e+e- in the low recoil region (large lepton invariant mass q^2 ~ m_b^2). In
this region the long-distance effects from quark loops can be computed with the
help of an operator product expansion in 1/Q, with Q={m_b, \sqrt{q^2}}.
Nonperturbative effects up to and including terms suppressed by Lambda/Q and
mc^2/mb^2 relative to the short-distance amplitude can be included in a
model-independent way. Based on these results, we propose an improved method
for determining the CKM matrix element |V{ub}| from a combination of rare and
semileptonic B and D decays near the zero recoil point. The residual
theoretical uncertainty from long distance effects in this |V{ub}|
determination comes from terms in the OPE of order alpha_s(Q)\Lambda/mb,
alpha_s^2(Q), mc^4/mb^4$ and duality violations and is estimated to be below
10%.


  The mathematical models used to represent physical phenomena are generally
known to be imperfect representations of reality. Model inadequacies arise for
numerous reasons, such as incomplete knowledge of the phenomena or
computational intractability of more accurate models. In such situations it is
impractical or impossible to improve the model, but necessity requires its use
to make predictions. With this in mind, it is important to represent the
uncertainty that a model's inadequacy causes in its predictions, as neglecting
to do so can cause overconfidence in its accuracy. A powerful approach to
addressing model inadequacy leverages the composite nature of physical models
by enriching a flawed embedded closure model with a stochastic error
representation. This work outlines steps in the development of a stochastic
operator as an inadequacy representation by establishing the framework for
inferring an infinite-dimensional operator and by introducing a novel method
for interrogating available high-fidelity models to learn about modeling error.


  We study the linear response to strain in a mean field elastoplastic model
for athermal amorphous solids, incorporating the power-law mechanical noise
spectrum arising from plastic events. In the "jammed" regime of the model,
where the plastic activity exhibits a non-trivial slow relaxation referred to
as aging, we find that the stress relaxes incompletely to an age-dependent
plateau, on a timescale which grows with material age. We determine the scaling
behaviour of this aging linear response analytically, finding that key scaling
exponents are universal and independent of the noise exponent $\mu$. For
$\mu>1$, we find simple aging, where the stress relaxation timescale scales
linearly with the age $t_{\rm w}$ of the material. At $\mu=1$, which
corresponds to interactions mediated by the physical elastic propagator, we
find instead a $t_{\rm w}^{1/2}$ scaling arising from the stretched exponential
decay of the plastic activity. We compare these predictions with measurements
of the linear response in computer simulations of a model jammed system of
repulsive soft athermal particles, during its slow dissipative relaxation
towards mechanical equilibrium, and find good agreement with the theory.


  Current autonomous driving systems are composed of a perception system and a
decision system. Both of them are divided into multiple subsystems built up
with lots of human heuristics. An end-to-end approach might clean up the system
and avoid huge efforts of human engineering, as well as obtain better
performance with increasing data and computation resources. Compared to the
decision system, the perception system is more suitable to be designed in an
end-to-end framework, since it does not require online driving exploration. In
this paper, we propose a novel end-to-end approach for autonomous driving
perception. A latent space is introduced to capture all relevant features
useful for perception, which is learned through sequential latent
representation learning. The learned end-to-end perception model is able to
solve the detection, tracking, localization and mapping problems altogether
with only minimum human engineering efforts and without storing any maps
online. The proposed method is evaluated in a realistic urban driving
simulator, with both camera image and lidar point cloud as sensor inputs. The
codes and videos of this work are available at our github repo and project
website.


  We present results of a dual eclipse expedition to observe the solar corona
from two sites during the annular solar eclipse of 2023 October 14, using a
novel coronagraph designed to be accessible for amateurs and students to build
and deploy. The coronagraph "CATEcor" builds on the standardized eclipse
observing equipment developed for the Citizen CATE 2024 experiment. The
observing sites were selected for likelihood of clear observations, for
historic relevance (near the Climax site in the Colorado Rocky Mountains), and
for centrality to the annular eclipse path (atop Sandia Peak above Albuquerque,
New Mexico). The novel portion of CATEcor is an external occulter assembly that
slips over the front of a conventional dioptric telescope, forming a
"shaded-truss" externally occulted coronagraph. CATEcor is specifically
designed to be easily constructed in a garage or "makerspace" environment. We
successfully observed some bright features in the solar corona to an altitude
of approximately 2.25 R$_\odot$ during the annular phases of the eclipse.
Future improvements to the design, in progress now, will reduce both stray
light and image artifacts; our objective is to develop a design that can be
operated successfully by amateur astronomers at sufficient altitude even
without the darkened skies of a partial or annular eclipse.


  We present multiwavelength data for twelve blazars observed from 2008-2010 as
part of an ongoing optical-infrared photometric monitoring project. Sources
were selected to be bright, southern (dec < 20 deg) blazars observed by the
Fermi Gamma-Ray Space Telescope, with daily and weekly gamma-ray fluxes made
available from the start of the Fermi mission. Light curves are presented for
the twelve blazars in BVRJK at near-daily cadence. We find that optical and
infrared fluxes are well correlated in all sources. Gamma-ray bright flat
spectrum radio quasars (FSRQs) in our sample have optical/infrared emission
correlated with gamma-rays consistent with inverse Compton-scattering models
for GeV emission. In FSRQs, the variability amplitude decreases towards
optical/IR wavelengths, consistent with the presence of a thermal emission
component from the accretion disk varying on significantly longer timescales
than the jet synchrotron emission. In BL Lac objects, variability is mainly
constant across wavelengths, consistent with a weak or radiatively inefficient
disk. FSRQs have redder optical-infrared colors when they are brighter, while
BL Lac objects show no such trend. Several objects show complicated
color-magnitude behavior: AO 0235+164 appears in two different states depending
on whether it is gamma-ray bright or not. OJ 287 and 3C 279 show some
hysteresis tracks in their color-magnitude diagrams. Individual flares may be
achromatic or otherwise depart from the trend, suggesting different jet
components becoming important at different times. We present a time-dependent
spectral energy distribution of the bright FSRQ 3C 454.3 during its December
2009 flare, which is well fit by an external Compton model in the bright state,
although day to day changes pose challenges to a simple one-zone model. All
data from the SMARTS monitoring program are publicly available on our website.


  Sequences of events in noise-driven excitable systems with slow variables
often show serial correlations among their intervals of events. Here, we employ
a master equation for general non-renewal processes to calculate the interval
and count statistics of superimposed processes governed by a slow adaptation
variable. For an ensemble of spike-frequency adapting neurons this results in
the regularization of the population activity and an enhanced post-synaptic
signal decoding. We confirm our theoretical results in a population of cortical
neurons.


  It is known that a self-adjoint, time-independent hamiltonian can be defined
for the quantum damped harmonic oscillator. We show here that the two vacua
naturally associated to this operator, when expressed in terms of
pseudo-bosonic lowering and raising operators, appear to be non
square-integrable. This fact is interpreted as the evidence of the dissipation
effect of the classical oscillator at a purely quantum level.


  Some spatially homogeneous Bianchi type I cosmological models filled with
homogeneous ``electric'' $p$-form fields are shown to mimic the never-ending
oscillatory behaviour of generic string cosmologies established recently. The
validity of the ``Kasner-free-flights plus collisions-on-potential-walls''
picture is also illustrated in the case of known, non-chaotic, superstring
solutions.