  The spatial distribution of galaxies in the Local Group (LG) is the footprint
of its formation mechanism and the gravitational interactions among its members
and the external massive galaxies or galaxy groups. Recently, Pasetto & Chiosi
(2007), using a 3D-geometrical description of the spatial distribution of all
the members of the LG (not only the satellites of the MW and M31) based on
present-day data on positions and distances, found that all galaxies (MW, M31,
their satellites, and even the most distant objects) are confined within a slab
of about 200 kpc thickness. Examining how external galaxies or groups would
gravitationally affect (and eventually alter) the planar structure (and its
temporal evolution) of the LG, they found that the external force field acts
parallel to the plane determined by geometry and studied this with the Least
Action Principle. In this paper, we have thoroughly investigated the role
played by the tidal forces exerted by external galaxies or galaxy groups on the
LG galaxies (the most distant dwarfs in particular) in shaping their large
scale distribution. The idea based on the well known effect of tidal
interactions, according to which a system of mass-points can undergo not only
tidal stripping but also tidal compression and thus become flatter. Excluding
the dwarf galaxies tightly bound to the MW and M31, the same tidal forces can
account for the planar distribution of the remaining dwarf galaxies. We
analytically recover the results of Pasetto & Chiosi (2007) and prove that a
planar distribution of the LG dwarf galaxies is compatible with the external
force field. We also highlight the physical cause of this result.


  The Method of Increments (MoI) has been employed using a multireference
approach to calculate the dissociation curve of beryllium ring-shaped clusters
Be$_n$ of different sizes. Benchmarks obtained through different single and
multireference methods including the ab initio Density Matrix Renormalization
Group (DMRG) were used to verify the validity of the MoI truncation which
showed a reliable behavior for the whole dissociation curve. Moreover we
investigated the size dependence of the correlation energy at different
distances in order to extrapolate the values for the periodic chain and to
discuss the transition from a metal-like to a insulating-like behavior of the
wave function through quantum chemical considerations.


  The displacement field of an object surface can be measured by using speckle
interferometry. This technique is based on the phenomenon of laser speckle and
consists in correlating speckle interferograms taken after and before the
deformation of the surface. The main requirement is that the surface under
study must be optically rough to generate the speckle patterns to be
correlated. In this paper, we present a very simple and intuitive method based
on speckle interferometry to measure out-of-plane displacements on specular
reflecting surfaces that generate no speckle patterns. The method consists in a
modified digital speckle pattern interferometer which requires no special
equipment other than that used in conventional speckle interferometers. The
proposed method could find useful application in the measurement of thermal
deformation of mirrors.


  We consolidate the BFJ and BTF (MVD) relations into a generalized Scaling
Mass Velocity Relation applicable to both pressure-supported galaxy clusters
and rotation-supported galaxies. Unlike MOND inspired relations containing a
characteristic acceleration scale and its normalization factor, our proposal is
dependent on observed dynamic surface mass densities and discrepancies. We
perform the same analysis for a sample of HIFLUGCS galaxy clusters (Tian et al,
2021) found in prior work with SPARC galaxies (arXiv: 2101.01537). For this
galaxy cluster sample, we find little evidence for a universal acceleration
constant as previously recognized for galaxies. We finish with an examination
of the virial energies for the combined sample recovering a mass-energy
relation consistent with the phenomenology.


  We study committee elections from a perspective of finding the most
conflicting candidates, that is, candidates that imply the largest amount of
conflict, as per voter preferences. By proposing basic axioms to capture this
objective, we show that none of the prominent multiwinner voting rules meet
them. Consequently, we design committee voting rules compliant with our
desiderata, introducing conflictual voting rules. A subsequent deepened
analysis sheds more light on how they operate. Our investigation identifies
various aspects of conflict, for which we come up with relevant axioms and
quantitative measures, which may be of independent interest. We support our
theoretical study with experiments on both real-life and synthetic data.


  One of the major challenges for the engineering of wireless sensing systems
is to improve the software abstractions and frameworks that are available to
programmers while ensuring system reliability and efficiency. The distributed
systems community have developed a rich set of such abstractions for building
dependable distributed systems connected using wired networks, however after 20
years research many of these elude wireless sensor systems. In this paper we
present X Process Commit (XPC) an atomic commit protocol framework that
utilizes Synchronous Transmission (ST). We also introduce Hybrid, a technique
that allows us to exploit the advantages of the Glossy and Chaos Synchronous
Transmission primitives to get lower latency and higher reliability than
either. Using XPC and Hybrid we demonstrate how to build protocols for the
classical 2-phase and 3-phase commit abstractions and evaluate these
demonstrating significantly improved performance and reliability than the use
of Glossy or Chaos individually as dissemination primitives. We address how we
overcame the timing challenges of bringing Glossy and Chaos together to form
Hybrid and through extensive experimentation demonstrate that it is robust to
in-network radio interference caused by multiple sources. We are first to
present testbed results that show that Hybrid can provide almost 100%
reliability in a network of nodes suffering from various levels of radio
interference.


  For lossy image compression systems, we develop an algorithm, iterative
refinement, to improve the decoder's reconstruction compared to standard
decoding techniques. Specifically, we propose a recurrent neural network
approach for nonlinear, iterative decoding. Our decoder, which works with any
encoder, employs self-connected memory units that make use of causal and
non-causal spatial context information to progressively reduce reconstruction
error over a fixed number of steps. We experiment with variants of our
estimator and find that iterative refinement consistently creates lower
distortion images of higher perceptual quality compared to other approaches.
Specifically, on the Kodak Lossless True Color Image Suite, we observe as much
as a 0.871 decibel (dB) gain over JPEG, a 1.095 dB gain over JPEG 2000, and a
0.971 dB gain over a competitive neural model.


  We investigate systems of interacting stochastic differential equations with
two kinds of heterogeneity: one originating from different weights of the
linkages, and one concerning their asymptotic relevance when the system becomes
large. To capture these effects we define a partial mean field system, and
prove a law of large numbers with explicit bounds on the mean squared error.
Furthermore, a large deviation result is established under reasonable
assumptions. The theory will be illustrated by several examples: on the one
hand, we recover the classical results of chaos propagation for homogeneous
systems, and on the other hand, we demonstrate the validity of our assumptions
for quite general heterogeneous networks including those arising from
preferential attachment random graph models.


  Estimating the parameters of gravitational wave signals detected by
ground-based detectors requires an understanding of the properties of the
detectors' noise. In particular, the most commonly used likelihood function for
gravitational wave data analysis assumes that the noise is Gaussian,
stationary, and of known frequency-dependent variance. The variance of the
colored Gaussian noise is used as a whitening filter on the data before
computation of the likelihood function. In practice the noise variance is not
known and it evolves over timescales of dozens of seconds to minutes. We study
two methods for estimating this whitening filter for ground-based gravitational
wave detectors with the goal of performing parameter estimation studies. The
first method uses large amounts of data separated from the specific segment we
wish to analyze and computes the power spectral density of the noise through
the mean-median Welch method. The second method uses the same data segment as
the parameter estimation analysis, which potentially includes a gravitational
wave signal, and obtains the whitening filter through a fit of the power
spectrum of the data in terms of a sum of splines and Lorentzians. We compare
these two methods and argue that the latter is more reliable for gravitational
wave parameter estimation.


  By restricting to a special class of smooth functions, the local action of
the symmetry group is globalized. This special class of functions is
constructed using parabolic induction.


  Interchange drive and cross-field transport of density filaments in
quasi-neutral inhomogeneously magnetized electron-positron plasmas is shown to
be strongly reduced by the presence of minority ions. Two mechanisms are
identified for the reduction in radial propagation and plasma transport:
effective mass related inertia, and collisionality dependent Boltzmann spin-up
of the filaments. Numerical results are obtained with a three-dimensional
full-F multi-species gyrofluid model.


  Stability of soliton families in one-dimensional nonlinear Schroedinger
equations with non-parity-time (PT)-symmetric complex potentials is
investigated numerically. It is shown that these solitons can be linearly
stable in a wide range of parameter values both below and above phase
transition. In addition, a pseudo-Hamiltonian-Hopf bifurcation is revealed,
where pairs of purely-imaginary eigenvalues in the linear-stability spectra of
solitons collide and bifurcate off the imaginary axis, creating oscillatory
instability, which resembles Hamiltonian-Hopf bifurcations of solitons in
Hamiltonian systems even though the present system is dissipative and
non-Hamiltonian. The most important numerical finding is that, eigenvalues of
linear-stability operators of these solitons appear in quartets $(\lambda,
-\lambda, \lambda^*, -\lambda^*)$, similar to conservative systems and
PT-symmetric systems. This quartet eigenvalue symmetry is very surprising for
non-PT-symmetric systems, and it has far-reaching consequences on the stability
behaviors of solitons.


  If two particles moving towards a black hole collide in the vicinity of the
horizon, the energy $E_{c.m.}$ in the center of mass frame can grow
indefinitely if one of particles is fine-tuned. This is the Ba\~{n}ados, Silk
and West (BSW) effect. One of objections against this effect consists in that
for some types of a horizon fine-tuned particles cannot reach the horizon.
However, this difficulty can be overcome if instead of exact fine-tuning, one
of particle is nearly fine-tuned, with the value of small detuning being
adjusted to the distance to the horizon. Such particles are called
near-fine-tuned. We give classification of such particles and describe possible
high energy scenarios of collision in which they participate. We analyze the
ranges of possible motion for each type of particle and determine under which
condition such particles can reach the horizon. We analyze collision energy
$E_{c.m.}\,$and determine under which conditions it may grow indefinitely. We
also include into consideration the forces acting on particles and find when
the BSW effect with nearly-fine-tuned particles is possible with finite forces.
We demonstrate that the BSW effect with particles under discussion is
consistent with the principle of kinematic censorship. According to this
principle, $E_{c.m.}\,$cannot be literally infinite in any event of collision
(if no singularity is present), although it can be made as large as one likes.


  Predicting click-through rate (CTR) is the core task of many ads online
recommendation systems, which helps improve user experience and increase
platform revenue. In this type of recommendation system, we often encounter two
main problems: the joint usage of multi-page historical advertising data and
the cold start of new ads. In this paper, we proposed GACE, a graph-based
cross-page ads embedding generation method. It can warm up and generate the
representation embedding of cold-start and existing ads across various pages.
Specifically, we carefully build linkages and a weighted undirected graph model
considering semantic and page-type attributes to guide the direction of feature
fusion and generation. We designed a variational auto-encoding task as
pre-training module and generated embedding representations for new and old ads
based on this task. The results evaluated in the public dataset AliEC from
RecBole and the real-world industry dataset from Alipay show that our GACE
method is significantly superior to the SOTA method. In the online A/B test,
the click-through rate on three real-world pages from Alipay has increased by
3.6%, 2.13%, and 3.02%, respectively. Especially in the cold-start task, the
CTR increased by 9.96%, 7.51%, and 8.97%, respectively.


  The dark sector of the Universe is beginning to be clarified step by step. If
the dark energy is vacuum energy, then 123 orders are exactly reduced by
ordinary physical processes. For many years these unexplained orders were
called a crisis in physics. There was indeed a "crisis" before the introduction
of the holographic principle and entropic force in physics. The vacuum energy
was spent for the organization of new microstates during the entire life of the
Universe, but in the initial period of its evolution the vacuum energy (78
orders) were reduced more effectively by the vacuum condensates produced by
phase transitions, because the Universe lost the high symmetry during its
expansion. Important problems of physics and cosmology can be solved if the
quarks, leptons, and gauge bosons are composite particles. The dark matter,
partially or all consisting of familon-type pseudo-Goldstone bosons with a mass
of 10^{-5} - 10^{-3} eV, can be explained in the composite model. Three
generations of elementary particles are absolutely necessary in this model. In
addition, this model realizes three relativistic phase transitions in a medium
of familons at different red shifts, forming a large-scale structure of dark
matter that was "repeated" by baryons. We predict the detection of dark matter
dynamics, the detection of familons as dark matter particles, and the
development of spectroscopy for dark medium due to the probable presence of
dark atoms in it. Other viewpoints on the dark components of the Universe are
also discussed briefly.


  In the presented work we study, by means of numerical simulations, the
behaviour of a suspension of active ring polymers in the bulk and under lateral
confinement. When changing the separation between the confining planes and the
polymers' density, we detect the emergence of a self-organised dynamical state,
characterised by the coexistence of slowly diffusing clusters of rotating disks
and faster rings moving in between them. This system represents a peculiar case
at the crossing point between polymer, liquid crystals and active matter
physics, where the interplay between activity, topology and confinement leads
to a spontaneous segregation of a one component solution.


  We investigate the general process of black hole pair creation in a
cosmological background, considering the creation of charged and rotating black
holes. We motivate the use of Kerr-Newmann-deSitter solutions to investigate
this process, showing how they arise from more general C-metric type solutions
that describe a pair of general black holes accelerating away from each other
in a cosmological background. All possible KNdS-type spacetimes are classified
and we examine whether they may be considered to be in full thermodynamic
equilibrium. Instantons that mediate the creation of these space-times are
constructed and we see that they are necessarily complex due to regularity
requirements. Thus we argue that instantons need not always be real Euclidean
solutions to the Einstein equations. Finally, we calculate the actions of these
instantons and find that the standard action functional must be modified to
correctly take into account the effects of the rotation. The resultant
probabilities for the creation of the space-times are found to be real and
consistent with the interpretation that the entropy of a charged and rotating
black hole is the logarithm of the number of its quantum states.


  We use a cellular automata model to study the evolution of HIV infection and
the onset of AIDS. The model takes into account the global features of the
immune response to any pathogen, the fast mutation rate of the HIV and a fair
amount of spatial localization. Our results reproduce quite well the
three-phase pattern observed in T cell and virus counts of infected patients,
namely, the primary response, the clinical latency period and the onset of
AIDS. We have also found that the infected cells may organize themselves into
special spatial structures since the primary infection, leading to a decrease
on the concentration of uninfected cells. Our results suggest that these cell
aggregations, which can be associated to syncytia, leads to AIDS.


  The Riccati equation for the Hubble parameter H of barotropic FRW cosmologies
in conformal time for \kappa \neq 0 spatial geometries and in comoving time for
the \kappa =0 geometry, respectively, is generalized to odd Grassmannian time
parameters. We obtain a system of simple differential equations for the four
supercomponents (two of even type and two of odd type) of the Hubble superfield
function {\cal H} that is explicitly solved. The second even Hubble component
does not have an evolution governed by general relativity although there are
effects of the latter upon it


  With the advent of the AI Act and other regulations, there is now an urgent
need for algorithms that repair unfairness in training data. In this paper, we
define fairness in terms of conditional independence between protected
attributes ($S$) and features ($X$), given unprotected attributes ($U$). We
address the important setting in which torrents of archival data need to be
repaired, using only a small proportion of these data, which are $S|U$-labelled
(the research data). We use the latter to design optimal transport (OT)-based
repair plans on interpolated supports. This allows {\em off-sample}, labelled,
archival data to be repaired, subject to stationarity assumptions. It also
significantly reduces the size of the supports of the OT plans, with
correspondingly large savings in the cost of their design and of their {\em
sequential\/} application to the off-sample data. We provide detailed
experimental results with simulated and benchmark real data (the Adult data
set). Our performance figures demonstrate effective repair -- in the sense of
quenching conditional dependence -- of large quantities of off-sample, labelled
(archival) data.


  We study the decoherence dynamics of dipole-coupled two-level quantum systems
in Ramsey-type experiments. We focus on large networks of two-level systems,
confined to two spatial dimensions and with positional disorder giving rise to
disordered dipolar couplings. This setting is relevant for modeling the
decoherence dynamics of the rotational excitations of polar molecules confined
to deep optical lattices, where disorder arises from the random filling of
lattice sites with occupation probability $p$. We show that the decoherence
dynamics exhibits a phase transition at a critical filling $p_c\simeq 0.15$.
For $p<p_c$ the dynamics is disorder-dominated and the Ramsey interference
signal decays on a timescale $T_2 \propto p^{-3/2}$. For $p>p_c$ the dipolar
interactions dominate the disorder, and the system behaves as a collective
spin-ordered phase, representing synchronization of the two-level systems and
persistent Ramsey oscillations with divergent $T_2$ for large systems. For a
finite number of two-level systems, $N$, the spin-ordered phase at $p> p_c$
undergoes a crossover to a collective spin-squeezed state on a timescale
$\tau_{\rm sq} \propto \sqrt{N}$. We develop a self-consistent mean-field
theory that is capable of capturing the synchronization transition at $p_c$,
and provide an intuitive theoretical picture that describes the phase
transition in the long-time dynamics. We also show that the decoherence
dynamics appear to be ergodic in the vicinity of $p_c$, the long-time behaviour
being well described by the predictions of equilibrium thermodynamics. The
results are supported by the results of exact diagonalization studies of small
systems.


  Novel fully discrete schemes are developed to numerically approximate a
semilinear stochastic wave equation driven by additive space-time white noise.
Spectral Galerkin method is proposed for the spatial discretization, and
exponential time integrators involving linear functionals of the noise are
introduced for the temporal approximation. The resulting fully discrete schemes
are very easy to implement and allow for higher strong convergence rate in time
than existing time-stepping schemes such as the Crank-Nicolson-Maruyama scheme
and the stochastic trigonometric method. Particularly, it is shown that the new
schemes achieve in time an order of $1- \epsilon$ for arbitrarily small
$\epsilon >0$, which exceeds the barrier order $\frac{1}{2}$ established by
Walsh. Numerical results confirm higher convergence rates and computational
efficiency of the new schemes.


  Dispersion interactions are long-range interactions between neutral
ground-state atoms or molecules, or polarizable bodies in general, due to their
common interaction with the quantum electromagnetic field. They arise from the
exchange of virtual photons between the atoms, and, in the case of three or
more atoms, are not additive. In this review, after having introduced the
relevant coupling schemes and effective Hamiltonians, as well as properties of
the vacuum fluctuations, we~outline the main properties of dispersion
interactions, both in the nonretarded (van der Waals) and retarded
(Casimir--Polder) regime. We then discuss their deep relation with the
existence of the vacuum fluctuations of the electromagnetic field and vacuum
energy. We describe some transparent physical models of two- and three-body
dispersion interactions, based on dressed vacuum field energy densities and
spatial field correlations, which stress their deep connection with vacuum
fluctuations and vacuum energy. These models give a clear insight of the
physical origin of dispersion interactions, and also provide useful
computational tools for their evaluation. We show that this aspect is
particularly relevant in more complicated situations, for example when
macroscopic boundaries are present. We also review recent results on dispersion
interactions for atoms moving with noninertial motions and the strict relation
with the Unruh effect, and on resonance interactions between entangled
identical atoms in uniformly accelerated motion.


  We consider an agent on a fixed but arbitrary node of a known threshold
network, with the task of detecting an unknown missing link/node. We obtain
analytic formulas for the probability of success, when the agent's tool is the
free evolution of a single excitation on an XX spin system paired with the
network. We completely characterize the parameters allowing for an advantageous
solution. From the results emerges an optimal (deterministic) algorithm for
quantum search, therefore gaining a quadratic speed-up with respect to the
optimal classical analogue, and in line with well-known results in quantum
computation. When attempting to detect a faulty node, the chosen setting
appears to be very fragile and the probability of success too small to be of
any direct use.


  We present Chandra ACIS-I and ACIS-S observations (~200ks in total) of the
X-ray luminous elliptical galaxy NGC4636, located in the outskirts of the Virgo
cluster. A soft band (0.5-2 keV) image shows the presence of a bright core in
the center surrounded by an extended X-ray corona and two pronounced
quasi-symmetric, 8 kpc long, arm-like features. Each of this features defines
the rim of an ellipsoidal bubble. An additional bubble-like feature, whose
northern rim is located ~2 kpc south of the north-eastern arm, is detected as
well. We present surface brightness and temperature profiles across the rims of
the bubbles, showing that their edges are sharp and characterized by
temperature jumps of about 20-25%. Through a comparison of the observed
profiles with theoretical shock models, we demonstrate that a scenario where
the bubbles were produced by shocks, probably driven by energy deposited
off-center by jets, is the most viable explanation to the X-ray morphology
observed in the central part of NGC4636. As a confirmation to this scenario,
radio jets extending towards the bubbles and a central weak X-ray and radio
source are detected and are most likely the signs of AGN activity which was
more intense in the past. A bright dense core of ~1 kpc radius is observed at
the center of NGC4636. A sharp decline in surface brightness from the core to
the ambient gas is observed and is not accompanied by a variation in the
temperature and thus could not be in thermal pressure equilibrium. However the
bright core could be a long lived feature if the radio jets are acting as a
balancing factor to thermal pressure or if the bright core is produced by steep
abundance gradients.


  We study the Dirichlet problem of the following discrete infinity Laplace
equation on a subgraph with finite width $$\Delta_{\infty} u(x) = \inf_{y \sim
x}u(y)+\sup_{y \sim x}u(y)-2u(x) = f(x).$$ We say that a subgraph has finite
width if the distances from all vertices to the boundary are uniformly bounded.
By Perron's method, we show the existence of bounded solutions. We also prove
the uniqueness if $f$ is nonnegative by establishing a comparison result, and
hence obtain the existence of game values for corresponding tug-of-war games
introduced by Peres, Schramm, Sheffield, and Wilson (2009). As an application
we show a strong Liouville property for infinity harmonic functions. By an
argument of Arzela-Ascoli, we prove the convergence of solutions of
$\varepsilon$-tug-of-war games as $\varepsilon$ tends to 0. Correspondingly, we
obtain the existence of bounded solutions to normalized infinity Laplace
equations on Euclidean domains with finite width.


  We extend the definition of eta-weak-pseudo-Hermiticity to the class of
potentials endowed with position-dependent mass. The construction of
non-Hermitian Hamiltonians through some generating function are obtained.
Special cases of potentials are thus deduced.


  We consider inductive limits of weighted spaces of holomorphic functions in
the unit ball of $\mathbb C^n$. The relationship between sets of uniqueness,
weakly sufficient sets and sampling sets in these spaces is studied. In
particular, the equivalence of these sets, under general conditions of the
weights, is obtained.


  An angular distribution of received signals has a significant impact on their
spectral and correlational properties. Most of angular dispersion models do not
consider antenna patterns. The developed procedure for determining the
propagation path parameters enables a wide range of assessment of the impact of
the propagation environment on the received signal properties. In contrast to
the other models, this procedure is based on a geometrical structure, which
parameters are defined on the basis of power delay profile or spectrum This
modeling method allows also the power radiation pattern (PRP) of the
transmitting antenna. The aim of the paper is to present the influence of the
transmitter antenna PRP on the scattering propagation paths that arrive at the
receiver. This analysis is realized on the basis of simulations studies using
the developed procedure. Presented in this paper procedure maps the effects of
propagation phenomena that predominate in an azimuth plane.


  In this note, we define and study Asai gamma factors over finite fields. We
also prove some results about local Asai L-functions over p-adic fields for
level zero representations.


  The convex hulls of face-vertex incident vectors of 3-face-colorable convex
polytopes are computed. It is found that every such convex hull is a
$d$-polytope with $d+2$ or $d+3$ vertices. Utilizing Gale transform and Gale
diagram, we calculate its combinatorial structure. Finally, a necessary and
sufficient criterion for combinatorial equivalence of two such convex hulls is
given.


  Fractonic superfluids are exotic states of matter with spontaneously broken
higher-rank $U(1)$ symmetry. The latter is associated with conserved quantities
that include not only particle number (i.e. charge) but also higher moments,
such as dipoles, quadrupoles, and angular moments. Due to the presence of such
conserved quantities, the mobility of particles is restricted either completely
or partially. In this work, we systematically study hydrodynamical properties
of fractonic superfluids, especially focusing on the fractonic superfluids with
conserved angular moments. The constituent bosons are called "lineons" with
$d$-components in $d$-dimensional space. From Euler-Lagrange equation, we
derive the continuity equation and Navier-Stokes-like equations, in which the
angular moment conservation introduces extra terms. Furthermore, we discuss the
current configurations that are related to the defects. Like the conventional
superfluid, we study the critical values of velocity fields and density
currents, which gives rise to a Landau-like criterion. At the end of this work,
several future directions are discussed.


  We report the first detection of the molecule cyanomethyl, CH$_2$CN, in a
protoplanetary disk. Until now, CH$_2$CN had only been observed at earlier
evolutionary stages, in the giant molecular clouds TMC-1 and Sgr 2, and the
prestellar core L1544. We detect six transitions of ortho-CH$_2$CN towards the
disk around nearby T Tauri star TW Hya. An excitation analysis reveals that the
disk-averaged column density, $N$, for ortho-CH$_2$CN is $(6.3\pm
0.5)\times10^{12}$ cm$^{-2}$, which is rescaled to reflect a 3:1 ortho-para
ratio, resulting in a total column density, $N_{\rm tot}$, of $(8.4\pm
0.7)\times10^{12}$ cm$^{-2}$. We calculate a disk-average rotational
temperature, $T_{\rm{rot}}$ = $40 \pm 5$ K, while a radially resolved analysis
shows that $T_{\rm{rot}}$ remains relatively constant across the radius of the
disk. This high rotation temperature suggests that in a static disk and if
vertical mixing can be neglected,CH$_2$CN is largely formed through gas-phase
reactions in the upper layers of the disk, rather than solid-state reactions on
the surface of grains in the disk midplane. The integrated intensity radial
profiles show a ring structure consistent with molecules such as CN and DCN. We
note that this is also consistent with previous lower-resolution observations
of centrally peaked CH$_3$CN emission towards the TW Hya disks, since the
observed emission gap disappears when convolving our observations with a larger
beam size. We obtain a CH$_2$CN/CH$_3$CN ratio ranging between 4 and 10. This
high CH$_2$CN/CH$_3$CN is reproduced in a representative chemical model of the
TW Hya disk that employs standard static disk chemistry model assumptions, i.e.
without any additional tuning.


  Our understanding and ability to effectively monitor and manage coastal
ecosystems are severely limited by observation methods. Automatic recognition
of species in natural environment is a promising tool which would revolutionize
video and image analysis for a wide range of applications in marine ecology.
However, classifying fish from images captured by underwater cameras is in
general very challenging due to noise and illumination variations in water.
Previous classification methods in the literature relies on filtering the
images to separate the fish from the background or sharpening the images by
removing background noise. This pre-filtering process may negatively impact the
classification accuracy. In this work, we propose a Convolutional Neural
Network (CNN) using the Squeeze-and-Excitation (SE) architecture for
classifying images of fish without pre-filtering. Different from conventional
schemes, this scheme is divided into two steps. The first step is to train the
fish classifier via a public data set, i.e., Fish4Knowledge, without using
image augmentation, named as pre-training. The second step is to train the
classifier based on a new data set consisting of species that we are interested
in for classification, named as post-training. The weights obtained from
pre-training are applied to post-training as a priori. This is also known as
transfer learning. Our solution achieves the state-of-the-art accuracy of
99.27% accuracy on the pre-training. The accuracy on the post-training is
83.68%. Experiments on the post-training with image augmentation yields an
accuracy of 87.74%, indicating that the solution is viable with a larger data
set.


  Due to the modality discrepancy between textual and acoustic modeling,
efficiently transferring linguistic knowledge from a pretrained language model
(PLM) to acoustic encoding for automatic speech recognition (ASR) still remains
a challenging task. In this study, we propose a cross-modality knowledge
transfer (CMKT) learning framework in a temporal connectionist temporal
classification (CTC) based ASR system where hierarchical acoustic alignments
with the linguistic representation are applied. Additionally, we propose the
use of Sinkhorn attention in cross-modality alignment process, where the
transformer attention is a special case of this Sinkhorn attention process. The
CMKT learning is supposed to compel the acoustic encoder to encode rich
linguistic knowledge for ASR. On the AISHELL-1 dataset, with CTC greedy
decoding for inference (without using any language model), we achieved
state-of-the-art performance with 3.64% and 3.94% character error rates (CERs)
for the development and test sets, which corresponding to relative improvements
of 34.18% and 34.88% compared to the baseline CTC-ASR system, respectively.


  (abridged) We investigate the detailed response of gas to the formation of
transient and long-lived dynamical structures induced in the early stages of a
disk-disk collision, and identify observational signatures of radial gas inflow
through a detailed examination of the collision simulation of an equal mass
bulge dominated galaxy. Stars respond to the tidal interaction by forming both
transient arms and long lived m=2 bars, but the gas response is more transient,
flowing directly toward the central regions within about 10^8 years after the
initial collision. The rate of inflow declines when more than half of the total
gas supply reaches the inner few kpc, where the gas forms a dense nuclear ring
inside the stellar bar. The average gas inflow rate to the central 1.8 kpc is
\~7 Msun/yr with a peak rate of 17 Msun/yr. The evolution of gas in a bulgeless
progenitor galaxy is also discussed, and a possible link to the ``chain
galaxy'' population observed at high redshifts is inferred. The evolution of
the structural parameters (the asymmetry and concentration) of both stars and
gas are studied in detail. Further, a new structural parameter (the compactness
parameter K) that traces the evolution of the size scale of the gas relative to
the stellar disk is introduced. Non-circular gas kinematics driven by the
perturbation of the non-axisymmetric structure can produce distinct emission
features in the "forbidden velocity quadrants'' of the position-velocity
diagram (PVD). The dynamical mass calculated using the rotation curve derived
from fitting the emission envelope of the PVD can determine the true mass to
within 20% to 40%. The evolution of the molecular fraction $M_H2/M_(H2 + HI)
and the compactness (K) are potential tracers to quantitatively assign the age
of the interaction.


  Quadratic algebras are generalizations of Lie algebras which include the
symmetry algebras of 2nd order superintegrable systems in 2 dimensions as
special cases. The superintegrable systems are exactly solvable physical
systems in classical and quantum mechanics. Distinct superintegrable systems
and their quadratic algebras can be related by geometric contractions, induced
by B\^ocher contractions of the conformal Lie algebra $\mathfrak{so}(4,\mathbb
{C})$ to itself. In 2 dimensions there are two kinds of quadratic algebras,
nondegenerate and degenerate. In the geometric case these correspond to 3
parameter and 1 parameter potentials, respectively. In a previous paper we
classified all abstract parameter-free nondegenerate quadratic algebras in
terms of canonical forms and determined which of these can be realized as
quadratic algebras of 2D nondegenerate superintegrable systems on constant
curvature spaces and Darboux spaces, and studied the relationship between
B\^ocher contractions of these systems and abstract contractions of the free
quadratic algebras. Here we carry out an analogous study of abstract
parameter-free degenerate quadratic algebras and their possible geometric
realizations. We show that the only free degenerate quadratic algebras that can
be constructed in phase space are those that arise from superintegrability. We
classify all B\^ocher contractions relating degenerate superintegrable systems
and, separately, all abstract contractions relating free degenerate quadratic
algebras. We point out the few exceptions where abstract contractions cannot be
realized by the geometric B\^ocher contractions.


  Motivated by recent studies of nonlinear perturbations of asymptotically
anti-de Sitter spacetimes, we study gravitational perturbations of $(n+2)$
dimensional Minkowski spacetime with a spherical Dirichlet wall. By considering
the tensor, vector and scalar perturbations on the $n$ sphere, we present
simplified nonhomogeneous equations at arbitrary order in weakly nonlinear
perturbation theory for each sector. A suitable choice of perturbative
variables is required at higher orders to simplify the expression for the
boundary conditions and to expand the variables in terms of linear order
eigenfunctions. Finally we comment on the nonlinear stability of the system.
Some of the tools used can easily be generalized to study nonlinear
perturbations of anti-de Sitter spacetime.


  The adoption of deep learning across various fields has been extensive, yet
there is a lack of focus on evaluating the performance of deep learning
pipelines. Typically, with the increased use of large datasets and complex
models, the training process is run only once and the result is compared to
previous benchmarks. This practice can lead to imprecise comparisons due to the
variance in neural network evaluation metrics, which stems from the inherent
randomness in the training process. Traditional solutions, such as running the
training process multiple times, are often infeasible due to computational
constraints. In this paper, we introduce a novel metric framework, the
Calibrated Loss Metric, designed to address this issue by reducing the variance
present in its conventional counterpart. Consequently, this new metric enhances
the accuracy in detecting effective modeling improvements. Our approach is
substantiated by theoretical justifications and extensive experimental
validations within the context of Deep Click-Through Rate Prediction Models.


  Synchrotrons are powerful and productive in revealing the spatiotemporal
complexities in matter. However, X-ray pulses produced by the synchrotrons are
predetermined in specific patterns and widths, limiting their operational
flexibility and temporal resolution. Here, we introduce the on-chip picosecond
synchrotron pulse shaper that shapes the sub-nm-wavelength hard X-ray pulses at
individual beamlines, flexibly and efficiently beyond the synchrotron pulse
limit. The pulse shaper is developed using the widely available
silicon-on-insulator technology, oscillates in torsional motion at the same
frequency or at harmonics of the storage ring, and manipulates X-ray pulses
through the narrow Bragg peak of the crystalline silicon. Stable pulse
manipulation is achieved by synchronizing the shaper timing to the X-ray timing
using electrostatic closed-loop control. Tunable shaping windows down to 40
$ps$ are demonstrated, allowing X-ray pulse picking, streaking, and slicing in
the majority of worldwide synchrotrons. The compact, on-chip shaper offers a
simple but versatile approach to boost synchrotron operating flexibility and to
investigate structural dynamics from condensed matter to biological systems
beyond the current synchrotron-source limit.


  Although supersymmetry remains the best candidate for solving the electroweak
hierarchy problem, a supersymmetric Higgs boson near 125 GeV requires heavy
scalars, highly-mixed stops, or non-minimal contributions to the Higgs
potential. Extensions of the Standard Model (SM) gauge group provide an
attractive means of raising the Higgs mass through non-decoupling D-term
contributions to the Higgs quartic, but in most cases this correction is
correlated with an enhanced coupling to bottom quarks and tau leptons that is
disfavored by current fits to LHC Higgs data. In this work we demonstrate that
the Higgs mass may be raised by non-decoupling D-terms without such enhanced
couplings if the two supersymmetric Higgs doublets are "chiral", i.e., charged
under different gauge groups at high energies. In this case there is no direct
correlation between the correction to the Higgs mass and its couplings to SM
states, and in general the chiral correction to the Higgs potential undoes the
MSSM preference for enhanced bottom couplings. This raises the prospects for
discovering additional supersymmetric Higgs bosons consistent with the measured
mass and couplings of the observed Higgs.


  We consider a minimal extension of the Standard Model in warped extra
dimensions, with fields propagating in the bulk including a bulk SM-like Higgs
doublet. We show that the Higgs can acquire a non-trivial oscillatory VEV,
strongly localized towards the TeV brane, but such that its value at that brane
could be highly suppressed due to its oscillatory behaviour. Within the minimal
Randall-Sundrum metric background, this oscillatory VEV can alleviate the
bounds coming from oblique precision electroweak parameters, such that the KK
gluon mass can be around 3 TeV (instead of about 8 TeV for the usual
non-oscillatory bulk Higgs). We also discuss the stability of the configuration
as well as the naturalness of the model parameters.


  While a wide range of different, sometimes heterogeneous test coverage
criteria have been proposed, there exists no generic formalism to describe
them, and available test automation tools usually support only a small subset
of them. We introduce a unified specification language, called HTOL, providing
a powerful generic mechanism to define test objectives, which permits encoding
numerous existing criteria and supporting them in a unified way. HTOL comes
with a formal semantics and can express complex requirements over several
executions (using a novel notion of hyperlabels), as well as alternative
requirements or requirements over a whole program execution. A novel
classification of a large class of existing criteria is proposed. Finally, a
coverage measurement tool for HTOL objectives has been implemented. Initial
experiments suggest that the proposed approach is both efficient and practical.


  The anomalous Hall effect in metal-insulator-semiconductor structures having
thin (Ga,Mn)As layers as a channel has been studied in a wide range of Mn and
hole densities changed by the gate electric field. Strong and unanticipated
temperature dependence, including a change of sign, of the anomalous Hall
conductance $\sigma_{xy}$ has been found in samples with the highest Curie
temperatures. For more disordered channels, the scaling relation between
$\sigma_{xy}$ and $\sigma_{xx}$, similar to the one observed previously for
thicker samples, is recovered.


  We present more than 80 new variable stars discovered during the first
observing season of the APACHE survey. APACHE is a project aimed at detecting
extrasolar planets transiting nearby, bright M dwarfs by using an array of
small-aperture telescopes. Despite the fact that the survey is targeted to a
well-defined sample of cool stars, we also reduce and analyze data for all the
detected field stars. Since July 2012 dozens of different stellar fields have
been monitored, leading to the detection of several variables for which we
propose a classification and estimate a period, when a periodicity is evident
in the data. Thanks to the SuperWASP public archive, we have also retrieved and
analyzed photometric data collected by the SWASP survey, which helped us to
refine the classification and the period estimation of many variables found in
the APACHE database. Some of the variables present peculiarities and thus are
discussed separately.


  We present a development of norms and discuss their relationship to
factorization. In earlier work, the first named author introduced the notion of
a normset, which is the image of the norm map. A normset is a monoid with its
own factorization properties. We discuss in several different environments the
relationship between factoring in domains and their respective normsets. We
will also discuss the utility of this notion when it comes to multiplicative
ideal theory.


  I describe a general approach to characterizing cosmological inflation
outside the standard slow-roll approximation, based on the Hamilton-Jacobi
formulation of scalar field dynamics. The basic idea is to view the equation of
state of the scalar field matter as the fundamental dynamical variable, as
opposed to the field value or the expansion rate. I discuss how to formulate
the equations of motion for scalar and tensor fluctuations in situations where
the assumption of slow roll is not valid. I apply the general results to the
simple case of inflation from an ``inverted'' polynomial potential, and to the
more complicated case of hybrid inflation.


  We use the UKIDSS Ultra-Deep Survey, the deepest degree-scale near-infrared
survey to date, to investigate the clustering of star-forming and passive
galaxies to z ~ 3.5. Our new measurements include the first determination of
the clustering for passive galaxies at z > 2, which we achieve using a
cross-correlation technique. We find that passive galaxies are the most
strongly clustered, typically hosted by massive dark matter halos with M_halo >
5 x 10^12 M_sun irrespective of redshift or stellar mass. Our findings are
consistent with models in which a critical halo mass determines the transition
from star-forming to passive galaxies. Star-forming galaxies show no strong
correlation between stellar mass and halo mass, but passive galaxies show
evidence for an anti-correlation; low-mass passive galaxies appear, on average,
to be located in the most massive halos. These results can be understood if the
termination of star formation is most efficient for galaxies of low stellar
mass in very dense environments.


  Currently, Atomic Force Microscopy (AFM) is the most preferred Scanning Probe
Microscopy (SPM) method due to its numerous advantages. However, increasing the
scanning speed and reducing the interaction forces between the probe's tip and
the sample surface are still the two main challenges in AFM. To meet these
challenges, we take advantage of the fact that the lateral movements performed
during an AFM scan is a repetitive motion and propose a Repetitive Controller
(RC) for the z-axis movements of the piezo-scanner. The RC utilizes the profile
of the previous scan line while scanning the current line to achieve a better
scan performance. The results of the scanning experiments performed with our
AFM set-up show that the proposed RC significantly outperforms a conventional
PI controller that is typically used for the same task. The scan error and the
average tapping forces are reduced by 66% and 58%, respectively when the scan
speed is increased by 7-fold.


  The purpose of this paper is to establish universality of the fluctuations of
the largest eigenvalue of some non necessarily Gaussian complex Deformed Wigner
Ensembles. The real model is also considered. Our approach is close to the one
used by A. Soshnikov in the investigations of classical real or complex Wigner
Ensembles. It is based on the computation of moments of traces of high powers
of the random matrices under consideration.


  In this paper, the behavior of scalar multi-agent systems over networks
subject to time-driven jumps. Assuming that all agents communicate through
distinct communication digraphs at jump and flow times, the asymptotic
multi-consensus behavior of the hybrid network is explicitly characterized. The
hybrid multi-consensus is shown to be associated with a suitable partition that
is almost equitable for both the jump and flow communication digraphs. In doing
so, no assumption on the underlying digraphs is introduced. Finally, the
coupling rules making the multi-consensus subspace attractive are established.
Several simulation examples illustrate the theoretical results.


  Suppose that Y is a cyclic cover of projective space branched over a
hyperplane arrangement D, and that U is the complement of the ramification
locus in Y. The first theorem implies that the Beilinson-Hodge conjecture holds
for U if certain multiplicities of D are coprime to the degree of the cover.
For instance this applies when D is reduced with normal crossings. The second
theorem shows that when D has normal crossings and the degree of the cover is a
prime number, the generalized Hodge conjecture holds for any toroidal
resolution of Y. The last section contains some partial extensions to more
general nonabelian covers.


  Multilevel, multiarea, and hierarchically interconnected electrical power
grids confront substantial challenges with the increasing integration of many
volatile energy resources. The traditional isolated operation of interconnected
power grids is uneconomical due to a lack of coordination; it may result in
severe accidents that affect operational safety. However, the centralized
operation of interconnected power grids is impractical, considering the
operational independence and information privacy of each power grid. This paper
proposes a nested decomposition method for the coordinated operation of
hierarchical electrical power grids, which can achieve global optimization by
iterating among upper- and lower-level power grids with exchange of boundary
information alone. During each iteration, a projection function, which embodies
the optimal objective value of a lower-level power grid projected onto its
boundary variable space, is computed with second-order exactness. Thus, the
proposed method can be applied widely to nonlinear continuous optimizations and
can converge much more rapidly than existing decomposition methods. We
conducted numerical tests of coordinated operation examples with a trilevel
power grid that demonstrate the validity and performance of the proposed
method.


  Under suitable conditions, with respect to some property on a random iterated
function system(RIFS), it is shown how the system satisfies in this property
almost surely.


  For most practical applications, quantum algorithms require large resources
in terms of qubit number, much larger than those available with current NISQ
processors. With the network and communication functionalities provided by the
Quantum Internet, Distributed Quantum Computing (DQC) is considered as a
scalable approach for increasing the number of available qubits for
computational tasks. For DQC to be effective and efficient, a quantum compiler
must find the best partitioning for the quantum algorithm and then perform
smart remote operation scheduling to optimize EPR pair consumption. At the same
time, the quantum compiler should also find the best local transformation for
each partition. In this paper we present a modular quantum compilation
framework for DQC that takes into account both network and device constraints
and characteristics. We implemented and tested a quantum compiler based on the
proposed framework with some circuits of interest, such as the VQE and QFT
ones, considering different network topologies, with quantum processors
characterized by heavy hexagon coupling maps. We also devised a strategy for
remote scheduling that can exploit both TeleGate and TeleData operations and
tested the impact of using either only TeleGates or both. The evaluation
results show that TeleData operations may have a positive impact on the number
of consumed EPR pairs, while choosing a more connected network topology helps
reduce the number of layers dedicated to remote operations.


  Shannon defined the mutual information between two variables. We illustrate
why the true mutual information between a variable and the predictions made by
a prediction algorithm is not a suitable measure of prediction quality, but the
apparent Shannon mutual information (ASI) is; indeed it is the unique
prediction quality measure with either of two very different lists of desirable
properties, as previously shown by de Finetti and other authors. However,
estimating the uncertainty of the ASI is a difficult problem, because of long
and non-symmetric heavy tails to the distribution of the individual values of
$j(x,y)=\log\frac{Q_y(x)}{P(x)}$ We propose a Bayesian modelling method for the
distribution of $j(x,y)$, from the posterior distribution of which the
uncertainty in the ASI can be inferred. This method is based on Dirichlet-based
mixtures of skew-Student distributions. We illustrate its use on data from a
Bayesian model for prediction of the recurrence time of prostate cancer. We
believe that this approach is generally appropriate for most problems, where it
is infeasible to derive the explicit distribution of the samples of $j(x,y)$,
though the precise modelling parameters may need adjustment to suit particular
cases.


  We present a differentiable formalism for learning free energies that is
capable of capturing arbitrarily complex model dependencies on coarse-grained
coordinates and finite-temperature response to variation of general system
parameters. This is done by endowing models with explicit dependence on
temperature and parameters and by exploiting exact differential thermodynamic
relationships between the free energy, ensemble averages, and response
properties. Formally, we derive an approach for learning high-dimensional
cumulant generating functions using statistical estimates of their derivatives,
which are observable cumulants of the underlying random variable. The proposed
formalism opens ways to resolve several outstanding challenges in bottom-up
molecular coarse graining dealing with multiple minima and state dependence.
This is realized by using additional differential relationships in the loss
function to significantly improve the learning of free energies, while exactly
preserving the Boltzmann distribution governing the corresponding fine-grain
all-atom system. As an example, we go beyond the standard force-matching
procedure to demonstrate how leveraging the thermodynamic relationship between
free energy and values of ensemble averaged all-atom potential energy improves
the learning efficiency and accuracy of the free energy model. The result is
significantly better sampling statistics of structural distribution functions.
The theoretical framework presented here is demonstrated via implementations in
both kernel-based and neural network machine learning regression methods and
opens new ways to train accurate machine learning models for studying
thermodynamic and response properties of complex molecular systems.


  We investigate the Monte Carlo approach to propagation of experimental
uncertainties within the context of the established "MSTW 2008" global analysis
of parton distribution functions (PDFs) of the proton at next-to-leading order
in the strong coupling. We show that the Monte Carlo approach using replicas of
the original data gives PDF uncertainties in good agreement with the usual
Hessian approach using the standard Delta(chi^2) = 1 criterion, then we explore
potential parameterisation bias by increasing the number of free parameters,
concluding that any parameterisation bias is likely to be small, with the
exception of the valence-quark distributions at low momentum fractions x. We
motivate the need for a larger tolerance, Delta(chi^2) > 1, by making fits to
restricted data sets and idealised consistent or inconsistent pseudodata.
Instead of using data replicas, we alternatively produce PDF sets randomly
distributed according to the covariance matrix of fit parameters including
appropriate tolerance values, then we demonstrate a simpler method to produce
an arbitrary number of random predictions on-the-fly from the existing
eigenvector PDF sets. Finally, as a simple example application, we use Bayesian
reweighting to study the effect of recent LHC data on the lepton charge
asymmetry from W boson decays.


  With the prevalence of the Pretraining-Finetuning paradigm in transfer
learning, the robustness of downstream tasks has become a critical concern. In
this work, we delve into adversarial robustness in transfer learning and reveal
the critical role of initialization, including both the pretrained model and
the linear head. First, we discover the necessity of an adversarially robust
pretrained model. Specifically, we reveal that with a standard pretrained
model, Parameter-Efficient Finetuning (PEFT) methods either fail to be
adversarially robust or continue to exhibit significantly degraded adversarial
robustness on downstream tasks, even with adversarial training during
finetuning. Leveraging a robust pretrained model, surprisingly, we observe that
a simple linear probing can outperform full finetuning and other PEFT methods
with random initialization on certain datasets. We further identify that linear
probing excels in preserving robustness from the robust pretraining. Based on
this, we propose Robust Linear Initialization (RoLI) for adversarial
finetuning, which initializes the linear head with the weights obtained by
adversarial linear probing to maximally inherit the robustness from
pretraining. Across five different image classification datasets, we
demonstrate the effectiveness of RoLI and achieve new state-of-the-art results.
Our code is available at \url{https://github.com/DongXzz/RoLI}.


  We find the holographic dual to the three classes of superconformal Janus
interfaces in $\mathcal{N}=4$ SYM that preserve three-dimensional
$\mathcal{N}=4$, $\mathcal{N}=2$, and $\mathcal{N}=1$ supersymmetry. The
solutions are constructed in five-dimensional SO(6) maximal gauged supergravity
and are then uplifted to type IIB supergravity. Corresponding to each of the
three classes of Janus solutions, there are also AdS$_4\times S^1\times S^5$
J-fold backgrounds. These J-folds have a non-trivial SL$(2,\mathbb{Z})$
monodromy for the axio-dilaton on the $S^1$ and are dual to three-dimensional
superconformal field theories.


  Accurate approximation of a real-valued function depends on two aspects of
the available data: the density of inputs within the domain of interest and the
variation of the outputs over that domain. There are few methods for assessing
whether the density of inputs is \textit{sufficient} to identify the relevant
variations in outputs -- i.e., the "geometric scale" of the function -- despite
the fact that sampling density is closely tied to the success or failure of an
approximation method. In this paper, we introduce a general purpose,
computational approach to detecting the geometric scale of real-valued
functions over a fixed domain using a deterministic interpolation technique
from computational geometry. Our algorithm is based on the observation that a
sequence of piecewise linear interpolants will converge to a continuous
function at a quadratic rate (in $L^2$ norm) if and only if the data are
sampled densely enough to distinguish the feature from noise. We present
numerical experiments demonstrating how our method can identify feature scale,
estimate uncertainty in feature scale, and assess the sampling density for
fixed (i.e. static) datasets of input-output pairs. In addition, we include
analytical results in support of our numerical findings and will release
lightweight code that can be adapted for use in a variety of data science
settings.


  To foster research and facilitate fair comparisons among recently proposed
pathloss radio map prediction methods, we have launched the ICASSP 2023 First
Pathloss Radio Map Prediction Challenge. In this short overview paper, we
briefly describe the pathloss prediction problem, the provided datasets, the
challenge task and the challenge evaluation methodology. Finally, we present
the results of the challenge.


  Recent evidence for pentaquark baryons in the channels $\Xi^-\pi^-$,
$\Xi^-\pi^+$ and their anti-particles claimed by the NA49 collaboration is
critically confronted with the vast amount of existing data on $\Xi$
spectroscopy which was accumulated over the past decades. It is shown that the
claim is at least partially inconsistent with these data. In addition two
further exotic channels of the pentaquark type available in the NA49 data are
investigated. It is argued that this study leads to internal inconsistency with
the purported signals.


  We consider unitary analogs of $1-$dimensional Anderson models on $l^2(\Z)$
defined by the product $U_\omega=D_\omega S$ where $S$ is a deterministic
unitary and $D_\omega$ is a diagonal matrix of i.i.d. random phases. The
operator $S$ is an absolutely continuous band matrix which depends on a
parameter controlling the size of its off-diagonal elements. We prove that the
spectrum of $U_\omega$ is pure point almost surely for all values of the
parameter of $S$. We provide similar results for unitary operators defined on
$l^2(\N)$ together with an application to orthogonal polynomials on the unit
circle. We get almost sure localization for polynomials characterized by
Verblunski coefficients of constant modulus and correlated random phases.


  Natural language understanding (NLU) and natural language generation (NLG)
are two fundamental and related tasks in building task-oriented dialogue
systems with opposite objectives: NLU tackles the transformation from natural
language to formal representations, whereas NLG does the reverse. A key to
success in either task is parallel training data which is expensive to obtain
at a large scale. In this work, we propose a generative model which couples NLU
and NLG through a shared latent variable. This approach allows us to explore
both spaces of natural language and formal representations, and facilitates
information sharing through the latent space to eventually benefit NLU and NLG.
Our model achieves state-of-the-art performance on two dialogue datasets with
both flat and tree-structured formal representations. We also show that the
model can be trained in a semi-supervised fashion by utilising unlabelled data
to boost its performance.


  As an exoplanet transits its host star, some of the light from the star is
absorbed by the atoms and molecules in the planet's atmosphere, causing the
planet to seem bigger; plotting the planet's observed size as a function of the
wavelength of the light produces a transmission spectrum. Measuring the tiny
variations in the transmission spectrum, together with atmospheric modelling,
then gives clues to the properties of the exoplanet's atmosphere. Chemical
species composed of light elements$-$such as hydrogen, oxygen, carbon, sodium
and potassium$-$have in this way been detected in the atmospheres of several
hot giant exoplanets, but molecules composed of heavier elements have thus far
proved elusive. Nonetheless, it has been predicted that metal oxides such as
titanium oxide (TiO) and vanadium oxide occur in the observable regions of the
very hottest exoplanetary atmospheres, causing thermal inversions on the
dayside. Here we report the detection of TiO in the atmosphere of the
hot-Jupiter planet WASP-19b. Our combined spectrum, with its wide spectral
coverage, reveals the presence of TiO (to a confidence level of 7.7{\sigma}), a
strongly scattering haze (7.4{\sigma}) and sodium (3.4{\sigma}), and confirms
the presence of water (7.9{\sigma}) in the atmosphere.


  High resolution 7 mm observations of the W49N massive star forming region
have detected recombination line emission from the individual ultracompact (UC)
HII regions on 50 milliarcsecond (600 AU) scales. These line observations,
combined with multifrequency, high-resolution continuum imaging of the region
at 7 mm (VLA) and at 3 mm and 1 mm (BIMA), indicate that five to seven of the
eighteen ultracompact sources in W49N are broad recombination line objects
(BRLOs) as described by Jaffe & Martin-Pintado (1999). BRLOs have both broad
radio recombination lines ($\Delta$V$>$60 \kms) and rising spectra
(S$_{\nu}\sim\nu^{\alpha}$), with $\alpha$ values greater than 0.4. The broad
line widths of the H52$\alpha$ line are probably related to motions in the
ionized gas rather than pressure broadening. A number of models have been
proposed to explain the long lifetime of UC HII regions, including the
photoevaporated disk model proposed by Hollenbach et al. (1994). This model can
also explain the broad lines, rising spectra and bipolar morphologies of some
sources. We suggest$-$based on line and continuum observations as well as
source morphology$-$that in a subset of the W49N ultracompact sources we may be
observing ionized winds that arise from circumstellar disks.


  We discuss the timescales for alignment of black hole and accretion disc
spins in the context of binary systems. We show that for black holes that are
formed with substantial angular momentum, the alignment timescales are likely
to be at least a substantial fraction of the systems' lifetimes. This result
explains the observed misalignment of the disc and the jet in the microquasar
GRO J 1655-40 and in SAX J 1819-2525 as being likely due to the
Bardeen-Petterson effect. We discuss the implications of these results on the
mass estimate for GRS 1915+105, which has assumed the jet is perpendicular to
the orbital plane of the system and may hence be an underestimate. We show that
the timescales for the spin alignment in Cygnus X-3 are consistent with the
likely misalignment of disc and jet in that system, and that this is suggested
by the observational data.


  We suggest to use the common appearance of voids with a scale of $5000 \kms$
in the galaxy distribution to estimate the power spectrum on this scale. We use
a simple model for a gravitational formation of voids and we compare the
results with the matter fluctuations as constrained by the CMBR observations of
COBE. We find that a power spectrum $P(k)\propto k^n$ with $n \approx 1.25$ is
compatible both with COBE and with gravitational growth of large voids in an
$\Omega=1$ universe. A Harrison-Zel'dovich spectrum, $n=1$, normalized to
produce the observed CMBR fluctuations, does not have enough power for
gravitational growth of voids with a diameter of $5000 \kms$ in an $\Omega=1$
Universe. Such a spectrum would be compatible if (i) void diameters are smaller
($3500 \kms$), the voids are shallower or if the voids are rare (we assume that
the universe is void filled); (ii) $\Omega < 1$ i.e. the Universe is open;
(iii) galaxies do not trace matter on very large scale or if (iv) the voids do
not grow gravitationally.


  The IceCube Neutrino Observatory at the geographic South Pole is, with its
surface and in-ice detectors, used for both neutrino and cosmic-ray physics.
The surface array, named IceTop, consists of ice-Cherenkov tanks grouped in 81
pairs spanning a 1 km$^2$ area. An enhancement of the surface array, composed
of elevated scintillation panels and radio antennas, was designed over the last
years in order to increase the scientific capabilities of IceTop. The surface
radio antennas, in particular, will be able to reconstruct $X_\mathrm{max}$, an
observable widely used to determine the mass composition of cosmic rays. A
complete prototype station of this enhanced array was deployed in the Austral
summer of 2019/20 at the South Pole. This station comprises three antennas and
eight scintillation panels, arranged in a three-arms star shape. The nominal
frequency band of the radio antennas is 70 to 350 MHz.
  In this work, we use a state-of-the-art reconstruction method in which
observed events are compared directly to CoREAS simulations to obtain an
estimation of the air-shower variables, in particular, energy and
$X_\mathrm{max}$. We will show the results in this unique frequency band using
the three prototype antennas.


  We propose a correction of the standard Big Bang nucleosynthesis (BBN)
scenario to resolve the primordial lithium problem by considering a possibility
that the primordial plasma can deviate from the ideal state. In the standard
BBN, the primordial plasma is assumed to be ideal, with particles and photons
satisfying the Maxwell-Boltzmann and Planck distribution, respectively. We
suggest that this assumption of the primordial plasma being ideal might
oversimplify the early Universe and cause the lithium problem. We find that
deviation of photon distribution from the Planck distribution, which is
parameterised with the help of Tsallis statistics, can resolve the primordial
lithium problem when the particle distributions of the primordial plasma still
follow the MaxwellBoltzmann distribution. We discuss how the primordial plasma
can be weakly non-ideal in this specific fashion and its effects on the cosmic
evolution.


  Due to Variety, Web data come in many different structures and formats, with
HTML tables and REST APIs (e.g., social media APIs) being among the most
popular ones. A big subset of Web data is also characterised by Velocity, as
data gets frequently updated so that consumers can obtain the most up-to-date
version of the respective datasets. At the moment, though, these data sources
are not effectively supported by Semantic Web tools. To address variety and
velocity, we propose Ontop4theWeb, a system that maps Web data of various
formats into virtual RDF triples, thus allowing for querying them on-the-fly
without materializing them as RDF. We demonstrate how Ontop4theWeb can use
SPARQL to uniformly query popular, but heterogeneous Web data sources, like
HTML tables and Web APIs. We showcase our approach in a number of use cases,
such as Twitter, Foursquare, Yelp and HTML tables. We carried out a thorough
experimental evaluation which verifies the high efficiency of our framework,
which goes beyond the current state-of-the-art in this area, in terms of both
functionality and performance.


  We present revised basic stellar astrophysical parameters: masses,
luminosities, ages and radii for 342 stars from PennState-Toru\'n Centre for
Astronomy Planet Search. Atmospheric parameters for 327 stars are available
from Zieli\'nski (2012), for the remaining 15 objects we present also
spectroscopic atmospheric parameters: effective temperatures, surface gravities
and iron abundances. Spectroscopic atmospheric parameters were obtained with a
standard spectroscopic analysis procedure, using ARES (Sousa, 2007) and MOOG
(Sneden, 1973) or TGVIT (Takeda, 2005) codes. To refine stellar masses, ages
and luminosities we applied a Bayesian method based on Jorgensen (2005)
formalism, modified by da Silva (2006). The revised stellar masses for 342
stars and their uncertainties are generally lower than those presented in
Zieli\'nski (2012). Atmospheric parameters for 13 objects are determined here
for the first time.


  We present a new outer bound for the sum capacity of general multi-unicast
deterministic networks. Intuitively, this bound can be understood as applying
the cut-set bound to concatenated copies of the original network with a special
restriction on the allowed transmit signal distributions. We first study
applications to finite-field networks, where we obtain a general outer-bound
expression in terms of ranks of the transfer matrices. We then show that, even
though our outer bound is for deterministic networks, a recent result relating
the capacity of AWGN KxKxK networks and the capacity of a deterministic
counterpart allows us to establish an outer bound to the DoF of KxKxK wireless
networks with general connectivity. This bound is tight in the case of the
"adjacent-cell interference" topology, and yields graph-theoretic necessary and
sufficient conditions for K DoF to be achievable in general topologies.


  Patients resuscitated from cardiac arrest who enter a coma are at high risk
of death. Forecasting neurological outcomes of these patients (the task of
neurological prognostication) could help with treatment decisions. In this
paper, we propose, to the best of our knowledge, the first dynamic framework
for neurological prognostication of post-cardiac-arrest comatose patients using
EEG data: our framework makes predictions for a patient over time as more EEG
data become available, and different training patients' available EEG time
series could vary in length. Predictions are phrased in terms of either
time-to-event outcomes (time-to-awakening or time-to-death) or as the patient's
probability of awakening or of dying across multiple time horizons. Our
framework uses any dynamic survival analysis model that supports competing
risks in the form of estimating patient-level cumulative incidence functions.
We consider three competing risks as to what happens first to a patient:
awakening, being withdrawn from life-sustaining therapies (and thus
deterministically dying), or dying (by other causes). We demonstrate our
framework by benchmarking three existing dynamic survival analysis models that
support competing risks on a real dataset of 922 patients. Our main
experimental findings are that: (1) the classical Fine and Gray model which
only uses a patient's static features and summary statistics from the patient's
latest hour's worth of EEG data is highly competitive, achieving accuracy
scores as high as the recently developed Dynamic-DeepHit model that uses
substantially more of the patient's EEG data; and (2) in an ablation study, we
show that our choice of modeling three competing risks results in a model that
is at least as accurate while learning more information than simpler models
(using two competing risks or a standard survival analysis setup with no
competing risks).


  We theoretically investigate effects of quantum fluctuations on superfluid
spin transport through easy-plane quantum antiferromagnetic spin chains in the
large-spin limit. Quantum fluctuations give rise to decaying of spin
supercurrent by unwinding the magnetic order parameter within the easy plane,
which is referred to as phase slips. We show that the topological term in the
nonlinear sigma model for the spin chains qualitatively differentiates decaying
rate of the spin supercurrent between integer spin and half-odd-integer spin
chains. An experimental setup for a magnetoelectric circuit is proposed, in
which the dependence of the decaying rate on constituent spins can be verified
by measuring nonlocal magnetoresistance.


  In this work, we have considered the spherically symmetric stellar system in
the contexts of Rastall-Rainbow gravity theory in presence of isotropic fluid
source with electromagnetic field. The Einstein-Maxwell's field equations have
been written in the framework of Rastall-Rainbow gravity. The gravastar
consists of three regions: interior region, thin shell region and exterior
region. In the interior region, the gravastar follows the equation of sate
(EoS) $p=-\rho$ and we have found the solutions of all physical quantities like
energy density, pressure, electric field, charge density, gravitational mass
and metric coefficients. In the exterior region, we have obtained the exterior
Riessner-Nordstrom solution for vacuum model ($p=\rho=0$). Since in the shell
region, the fluid source follows the EoS $p=\rho$ (ultra-stiff fluid) and the
thickness of the shell of the gravastar is infinitesimal, so by the
approximation $h~(\equiv A^{-1})\ll 1$, we have found the analytical solutions
within the thin shell. The physical quantities like the proper length of the
thin shell, entropy and energy content inside the thin shell of the charged
gravastar have been computed and we have shown that they are directly
proportional to the proper thickness of the shell ($\epsilon$) due to the
approximation ($\epsilon\ll 1$). The physical parameters significantly depend
on the Rastall parameter and Rainbow function. Next we have studied the
matching between the surfaces of interior and exterior regions of the charged
gravastar and using the matching conditions, the surface energy density and the
surface pressure have been obtained. Also the equation of state parameter on
the surface, mass of the thin shell, mass of the gravastar have been obtained.
Finally, we have explored the stable regions of the charged gravastar in
Rastall-Rainbow gravity.


  Based on the algebraic equation of motion (AEOM) method, we investigate the
transport properties of a quantum dot. We obtain an analytical expression for
the dot electron single-particle Green's function, and based on this
expression, we plot the dot electron density of states under different biases.
We find that the Kondo resonance splits and is suppressed as the bias is
increased. In addition, we calculate the differential conductance of the dot
and obtain the zero-bias Kondo resonance at different temperatures, which is
found to be suppressed as the temperature is increased.


  We study 4d N=1 supersymmetric theories of class S_k, obtained from flux
compactifications on a Riemann surface of 6d (1,0) conformal theories
describing the low energy physics on a stack of M5 branes probing a Z_k
singularity. We conjecture that the protected spectrum of class S_k theories
contains a freely generated ring, generalizing the Coulomb branch of the N=2
theories. We derive this by examining a limit of the supersymmetric index of 4d
N=1 class S_k theories. The limit generalizes the Coulomb limit of N=2
theories, which coincides with the case of k=1 for a particular choice of flux.
We conjecture a general simple formula for the index in the aforementioned
limit.


  This expository article is an introduction to the adjoint orbits of complex
semisimple groups, primarily in the algebro-geometric and Lie-theoretic
contexts, and with a pronounced emphasis on the properties of semisimple and
nilpotent orbits. It is intended to build a foundation for more specialized
settings in which adjoint orbits feature prominently (ex. hyperk\"{a}hler
geometry, Landau-Ginzburg models, and the theory of symplectic singularities).
Also included are a few arguments and observations that, to the author's
knowledge, have not yet appeared in the research literature.


  The academic literature of social sciences records human civilization and
studies human social problems. With its large-scale growth, the ways to quickly
find existing research on relevant issues have become an urgent demand for
researchers. Previous studies, such as SciBERT, have shown that pre-training
using domain-specific texts can improve the performance of natural language
processing tasks. However, the pre-trained language model for social sciences
is not available so far. In light of this, the present research proposes a
pre-trained model based on the abstracts published in the Social Science
Citation Index (SSCI) journals. The models, which are available on GitHub
(https://github.com/S-T-Full-Text-Knowledge-Mining/SSCI-BERT), show excellent
performance on discipline classification, abstract structure-function
recognition, and named entity recognition tasks with the social sciences
literature.


  Biological neural networks are notoriously hard to model due to their
stochastic behavior and high dimensionality. We tackle this problem by
constructing a dynamical model of both the expectations and covariances of the
fractions of active and refractory neurons in the network's populations. We do
so by describing the evolution of the states of individual neurons with a
continuous-time Markov chain, from which we formally derive a low-dimensional
dynamical system. This is done by solving a moment closure problem in a way
that is compatible with the nonlinearity and boundedness of the activation
function. Our dynamical system captures the behavior of the high-dimensional
stochastic model even in cases where the mean-field approximation fails to do
so. Taking into account the second-order moments modifies the solutions that
would be obtained with the mean-field approximation, and can lead to the
appearance or disappearance of fixed points and limit cycles. We moreover
perform numerical experiments where the mean-field approximation leads to
periodically oscillating solutions, while the solutions of the second-order
model can be interpreted as an average taken over many realizations of the
stochastic model. Altogether, our results highlight the importance of including
higher moments when studying stochastic networks and deepen our understanding
of correlated neuronal activity.


  Denoising is omnipresent in image processing. It is usually addressed with
algorithms relying on a set of hyperparameters that control the quality of the
recovered image. Manual tuning of those parameters can be a daunting task,
which calls for the development of automatic tuning methods. Given a denoising
algorithm, the best set of parameters is the one that minimizes the error
between denoised and ground-truth images. Clearly, this ideal approach is
unrealistic, as the ground-truth images are unknown in practice. In this work,
we propose unsupervised cost functions -- i.e., that only require the noisy
image -- that allow us to reach this ideal gold standard performance.
Specifically, the proposed approach makes it possible to obtain an average PSNR
output within less than 1% of the best achievable PSNR.


  Accelerated expansion of the Universe prompted searches of modified gravity
theory beyond general relativity, instead of adding a mysterious dark energy
component with exotic physical properties. One such alternative gravity
approach is metric-affine Palatini $f(\hat{R})$ theory. By now routine
gravitational wave detections have opened a promising avenue of searching for
modified gravity effects. Future expected cases of strong lensing of
gravitational waves will enhance this opportunity further. In this paper, we
present a systematic study of the propagation and gravitational lensing of
gravitational waves in Palatini $f(\hat R)$ gravity and compare it with general
relativity. Using the WKB approximation we explore the geometric-optical limit
of lensing and derive the corrections to the measured luminosity distance of
the gravitational source. In addition, we study the lensing by the Singular
Isothermal Sphere lens model and show that Palatini $f(\hat{R})$ modifies the
lensing potential and hence the deflection angle. Then we show that the lens
model and chosen theory of gravity influences the rotation of the gravitational
wave polarization plane through the deflection angle. To be more specific we
discuss the $f(\hat R)=\hat R+\alpha \hat R^2$ gravity theory and find that the
modifications comparing to general relativity are negligible if the upper bound
of $\alpha \sim 10^{9} \, $m$^2$ suggested in the literature is adopted.
However, this bound is not firmly established and can be updated in the future.
Therefore, the results we obtained could be valuable for further metric-affine
gravity vs. general relativity tests involving lensing of gravitational waves
and comparison of luminosity distances measured from electromagnetic and
gravitational wave sources.


  We describe a novel iterative strategy for Kohn-Sham density functional
theory calculations aimed at large systems (> 1000 electrons), applicable to
metals and insulators alike. In lieu of explicit diagonalization of the
Kohn-Sham Hamiltonian on every self-consistent field (SCF) iteration, we employ
a two-level Chebyshev polynomial filter based complementary subspace strategy
to: 1) compute a set of vectors that span the occupied subspace of the
Hamiltonian; 2) reduce subspace diagonalization to just partially occupied
states; and 3) obtain those states in an efficient, scalable manner via an
inner Chebyshev-filter iteration. By reducing the necessary computation to just
partially occupied states, and obtaining these through an inner Chebyshev
iteration, our approach reduces the cost of large metallic calculations
significantly, while eliminating subspace diagonalization for insulating
systems altogether. We describe the implementation of the method within the
framework of the Discontinuous Galerkin (DG) electronic structure method and
show that this results in a computational scheme that can effectively tackle
bulk and nano systems containing tens of thousands of electrons, with chemical
accuracy, within a few minutes or less of wall clock time per SCF iteration on
large-scale computing platforms. We anticipate that our method will be
instrumental in pushing the envelope of large-scale ab initio molecular
dynamics. As a demonstration of this, we simulate a bulk silicon system
containing 8,000 atoms at finite temperature, and obtain an average SCF step
wall time of 51 seconds on 34,560 processors; thus allowing us to carry out 1.0
ps of ab initio molecular dynamics in approximately 28 hours (of wall time).


  Algebraic statistics uses tools from algebra (especially from multilinear
algebra, commutative algebra and computational algebra), geometry and
combinatorics to provide insight into knotty problems in mathematical
statistics. In this survey we illustrate this on three problems related to
networks, namely network models for relational data, causal structure discovery
and phylogenetics. For each problem we give an overview of recent results in
algebraic statistics with emphasis on the statistical achievements made
possible by these tools and their practical relevance for applications to other
scientific disciplines.


  A Brain-Computer Interface (BCI) acquires brain signals, analyzes and
translates them into commands that are relayed to actuation devices for
carrying out desired actions. With the widespread connectivity of everyday
devices realized by the advent of the Internet of Things (IoT), BCI can empower
individuals to directly control objects such as smart home appliances or
assistive robots, directly via their thoughts. However, realization of this
vision is faced with a number of challenges, most importantly being the issue
of accurately interpreting the intent of the individual from the raw brain
signals that are often of low fidelity and subject to noise. Moreover,
pre-processing brain signals and the subsequent feature engineering are both
time-consuming and highly reliant on human domain expertise. To address the
aforementioned issues, in this paper, we propose a unified deep learning based
framework that enables effective human-thing cognitive interactivity in order
to bridge individuals and IoT objects. We design a reinforcement learning based
Selective Attention Mechanism (SAM) to discover the distinctive features from
the input brain signals. In addition, we propose a modified Long Short-Term
Memory (LSTM) to distinguish the inter-dimensional information forwarded from
the SAM. To evaluate the efficiency of the proposed framework, we conduct
extensive real-world experiments and demonstrate that our model outperforms a
number of competitive state-of-the-art baselines. Two practical real-time
human-thing cognitive interaction applications are presented to validate the
feasibility of our approach.


  The aim of this paper is to extend the theory of standard subalgebras of
finite dimensional simple Lie algebras to infinite dimensional Lie algebras. We
construct and characterize a class of standard subalgebras of affine Kac-Moody
algebra.


  Investigating the code fragments of code clones detected by code clone
detection tools is a time-consuming task, especially when a large number of
reference source files are available. This paper proposes (i) a method for
clustering a clone class, which is detected by code clone detection tools using
syntactic similarity, based on topic similarity by considering its code
fragments as sequences of words and (ii) a method for assigning short tags to
clusters of the clustering result. We also report an experiment of applying the
proposed method to packages of an open source operating system.


  We introduce a method to obtain the envelopes of eccentric orbits in axially
symmetric potentials, $\Phi(R,z)$, endowed with $z$-symmetry of reflection. By
making the transformation $z\rightarrow a+\sqrt{a^{2}+ z^{2}}$, with $a>0$, we
compute the resulting mass density, referred here as the \emph{effective
density} $\rho_{\rm ef}(R,z;a)$, in order to calculate the envelopes $Z(R)$ of
orbits in the meridional plane $(R,z)$. We find that they obey the approximated
formula $Z(R)\propto [\Sigma_{\rm ef}(R;a\approx 0)]^{-1/3}$, where
$\Sigma_{\rm ef}(R;a)$ is the integrated surface density associated with
$\rho_{\rm ef}(R,z;a)$. As examples we consider the dynamics in two potentials:
the monopole plus quadrupole and the Kalnajs disc.


  We use the radio axis as an indicator of the orientation of the obscuring
torus in Seyfert galaxies, and analyze the difference between the position
angles of extended radio structures and host galaxy major axis of Seyfert 1 and
Seyfert 2 galaxies. We find that Seyfert 1's are less likely to have extended
radio structures along the host galaxy major axis, while Seyfert 2's have these
structures distributed in most directions. We also find a zone of avoidance in
the distribution of position angles; both Seyfert 1's and Seyfert 2's seem to
avoid close alignment between the radio axis and the host galaxy plane axis.
These results are analyzed from the point of view of a model in which Seyfert
1's have their obscuring torus axis aligned preferentially along the host
galaxy disk axis, and Seyfert 2's have their torus axis laying at an
intermediate angle between the galaxy disk and its axis.


  There is some experimental evidence that some stars are older than the
Universe in General Relativity based cosmology. In TGD based cosmology the
paradox has explanation. Photons can be either topologically condensed on
background spacetime surface or in 'vapour phase' that is progate in
$M^4_+\times CP_2$ as small surfaces. The time for propagation from A to B is
in general larger in condensate than in vapour phase. In principle observer
detects from a given astrophysical object both vapour phase and condensate
photons, vapour phase photons being emitted later than condensate photons.
Therefore the erraneous identification of vapour phase photons as condensate
photons leads to an over estimate for the age of the star and star can look
older than the Universe. The Hubble constant for vapour phase photons is that
associated with $M^4_+$ and smaller than the Hubble constant of matter
dominated cosmology. This could explain the measured two widely different
values of Hubble constant if smaller Hubble constant corresponds to the Hubble
constant of the future light cone $M^4_+$. The ratio of propagation velocities
of vapour phase and condensate photons equals to ratio of the two Hubble
constants, which in turn is depends on the ratio of mass density and critical
mass density, only. Anomalously large redshifts are possible since vapour phase
photons can come also from region outside the horizon.


  We explore the emergence of many-body physics from quantum mechanics via
spontaneous symmetry breaking. To this end, we study potentials which are
functionals on the space of Hamiltonians enjoying an unstable critical point
corresponding to a random quantum mechanical system (the Gaussian unitary
ensemble), but also less symmetrical local minima corresponding to interacting
systems at the level of operators.


  In this paper, we introduce regularized stochastic team problems. Under mild
assumptions, we prove that there exists an unique fixed point of the best
response operator, where this unique fixed point is the optimal regularized
team decision rule. Then, we establish an asynchronous distributed algorithm to
compute this optimal strategy. We also provide a bound that shows how the
optimal regularized team decision rule performs in the original stochastic team
problem.


  Influence diagram is a graphical representation of belief networks with
uncertainty. This article studies the structural properties of a probabilistic
model in an influence diagram. In particular, structural controllability
theorems and structural observability theorems are developed and algorithms are
formulated. Controllability and observability are fundamental concepts in
dynamic systems (Luenberger 1979). Controllability corresponds to the ability
to control a system while observability analyzes the inferability of its
variables. Both properties can be determined by the ranks of the system
matrices. Structural controllability and observability, on the other hand,
analyze the property of a system with its structure only, without the specific
knowledge of the values of its elements (tin 1974, Shields and Pearson 1976).
The structural analysis explores the connection between the structure of a
model and the functional dependence among its elements. It is useful in
comprehending problem and formulating solution by challenging the underlying
intuitions and detecting inconsistency in a model. This type of qualitative
reasoning can sometimes provide insight even when there is insufficient
numerical information in a model.


  When comparing measurements to numerical simulations of moisture transfer
through porous materials a rush of the experimental moisture front is commonly
observed in several works shown in the literature, with transient models that
consider only the diffusion process. Thus, to overcome the discrepancies
between the experimental and the numerical models, this paper proposes to
include the moisture advection transfer in the governing equation. To solve the
advection-diffusion differential equation, it is first proposed two efficient
numerical schemes and their efficiencies are investigated for both linear and
nonlinear cases. The first scheme, Scharfetter-Gummel (SG), presents a
Courant-Friedrichs-Lewy (CFL) condition but is more accurate and faster than
the second scheme, the well-known Crank-Nicolson approach. Furthermore, the SG
scheme has the advantages of being well-balanced and asymptotically preserved.
Then, to conclude, results of the convective moisture transfer problem obtained
with the SG numerical scheme are compared to experimental data from the
literature. The inclusion of an advective term in the model may clearly lead to
better results than purely diffusive models.


  We have computed ensembles of complete spectra of the staggered Dirac
operator using four-dimensional SU(2) gauge fields, both in the quenched
approximation and with dynamical fermions. To identify universal features in
the Dirac spectrum, we compare the lattice data with predictions from chiral
random matrix theory for the distribution of the low-lying eigenvalues. Good
agreement is found up to some limiting energy, the so-called Thouless energy,
above which random matrix theory no longer applies. We determine the dependence
of the Thouless energy on the simulation parameters using the scalar
susceptibility and the number variance.


  We developed a computer code for the thermodynamic quantum Fokker--Planck
equations (T-QFPE), derived from a thermodynamic system-bath model. This model
consists of an anharmonic subsystem coupled to multiple Ohmic baths at
different temperatures, which are connected to or disconnected from the
subsystem as a function of time. The code numerically integrates the T-QFPE and
their classical expression to simulate isothermal, isentropic, thermostatic,
and entropic processes in both quantum and classical cases. The accuracy of the
results was verified by comparing the analytical solutions of the Brownian
oscillator. Additionally, we illustrated a breakdown of the Markovian
Lindblad-master equation in the pure quantum regime. As a demonstration, we
simulated a thermostatic Stirling engine employed to develop non--equilibrium
thermodynamics [S. Koyanagi and Y. Tanimura,
https://doi.org/10.48550/arXiv.2405.17791] under quasi-static conditions. The
quasi-static thermodynamic potentials, described as intensive and extensive
variables, were depicted as work diagrams. In the classical case, the work done
by the external field is independent of the system-bath coupling strength. In
contrast, in the quantum case, the work decreases as the coupling strength
increases due to quantum entanglement between the subsystem and bath. The codes
were developed for multicore processors using Open multiprocessing (OpenMP) and
for graphics processing units (GPU) using the Compute United Device
Architecture (CUDA). These codes are provided as supplementary materials.


  We consider open, oriented 3-manifolds which are infinite connected sums of
closed 3-manifolds. We introduce some topological invariants for these
manifolds and obtain a classification in the case where there are only finitely
many summands up to diffeomorphism. This result encompasses both the
Kneser-Milnor Prime Decomposition Theorem for closed 3-manifolds and the
Ker{\'e}kj{\'a}rt{\'o}-Richards classification theorem for open surfaces.