  Combination of the power spectrum and bispectrum is a powerful way of
breaking degeneracies between galaxy bias and cosmological parameters, enabling
us to maximize the constraining power from galaxy surveys. Recent cosmological
constraints treat the power spectrum and bispectrum on an uneven footing: they
include one-loop bias corrections for the power spectrum but not the
bispectrum. To bridge this gap, we develop the galaxy bias description up to
fourth order in perturbation theory, conveniently expressed through a basis of
Galilean invariants that clearly split contributions that are local and
nonlocal in the second derivatives of the linear gravitational potential. In
addition, we consider relevant contributions from short-range nonlocality
(higher-derivative terms), stress-tensor corrections and stochasticity. To
sidestep the usual renormalization of bias parameters that complicates
predictions beyond leading order, we recast the bias expansion in terms of
multipoint propagators, which take a simple form in our split-basis with loop
corrections depending only on bias parameters corresponding to nonlocal
operators. We show how to take advantage of Galilean invariance to compute the
time evolution of bias and present results for the fourth-order parameters for
the first time. We also discuss the possibilities of reducing the bias
parameter space by using the evolution of bias and exploiting degeneracies
between various bias contributions in the large-scale limit. Our baseline model
allows to verify these simplifications for any application to large-scale
structure data sets.


  The traction force of a kite can be used to drive a cyclic motion for
extracting wind energy from the atmosphere. This paper presents a novel
quasi-steady modelling framework for predicting the power generated over a full
pumping cycle. The cycle is divided into traction, retraction and transition
phases, each described by an individual set of analytic equations. The effect
of gravity on the airborne system components is included in the framework. A
trade-off is made between modelling accuracy and computation speed such that
the model is specifically useful for system optimisation and scaling in
economic feasibility studies. Simulation results are compared to experimental
measurements of a 20 kW kite power system operated up to a tether length of 720
m. Simulation and experiment agree reasonably well, both for moderate and for
strong wind conditions, indicating that the effect of gravity has to be taken
into account for a predictive performance simulation.


  We present an online approach to efficiently and simultaneously detect and
track the 2D pose of multiple people in a video sequence. We build upon Part
Affinity Field (PAF) representation designed for static images, and propose an
architecture that can encode and predict Spatio-Temporal Affinity Fields (STAF)
across a video sequence. In particular, we propose a novel temporal topology
cross-linked across limbs which can consistently handle body motions of a wide
range of magnitudes. Additionally, we make the overall approach recurrent in
nature, where the network ingests STAF heatmaps from previous frames and
estimates those for the current frame. Our approach uses only online inference
and tracking, and is currently the fastest and the most accurate bottom-up
approach that is runtime invariant to the number of people in the scene and
accuracy invariant to input frame rate of camera. Running at $\sim$30 fps on a
single GPU at single scale, it achieves highly competitive results on the
PoseTrack benchmarks.


  Diffusion of knowledge is expected to be huge when agents are open minded.
The report concerns a more difficult diffusion case when communities are made
of stubborn agents. Communities having markedly different opinions are for
example the Neocreationist and Intelligent Design Proponents (IDP), on one
hand, and the Darwinian Evolution Defenders (DED), on the other hand. The case
of knowledge diffusion within such communities is studied here on a network
based on an adjacency matrix built from time ordered selected quotations of
agents, whence for inter- and intra-communities. The network is intrinsically
directed and not necessarily reciprocal. Thus, the adjacency matrices have
complex eigenvalues, the eigenvectors present complex components. A
quantification of the slow-down or speed-up effects of information diffusion in
such temporal networks, with non-Markovian contact sequences, can be made by
comparing the real time dependent (directed) network to its counterpart, the
time aggregated (undirected) network, - which has real eigenvalues. In order to
do so, small world networks which both contain an $odd$ number of nodes are
studied and compared to similar networks with an $even$ number of nodes.
  It is found that (i) the diffusion of knowledge is more difficult on the
largest networks, (ii) the network size influences the slowing-down or
speeding-up diffusion process. Interestingly, it is observed that (iii) the
diffusion of knowledge is slower in IDP and faster in DED communities. It is
suggested that the finding can be "rationalized", if some "scientific quality"
and "publication habit" is attributed to the agents, as common sense would
guess. This finding offers some opening discussion toward tying scientific
knowledge to belief.


  Recently, it has been claimed that the back reaction of vacuum polarization
on a black hole spacetime naturally regularizes infinities in the black hole
entropy. We examine the back reaction calculation and find no such
short-distance cut-off,in contradiction with these recent claims. Moreover, the
intuitive expectation that the perturbative calculation breaks down near the
event horizon is confirmed. The new surface gravity diverges and the metric is
degenerate at the stretched horizon.


  The Hydrogen Balmer series is a basic radiative loss channel from the flaring
solar chromosphere. We report here on the analysis of an extremely rare set of
simultaneous observations of a solar flare in the H${\alpha}$ and H${\beta}$
lines at high spatial and temporal resolution, which were acquired at the Dunn
Solar Telescope. Images of the C3.3 flare (SOL2014-04-22T15:22) made at various
wavelengths along the H${\alpha}$ line profile by the Interferometric
Bidimensional Spectrometer (IBIS) and in the H${\beta}$ with the Rapid
Oscillations in the Solar Atmosphere (ROSA) broadband imager are analyzed to
obtain the intensity evolution. The H${\alpha}$ and H${\beta}$ intensity
excesses in three identified flare footpoints are well correlated in time. We
examine the ratio of H${\alpha}$ to H${\beta}$ flare excess, which was proposed
by previous authors as a possible diagnostic of the level of electron beam
energy input. In the stronger footpoints, the typical value of the the
H${\alpha}$/H${\beta}$ intensity ratio observed is $\sim 0.4-0.5$, in broad
agreement with values obtained from a RADYN non-LTE simulation driven by an
electron beam with parameters constrained (as far as possible) by observation.
The weaker footpoint has a larger H${\alpha}$/H${\beta}$ ratio, again
consistent with a RADYN simulation but with a smaller energy flux. The
H${\alpha}$ line profiles observed have a less prominent central reversal than
is predicted by the RADYN results, but can be brought into agreement if the
H${\alpha}$-emitting material has a filling factor of around 0.2--0.3.


  This is a paper with two aims. First, we show that the map from
$\mathbb{Z}/p\mathbb{Z}$ to itself defined by exponentiation $x\to m^x$ has few
$3$-cycles -- that is to say, the number of cycles of length three is $o(p)$.
This improves on previous bounds.
  Our second objective is to contribute to an ongoing discussion on how to find
a non-sofic group. In particular, we show that, if the Higman group were sofic,
there would be a map from $\mathbb{Z}/p\mathbb{Z}$ to itself, locally like an
exponential map, yet satisfying a recurrence property.


  At low energies, interactions of massless particles in type II strings
compactified on a torus $T^d$ are described by an effective Wilsonian action
$\mathcal{S}(\Lambda)$, consisting of the usual supergravity Lagrangian
supplemented by an infinite series of higher-derivative vertices, including the
much studied $\nabla^{4p+6q} \mathcal{R}^4$ gravitational interactions. Using
recent results on the asymptotics of the integrands governing four-graviton
scattering at genus one and two, I determine the $\Lambda$-dependence of the
coefficient of the above interaction, and show that the logarithmic terms
appearing in the limit $\Lambda\to 0$ are related to UV divergences in
supergravity amplitudes, augmented by stringy interactions. This provides a
strong consistency check on the expansion of the integrand near the boundaries
of moduli space, in particular it elucidates the appearance of odd zeta values
in these expansions. I briefly discuss how these logarithms are reflected in
non-analytic terms in the low energy expansion of the string scattering
amplitude.


  Recently, it has been recognised that very large spectroscopic surveys
(several million spectra) are required to advance our understanding of Dark
Energy (via baryonic wiggles) and the detailed history of our Local Group of
galaxies (via Galactic Archeology or near-field cosmology). In this paper I
make a preliminary exploration of how this might be done by putting a wide
field, optical, prime-focus fibre-fed spectroscopic facility on one of the
VLT's UTs.


  In the presence of certain non-minimal couplings between a scalar field and
the Gauss-Bonnet curvature invariant, Kerr black holes can scalarize, as long
as they are spinning fast enough. This provides a distinctive violation of the
Kerr hypothesis, occurring only for some high spin range. In this paper we
assess if strong magnetic fields, that may exist in the vicinity of
astrophysical black holes, could facilitate this distinctive effect, by
bringing down the spin threshold for scalarization. This inquiry is motivated
by the fact that self-gravitating magnetic fields, by themselves, can also
promote "spin-induced" scalarization. Nonetheless, we show that in the
\textit{vicinity of the horizon} the effect of the magnetic field $B$ on a
black hole of mass $M$, up to $BM\lesssim 1$, works \textit{against}
spin-induced scalarization, requiring a larger dimensionless spin $j$ from the
black hole. A geometric interpretation for this result is suggested, in terms
of the effects of rotation $vs.$ magnetic fields on the horizon geometry.


  The majority of existing speech emotion recognition models are trained and
evaluated on a single corpus and a single language setting. These systems do
not perform as well when applied in a cross-corpus and cross-language scenario.
This paper presents results for speech emotion recognition for 4 languages in
both single corpus and cross corpus setting. Additionally, since multi-task
learning (MTL) with gender, naturalness and arousal as auxiliary tasks has
shown to enhance the generalisation capabilities of the emotion models, this
paper introduces language ID as another auxiliary task in MTL framework to
explore the role of spoken language on emotion recognition which has not been
studied yet.


  This is an expository paper on the regularity theory of maximal operators,
when these act on Sobolev and BV functions, with a special focus on some of the
current open problems in the topic. Overall, a list of fifteen research
problems is presented. It summarizes the contents of a talk delivered by the
author at the CIMPA 2017 Research School - Harmonic Analysis, Geometric Measure
Theory and Applications, in Buenos Aires, Argentina.


  Flavor-dependent long range (LR) leptonic forces, like those mediated by the
$L_e-L_\mu$ or $L_e -L_\tau$ gauge bosons, constitute a minimal extension of
the standard model that preserves its renormalizability. We study the impact of
such interactions on the solar neutrino oscillations when the interaction range
$R_{LR}$ is much larger than the Earth-Sun distance. The LR potential can
dominate over the standard charged current potential inside the Sun in spite of
strong constraints on the coupling $\alpha$ of the LR force coming from the
atmospheric neutrino data and laboratory search for new forces. We demonstrate
that the solar and atmospheric neutrino mass scales do not get trivially
decoupled even if $\theta_{13}$ is vanishingly small. In addition, for $\alpha
\gsim 10^{-52}$ and normal hierarchy, resonant enhancement of $\theta_{13}$
results in nontrivial energy dependent effects on the $\nu_e$ survival
probability. We perform a complete three generation analysis, and obtain
constraints on $\alpha$ through a global fit to the solar neutrino and KamLAND
data. We get the $3\sigma$ limits $\alpha_{e\mu} < 3.4 \times 10^{-53}$ and
$\alpha_{e\tau} < 2.5 \times 10^{-53}$ when $R_{LR}$ is much smaller than our
distance from the galactic center. With larger $R_{LR}$, the collective LR
potential due to all the electrons in the galaxy becomes significant and the
constraints on $\alpha$ become stronger by upto two orders of magnitude.


  The transformation n to k in post-post-Newtonian order is simplified. All
post-post-Newtonian terms of the order m^2/d^2 are neglected and we show that
the total sum of these terms is smaller than 15/4 pi m^2/d^2. This simpler
transformation will improve the efficiency of Gaia data reduction.


  In a Peccei-Quinn extension of supergravity the h --> \gamma\gamma detection
rate can be significantly enhanced due to the reduction of the total Higgs
decay width. To assess the viability of various Peccei-Quinn extensions of
minimal supergravity we perform a Bayesian analysis on three such scenarios.
The main constraints on these models come from the currently observed Higgs
boson like state by the Large Hadron Collider and from the WMAP observation of
dark matter abundance. Our comparative study reveals that under these
constraints the PQ violating scenarios with axino dark matter are clearly
preferred over the minimal supegravity model with the lightest neutralino as a
dark matter candidate.


  To study whether it is possible to differentiate intermediate age-related
macular degeneration (AMD) from healthy controls using partial optical
coherence tomography (OCT) data, that is, restricting the input B-scans to
certain pre-defined regions of interest (ROIs). A total of 15744 B-scans from
269 intermediate AMD patients and 115 normal subjects were used in this study
(split on subject level in 80% train, 10% validation and 10% test). From each
OCT B-scan, three ROIs were extracted: retina, complex between retinal pigment
epithelium (RPE) and Bruch membrane (BM), and choroid (CHO). These ROIs were
obtained using two different methods: masking and cropping. In addition to the
six ROIs, the whole OCT B-scan and the binary mask corresponding to the
segmentation of the RPE-BM complex were used. For each subset, a convolutional
neural network (based on VGG16 architecture and pre-trained on ImageNet) was
trained and tested. The performance of the models was evaluated using the area
under the receiver operating characteristic (AUROC), accuracy, sensitivity, and
specificity. All trained models presented an AUROC, accuracy, sensitivity, and
specificity equal to or higher than 0.884, 0.816, 0.685, and 0.644,
respectively. The model trained on the whole OCT B-scan presented the best
performance (AUROC = 0.983, accuracy = 0.927, sensitivity = 0.862, specificity
= 0.913). The models trained on the ROIs obtained with the cropping method led
to significantly higher outcomes than those obtained with masking, with the
exception of the retinal tissue, where no statistically significant difference
was observed between cropping and masking (p = 0.47). This study demonstrated
that while using the complete OCT B-scan provided the highest accuracy in
classifying intermediate AMD, models trained on specific ROIs such as the
RPE-BM complex or the choroid can still achieve high performance.


  For general nonlinear Klein-Gordon equations with dissipation we show that
any finite energy radial solution either blows up in finite time or
asymptotically approaches a stationary solution in $H^1\times L^2$. In
particular, any global solution is bounded. The result applies to standard
energy subcritical focusing nonlinearities $|u|^{p-1} u$,
$1\textless{}p\textless{}(d+2)/(d-2)$ as well as any energy subcritical
nonlinearity obeying a sign condition of the Ambrosetti-Rabinowitz type. The
argument involves both techniques from nonlinear dispersive PDEs and dynamical
systems (invariant manifold theory in Banach spaces and convergence theorems).


  We show that for any natural number $n$ satisfying $n\equiv 4 \mod 8$ and
$n\not\equiv 0 \mod 5$, and for any odd integer $t\geq \frac{n+6}{2}$ there are
infinitely many Salem numbers ${\alpha}$ of degree $2t$ such that
${\alpha}^n-1$ is a unit. This result, obtained using a generalization of a
construction due to Gross and McMullen [5], partially completes the main result
of [7].


  Non-attractor inflation is known as the only single field inflationary
scenario that can violate non-Gaussianity consistency relation with the
Bunch-Davies vacuum state and generate large local non-Gaussianity. However, it
is also known that the non-attractor inflation by itself is incomplete and
should be followed by a phase of slow-roll attractor. Moreover, there is a
transition process between these two phases. In the past literature, this
transition was approximated as instant and the evolution of non-Gaussianity in
this phase was not fully studied. In this paper, we follow the detailed
evolution of the non-Gaussianity through the transition phase into the
slow-roll attractor phase, considering different types of transition. We find
that the transition process has important effect on the size of the local
non-Gaussianity. We first compute the net contribution of the non-Gaussianities
at the end of inflation in canonical non-attractor models. If the curvature
perturbations keep evolving during the transition - such as in the case of
smooth transition or some sharp transition scenarios - the $\mathcal{O}(1)$
local non-Gaussianity generated in the non-attractor phase can be completely
erased by the subsequent evolution, although the consistency relation remains
violated. In extremal cases of sharp transition where the super-horizon modes
freeze immediately right after the end of the non-attractor phase, the original
non-attractor result can be recovered. We also study models with non-canonical
kinetic terms, and find that the transition can typically contribute a
suppression factor in the squeezed bispectrum, but the final local
non-Gaussianity can still be made parametrically large.


  The enhanced degradation of organophosphorous-based chemical warfare agents
(CWAs) on metal-oxide surfaces holds immense promise for neutralization
efforts; however, the underlying mechanisms in this process remain poorly
understood. We utilize large-scale quantum calculations for the first time to
probe the high-temperature degradation of diisopropyl methylphosphonate (DIMP),
a nerve agent simulant. Our Born-Oppenheimer molecular dynamics (BOMD)
calculations show that the $\gamma$-Al$_2$O$_3$ surface shows immense promise
for quickly adsorbing and destroying CWAs. We find that the alumina surface
quickly adsorbs DIMP at all temperatures, and subsequent decomposition of DIMP
proceeds via a propene elimination. Our BOMD calculations are complemented with
metadynamics simulations to produce free energy paths, which show that the
activation barrier decreases with temperature and DIMP readily decomposes on
$\gamma$-Al$_2$O$_3$. Our first-principle BOMD and metadynamics simulations
provide crucial diagnostics for sarin decomposition models and mechanistic
information for examining CWA decomposition reactions on other candidate metal
oxide surfaces.


  Here we study the emergence of spontaneous leadership in large populations.
In standard models of opinion dynamics, herding behavior is only obeyed at the
local scale due to the interaction of single agents with their neighbors; while
at the global scale, such models are governed by purely diffusive processes.
Surprisingly, in this paper we show that the combination of a strong separation
of time scales within the population and a hierarchical organization of the
influences of some agents on the others induces a phase transition between a
purely diffusive phase, as in the standard case, and a herding phase where a
fraction of the agents self-organize and lead the global opinion of the whole
population.


  Recently it is established, via lower order moments, that the univariate
q-normal distribution, which is the weight function for $q$-Hermite
polynomials, describes the ensemble averaged eigenvalue density from
many-particle random matrix ensembles generated by $k$-body interactions [Manan
Vyas and V.K.B. Kota, J. Stat. Mech. {\bf 2019}, 103103 (2019)]. These
ensembles are generically called embedded ensembles of $k$-body interactions
[EE($k$)] and their GOE and GUE versions are called EGOE($k$) and EGUE($k$)
respectively. Going beyond this work, the lower order bivariate reduced moments
of the transition strength densities, generated by EGOE($k$) [or EGUE($k$)] for
the Hamiltonian and an independent EGOE($t$) for the transition operator ${\cal
O}$ that is $t$-body, are used to establish that the ensemble averaged
bivariate transition densities follow the bivariate $q$-normal distribution.
Presented are also formulas for the bivariate correlation coefficient $\rho$
and the $q$ values as a function of the particle number $m$, number of single
particle states $N$ that the particles are occupying and the body ranks $k$ and
$t$ of $H$ and ${\cal O}$ respectively. Finally, using the bivariate $q$ normal
form a formula for the chaos measure number of principal components (NPC) in
the transition strengths from a state with energy $E$ is presented.


  Certain two-component reaction-diffusion systems on a finite interval are
known to possess mesa (box-like) steadystate patterns in the singularly
perturbed limit of small diffusivity for one of the two solution components. As
the diffusivity D of the second component is decreased below some critical
value Dc, with Dc = O(1), the existence of a steady-state mesa pattern is lost,
triggering the onset of a mesa self-replication event that ultimately leads to
the creation of additional mesas. The initiation of this phenomena is studied
in detail for a particular scaling limit of the Brusselator model. Near the
existence threshold Dc of a single steady-state mesa, it is shown that an
internal layer forms in the center of the mesa. The structure of the solution
within this internal layer is shown to be governed by a certain core problem,
comprised of a single non-autonomous second-order ODE. By analyzing this core
problem using rigorous and formal asymptotic methods, and by using the Singular
Limit Eigenvalue Problem (SLEP) method to asymptotically calculate small
eigenvalues, an analytical verification of the conditions of Nishiura and
Ueyema [Physica D, 130, No. 1, (1999), pp. 73-104], believed to be responsible
for self-replication, is given. These conditions include: (1) The existence of
a saddle-node threshold at which the steady-state mesa pattern disappears; (2)
the dimple-shaped eigenfunction at the threshold, believed to be responsible
for the initiation of the replication process; and (3) the stability of the
mesa pattern above the existence threshold. Finally, we show that the core
problem is universal in the sense that it pertains to a class of
reaction-diffusion systems, including the Gierer-Meinhardt model with
saturation, where mesa self-replication also occurs.


  The popularity of smart-home assistant systems such as Amazon Alexa and
Google Home leads to a booming third-party application market (over 70,000
applications across the two stores). While existing works have revealed
security issues in these systems, it is not well understood how to help
application developers to enforce security requirements. In this paper, we
perform a preliminary case study to examine the security vetting mechanisms
adopted by Amazon Alexa and Google Home app stores. With a focus on the
authentication mechanisms between Alexa/Google cloud and third-party
application servers (i.e. endpoints), we show the current security vetting is
insufficient as developer mistakes can not be effectively detected and
notified. A weak authentication would allow attackers to spoof the cloud to
insert/retrieve data into/from the application endpoints. We validate the
attack through ethical proof-of-concept experiments. To confirm vulnerable
applications have indeed passed the security vetting and entered the markets,
we develop a heuristic-based searching method. We find 219 real-world Alexa
endpoints that carry the vulnerability, many of which are related to critical
applications that control smart home devices and electronic cars. We have
notified Amazon and Google about our findings and offered our suggestions to
mitigate the issue.


  We present a new algorithm for generating merger trees and halo catalogs
which explicitly ensures consistency of halo properties (mass, position, and
velocity) across timesteps. Our algorithm has demonstrated the ability to
improve both the completeness (through detecting and inserting otherwise
missing halos) and purity (through detecting and removing spurious objects) of
both merger trees and halo catalogs. In addition, our method is able to
robustly measure the self-consistency of halo finders; it is the first to
directly measure the uncertainties in halo positions, halo velocities, and the
halo mass function for a given halo finder based on consistency between
snapshots in cosmological simulations. We use this algorithm to generate merger
trees for two large simulations (Bolshoi and Consuelo) and evaluate two halo
finders (ROCKSTAR and BDM). We find that both the ROCKSTAR and BDM halo finders
track halos extremely well; in both, the number of halos which do not have
physically consistent progenitors is at the 1-2% level across all halo masses.
Our code is publicly available at http://code.google.com/p/consistent-trees .
Our trees and catalogs are publicly available at
http://hipacc.ucsc.edu/Bolshoi/ .


  The number of spanning trees of a graph $G$ is called the {\em complexity} of
$G$ and is denoted $c(G)$. Let C(n) denote the {\em (binary) hypercube} of
dimension $n$. A classical result in enumerative combinatorics (based on
explicit diagonalization) states that $c(C(n)) = \prod_{k=2}^n (2k)^{n\choose
k}$.
  In this paper we use the explicit block diagonalization methodology to derive
formulas for the complexity of two $q$-analogs of C(n), the {\em nonbinary
hypercube} $\Cq(n)$, defined for $q\geq 2$, and the {\em vector space analog of
the hypercube} $\Cfq(n)$, defined for prime powers $q$.
  We consider the nonbinary and vector space analogs of the Boolean algebra. We
show the existence, in both cases, of a graded Jordan basis (with respect to
the up operator) that is orthogonal (with respect to the standard inner
product) and we write down explicit formulas for the ratio of the lengths of
the successive vectors in the Jordan chains (i.e., the singular values). With
respect to (the normalizations of) these bases the Laplacians of $\Cq(n)$ and
$\Cfq(n)$ block diagonalize, with quadratically many distinct blocks in the
nonbinary case and linearly many distinct blocks in the vector space case, and
with each block an explicitly written down real, symmetric, tridiagonal matrix
of known multiplicity and size at most $n+1$. In the nonbinary case we further
determine the eigenvalues of the blocks, by explicitly writing out the
eigenvectors, yielding an explicit formula for $c(\Cq(n))$ (this proof yields
new information even in the binary case). In the vector space case we have been
unable to determine the eigenvalues of the blocks but we give a useful formula
for $c(\Cfq(n))$ involving "small" determinants (of size at most $n$).


  We identify a categorical structure of the set of all CFTs. In particular, we
show that the set of all CFTs has a natural monoidal strict $2$-category
structure with the $1$-morphisms being sequences of deformations and
$2$-morphisms determined by $0$-form symmetries of the CFTs.


  In the regime of hot stars, winds were not seen as a common thing until the
era of UV astronomy. Since we have access to the UV wavelength range, it has
become clear that winds are not an exotic phenomenon limited to some special
objects, but actually ubiquitous among hot and massive stars. The opacities due
to spectral lines are the decisive ingredient that allows hot, massive stars to
launch powerful winds. While the fundamental principles of these so-called
line-driven winds have been realized decades ago, their proper quantitative
prediction is still a major challenge today. Established theoretical and
empirical descriptions have allowed us to make major progress on all
astrophysical scales. However, we are now reaching their limitations as we
still lack various fundamental insights on the nature of hot star winds,
thereby hampering us from drawing deeper conclusions, not least when dealing
with stellar or sub-stellar companions. This has spawned a new generation of
researchers searching for answers with a yet unprecedented level of detail in
observational and new theoretical approaches.
  In these proceedings, the fundamental principles of driving hot star winds
will be briefly reviewed. Starting from the classical CAK theory and its
extensions, over Monte Carlo and recent comoving-frame-based simulations, the
different methods to describe and model the acceleration of hot star winds will
be introduced. The review continues with briefly discussing instabilities as
well as qualitative and quantitative insights for OB- and Wolf-Rayet-star
winds. Moreover, the challenges of companions and their impact on
radiation-driven winds are outlined.


  Considerable progress has been made in determining the Hubble constant over
the past two decades. We discuss the cosmological context and importance of an
accurate measurement of the Hubble constant, and focus on six high-precision
distance-determination methods: Cepheids, tip of the red giant branch, maser
galaxies, surface brightness fluctuations, the Tully-Fisher relation and Type
Ia supernovae. We discuss in detail known systematic errors in the measurement
of galaxy distances and how to minimize them. Our best current estimate of the
Hubble constant is 73 +/-2 (random) +/-4 (systematic) km/s/Mpc. The importance
of improved accuracy in the Hubble constant will increase over the next decade
with new missions and experiments designed to increase the precision in other
cosmological parameters. We outline the steps that will be required to deliver
a value of the Hubble constant to 2% systematic uncertainty and discuss the
constraints on other cosmological parameters that will then be possible with
such accuracy.


  The diffusion coefficient of heavy quarks in the deconfined medium is
examined in this research using a deep convolutional neural network (CNN)
trained with data from relativistic heavy ion collisions involving heavy flavor
hadrons. The CNN is trained using observables such as the nuclear modification
factor $R_{AA}$ and the elliptic flow $v_2$ of non-prompt $J/\psi$ from
B-hadron decay in different centralities, where B meson evolutions are
calculated using the Langevin equation and the Instantaneous Coalescence Model.
The CNN outputs the parameters characterizing the temperature and momentum
dependence of the heavy quark diffusion coefficient. By inputting the
experimental data of non-prompt $J/\psi$ $(R_{AA}, v_2)$ from various collision
centralities into multiple channels of the well-trained network, we derive the
values of the diffusion coefficient parameters. Additionally, We evaluate the
uncertainty in determining the diffusion coefficient by taking into account the
uncertainties present in the experimental data $(R_{AA}, v_2)$, which serve as
inputs to the deep neural network.


  We report on the results of a simultaneous monitoring campaign employing
eight Chandra X-ray (0.5-10 keV) and six VLA/EVLA (8.4 GHz) radio observations
of NGC 4051 over seven months. Evidence for compact jets is observed in the 8.4
GHz radio band; This builds on mounting evidence that jet production may be
prevalent even in radio-quiet Seyferts. Assuming comparatively negligible local
diffuse emission in the nucleus, the results also demonstrate an inverse
correlation of L_radio proportional to L_X-ray ^(-0.72+/-0.04) . Current
research linking the mass of supermassive black holes and stellar-mass black
holes in the "low/hard" state to X-ray luminosities and radio luminosities
suggest a "fundamental plane of accretion onto black holes" that has a positive
correlation of L_radio proportional to L_X-ray^(0.67+/-0.12) . Our simultaneous
results differ from this relation by more than 11 sigma, indicating that a
separate mode of accretion and ejection may operate in this system. A review of
the literature shows that the inverse correlation seen in NGC 4051 is seen in
three other black hole systems, all of which accrete at near 10% of their
Eddington luminosity, perhaps suggesting a distinct mode of disk-jet coupling
at high Eddington fractions. We discuss our results in the context of disk and
jets in black holes and accretion across the black hole mass scale.


  This article provides a new toolbox to derive sparse recovery guarantees from
small deviations on extreme singular values or extreme eigenvalues obtained in
Random Matrix Theory. This work is based on Restricted Isometry Constants
(RICs) which are a pivotal notion in Compressed Sensing and High-Dimensional
Statistics as these constants finely assess how a linear operator is
conditioned on the set of sparse vectors and hence how it performs in SRSR.
While it is an open problem to construct deterministic matrices with apposite
RICs, one can prove that such matrices exist using random matrices models. In
this paper, we show upper bounds on RICs for Gaussian and Rademacher matrices
using state-of-the-art small deviation estimates on their extreme eigenvalues.
This allows us to derive a lower bound on the probability of getting SRSR. One
benefit of this paper is a direct and explicit derivation of upper bounds on
RICs and lower bounds on SRSR from small deviations on the extreme eigenvalues
given by Random Matrix theory.


  In this paper, we show a construction of a weakly universal cellular
automaton in the 3D hyperbolic space with two states. The cellular automaton is
rotation invariant and, moreover, based on a new implementation of a railway
circuit in the dodecagrid,the construction is a truly 3D-one.


  We investigate the kinematics of red clump stars in the Solar Neighbourhood
by combining data from TGAS and RAVE to constrain the local dark matter
density. After calibrating the absolute magnitude of red clump stars, we
characterize their velocity distribution over a radial distance range of
$6$-$10$ kpc and up to $1.5$ kpc away from the Galactic plane. We then apply
the axisymmetric Jeans equations on subsets representing the thin and thick
disks to determine the (local) distribution of mass near the disk of our
Galaxy. Our kinematic maps are well-behaved permitting a straightforward local
determination of the vertical force, which we find to be $K_z^{\rm thin} =
-2454 \pm 619$ and $K_z^{\rm thick} = -2141 \pm 774$ $(\mathrm{km/s})^2 \!
/\mathrm{kpc}$ at $1.5$ kpc away from the Galactic plane for the thin and thick
disk samples and for thin and thick disk scale heights of 0.28 kpc and 1.12 kpc
respectively. These measurements can be translated into a local dark matter
density $\rho_\textrm{DM} \sim 0.018 \pm 0.002 M_\odot/\textrm{pc}^3$. The
systematic error on this estimate is much larger than the quoted statistical
error, since even a 10% difference in the scale height of the thin disk leads
to a 30% change in the value of $\rho_\textrm{DM}$, and a nearly equally good
fit to the data.


  We propose a novel approach for parameterizing the luminosity distance, based
on the use of rational "Pad\'e" approximations. This new technique extends
standard Taylor treatments, overcoming possible convergence issues at high
redshifts plaguing standard cosmography. Indeed, we show that Pad\'e expansions
enable us to confidently use data over a larger interval with respect to the
usual Taylor series. To show this property in detail, we propose several Pad\'e
expansions and we compare these approximations with cosmic data, thus obtaining
cosmographic bounds from the observable universe for all cases. In particular,
we fit Pad\'e luminosity distances with observational data from different
uncorrelated surveys. We employ union 2.1 supernova data, baryonic acoustic
oscillation, Hubble space telescope measurements and differential age data. In
so doing, we also demonstrate that the use of Pad\'e approximants can improve
the analyses carried out by introducing cosmographic auxiliary variables, i.e.
a standard technique usually employed in cosmography in order to overcome the
divergence problem. Moreover, for any drawback related to standard cosmography,
we emphasize possible resolutions in the framework of Pad\'e approximants. In
particular, we investigate how to reduce systematics, how to overcome the
degeneracy between cosmological coefficients, how to treat divergences and so
forth. As a result, we show that cosmic bounds are actually refined through the
use of Pad\'e treatments and the thus derived best values of the cosmographic
parameters show slight departures from the standard cosmological paradigm.
Although all our results are perfectly consistent with the $\Lambda$CDM model,
evolving dark energy components different from a pure cosmological constant are
not definitively ruled out.


  Let L be a D-dimensional submanifold of a 2D-dimensional exact symplectic
manifold (M, w) and let f be a symplectic diffeomorphism onf M. In this
article, we deal with the link between the dynamics of f restricted to L and
the geometry of L (is L Lagrangian, is it smooth, is it a graph...?). We prove
different kinds of results. - for D=3, we prove that if a torus that carries
some characteristic loop, then either L is Lagrangian or the restricted
dynamics g of f to L can not be minimal (i.e. all the orbits are dense) with
(g^k) equilipschitz; - for a Tonelli Hamiltonian of the cotangent bundle M of
the 3-dimenional torus, we give an example of an invariant submanifold L with
no conjugate points that is not Lagrangian and such that for every symplectic
diffeomorphism f of M, if $f(L)=L$, then $L$ is not minimal; - with some
hypothesis for the restricted dynamics, we prove that some invariant Lipschitz
D-dimensional submanifolds of Tonelli Hamiltonian flows are in fact Lagrangian,
C^1 and graphs; -we give similar results for C^1 submanifolds with weaker
dynamical assumptions.


  We present a method based on symbolic dynamics for the detection of
synchronization in networks of coupled maps and distinguishing between chaotic
and random iterations. The symbolic dynamics are defined using special
partitions of the phase space which prevent the occurrence of certain symbol
sequences related to the characteristics of the dynamics. Synchrony in a large
network can be detected using measurements from only a single node by checking
for the presence of forbidden symbol transitions. The method utilises a
relatively short time series of measurements and hence is computationally very
fast. Furthermore, it is robust against parameter uncertainties, is independent
of the network size, and does not require knowledge of the connection
structure.


  A new exact nonlinear Newtonian solution for a plane matter flow superimposed
on the isotropic Hubble expansion is reported. The dynamical effect of cosmic
vacuum is taken into account. The solution describes the evolution of nonlinear
perturbations via gravitational instability of matter and the termination of
the perturbation growth by anti-gravity of vacuum at the epoch of transition
from matter domination to vacuum domination. On this basis, an `approximate' 3D
solution is suggested as an analog of the Zeldovich ansatz.


  A quantitative "fourth moment theorem" is provided for any self-adjoint
element in a homogeneous Wigner chaos: the Wasserstein distance is controlled
by the distance from the fourth moment to two. The proof uses the free
counterpart of the Stein discrepancy. On the way, the free analogue of the WSH
inequality is established.


  An important issue in releasing individual data is to protect the sensitive
information from being leaked and maliciously utilized. Famous privacy
preserving principles that aim to ensure both data privacy and data integrity,
such as $k$-anonymity and $l$-diversity, have been extensively studied both
theoretically and empirically. Nonetheless, these widely-adopted principles are
still insufficient to prevent attribute disclosure if the attacker has partial
knowledge about the overall sensitive data distribution. The $t$-closeness
principle has been proposed to fix this, which also has the benefit of
supporting numerical sensitive attributes. However, in contrast to
$k$-anonymity and $l$-diversity, the theoretical aspect of $t$-closeness has
not been well investigated.
  We initiate the first systematic theoretical study on the $t$-closeness
principle under the commonly-used attribute suppression model. We prove that
for every constant $t$ such that $0\leq t<1$, it is NP-hard to find an optimal
$t$-closeness generalization of a given table. The proof consists of several
reductions each of which works for different values of $t$, which together
cover the full range. To complement this negative result, we also provide exact
and fixed-parameter algorithms. Finally, we answer some open questions
regarding the complexity of $k$-anonymity and $l$-diversity left in the
literature.


  Assuming trivial action of Euclidean translations of the little group, we
derive a simple correspondence between massless field representations
transforming under the full generalized even dimensional Lorentz group, and
highest weight states of the relevant little group. This yields a connection
between `helicity' and `chirality' in all dimensions, and highlights the
special nature of the restricted representations under `gauge' transformations.


  In time series analysis research there is a strong interest in discrete
representations of real valued data streams. One approach that emerged over a
decade ago and is still considered state-of-the-art is the Symbolic Aggregate
Approximation algorithm. This discretization algorithm was the first symbolic
approach that mapped a real-valued time series to a symbolic representation
that was guaranteed to lower-bound Euclidean distance. The interest of this
paper concerns the SAX assumption of data being highly Gaussian and the use of
the standard normal curve to choose partitions to discretize the data. Though
not necessarily, but generally, and certainly in its canonical form, the SAX
approach chooses partitions on the standard normal curve that would produce an
equal probability for each symbol in a finite alphabet to occur. This procedure
is generally valid as a time series is normalized before the rest of the SAX
algorithm is applied. However there exists a caveat to this assumption of
equi-probability due to the intermediate step of Piecewise Aggregate
Approximation (PAA). What we will show in this paper is that when PAA is
applied the distribution of the data is indeed altered, resulting in a
shrinking standard deviation that is proportional to the number of points used
to create a segment of the PAA representation and the degree of
auto-correlation within the series. Data that exhibits statistically
significant auto-correlation is less affected by this shrinking distribution.
As the standard deviation of the data contracts, the mean remains the same,
however the distribution is no longer standard normal and therefore the
partitions based on the standard normal curve are no longer valid for the
assumption of equal probability.


  For a symplectic manifold M without boundary (not necessarily compact), we
prove Poincare type duality in filtered cohomology rings of differential forms
on M.


  We consider the problem of determining the minimum number of moves needed to
solve a certain one-dimensional peg puzzle. Let N be a positive integer. The
puzzle apparatus consists of a block with a single row of 2N+1 equally spaced
holes which, apart from the central hole, are occupied by an equal number N of
red and blue pegs. The object of the puzzle is to exchange the colors of the
pegs by a succession of allowable moves. Allowable moves are of two types: a
peg can be shifted from the hole it occupies into the empty hole adjacent to
it, or a peg can jump over an adjacent peg into the empty hole. We exhibit a
sequence of N^2+2N moves that solves the puzzle, and prove that no solution can
employ fewer moves.


  The paper presents a sample of newly detected eclipsing binaries from the
public Kepler data. Orbits and fundamental parameters of 20 unknown eclipsing
binaries were determined by modeling of their photometric data. Most of them
are well-detached, high-eccentric binaries. We established that the target
KID8552719 satisfied all widespread criteria for a planetary candidate. Fitting
its light curve we obtained radius R_p=0.9 R_Nept, distance to the host star a
= 42.58 Rsun = 0.198 AU and equilibrium temperatute T_p= 489 K. These values
imply a Neptune-size object out of the habitable zone of the host star.


  In this paper we study the linear systems arising from discretized
poroelasticity problems. We formulate one block preconditioner for the
two-filed Biot model and several preconditioners for the classical three-filed
Biot model under the unified relationship framework between well-posedness and
preconditioners. By the unified theory, we show all the considered
preconditioners are uniformly optimal with respect to material and
discretization parameters. Numerical tests demonstrate the robustness of these
preconditioners.


  We report a systematic study of thickness-dependent superconductivity and
carrier transport properties in exfoliated layered 2H-NbS2. Hall-effect
measurements reveal 2H-NbS2 in its normal state to be a p-type metal with hole
mobility of 1-3 cm2/Vs. The superconducting transition temperature is found to
decrease with thickness. We find that the suppression of superconductivity is
due to disorder resulting from the incorporation of atmospheric oxygen and a
reduced hole density. Cross-section transmission electron microscope (TEM)
imaging reveals a chemical change of NbS2 in ambient conditions, resulting in
the formation of amorphous oxide layers sandwiching crystalline layered NbS2.
Though few-nm-thick 2H-NbS2 completely converts to amorphous oxide in ambient
conditions, PMMA encapsulation prevents further chemical change and preserves
superconductivity.


  Training a task-completion dialogue agent via reinforcement learning (RL) is
costly because it requires many interactions with real users. One common
alternative is to use a user simulator. However, a user simulator usually lacks
the language complexity of human interlocutors and the biases in its design may
tend to degrade the agent. To address these issues, we present Deep Dyna-Q,
which to our knowledge is the first deep RL framework that integrates planning
for task-completion dialogue policy learning. We incorporate into the dialogue
agent a model of the environment, referred to as the world model, to mimic real
user response and generate simulated experience. During dialogue policy
learning, the world model is constantly updated with real user experience to
approach real user behavior, and in turn, the dialogue agent is optimized using
both real experience and simulated experience. The effectiveness of our
approach is demonstrated on a movie-ticket booking task in both simulated and
human-in-the-loop settings.


  Distinct X-ray plateau and flare phases have been observed in the afterglows
of gamma-ray bursts (GRBs), and most of them should be related to central
engine activities. In this paper, we collect 174 GRBs with X-ray plateau phases
and 106 GRBs with X-ray flares. There are 51 GRBs that overlap in the two
selected samples. We analyze the distributions of the proportions of the
plateau energy $E_{\rm plateau}$ and the flare energy $E_{\rm flare}$ relative
to the isotropic prompt emission energy $E_{\rm \gamma,iso}$. The results
indicate that they well meet the Gaussian distributions and the medians of the
logarithmic ratios are $\sim -0.96$ and $-1.39$ in the two cases. Moreover,
strong positive correlations between $E_{\rm plateau}$ (or $E_{\rm flare}$) and
$E_{\rm \gamma,iso}$ with slopes of $\sim 0.95$ (or $\sim0.80$) are presented.
For the overlapping sample, the slope is $\sim 0.80$. We argue that most of
X-ray plateaus and flares might have the same physical origin but appear with
different features because of the different circumstances and radiation
mechanisms. We also test the applicabilities of two models, i.e., black holes
surrounded by fractured hyperaccretion disks and millisecond magnetars, on the
origins of X-ray plateaus and flares.


  We consider classes of ideals which generalize the mixed product ideals
introduced by Restuccia and Villarreal, and also generalize the expansion
construction by Bayati and the first author \cite{BH}. We compute the minimal
graded free resolution of generalized mixed product ideals and show that the
regularity of a generalized mixed product ideal coincides with regularity of
the monomial ideal by which it is induced.


  Understanding the phase transition mechanisms in two-dimensional (2D)
materials is a key to precisely tailor their properties at the nanoscale.
Molybdenum ditelluride (MoTe2) exhibits multiple phases at room temperature,
making it a promising candidate for phase-change applications. Here, we
fabricate lateral 2H-Td interfaces with laser irradiation and probe their phase
transitions from micro- to atomic scales with in situ heating in the
transmission electron microscope (TEM). By encapsulating the MoTe2 with
graphene protection layers, we create an in situ reaction cell compatible with
atomic resolution imaging. We find that the Td-to-2H phase transition initiates
at phase boundaries at low temperatures (200-225 degree C) and propagates
anisotropically along the b-axis in a layer-by-layer fashion. We also
demonstrate a fully reversible 2H-Td-2H phase transition cycle, which generates
a coherent 2H lattice containing inversion domain boundaries. Our results
provide insights on fabricating 2D hetero-phase devices with atomically sharp
and coherent interfaces.


  We introduce the notion of "non-malleability" of a quantum state encryption
scheme (in dimension d): in addition to the requirement that an adversary
cannot learn information about the state, here we demand that no controlled
modification of the encrypted state can be effected.
  We show that such a scheme is equivalent to a "unitary 2-design" [Dankert et
al.], as opposed to normal encryption which is a unitary 1-design. Our other
main results include a new proof of the lower bound of (d^2-1)^2+1 on the
number of unitaries in a 2-design [Gross et al.], which lends itself to a
generalization to approximate 2-design.
  Furthermore, while in prime power dimension there is a unitary 2-design with
=< d^5 elements, we show that there are always approximate 2-designs with
O(epsilon^{-2} d^4 log d) elements.


  Registration of longitudinal optical coherence tomography (OCT) images
assists disease monitoring and is essential in image fusion applications. Mouse
retinal OCT images are often collected for longitudinal study of eye disease
models such as uveitis, but their quality is often poor compared with human
imaging. This paper presents a novel but efficient framework involving an
optimal transport based graph matching (OT-GM) method for 3D mouse OCT image
registration. We first perform registration of fundus-like images obtained by
projecting all b-scans of a volume on a plane orthogonal to them, hereafter
referred to as the x-y plane. We introduce Adaptive Weighted Vessel Graph
Descriptors (AWVGD) and 3D Cube Descriptors (CD) to identify the correspondence
between nodes of graphs extracted from segmented vessels within the OCT
projection images. The AWVGD comprises scaling, translation and rotation, which
are computationally efficient, whereas CD exploits 3D spatial and frequency
domain information. The OT-GM method subsequently performs the correct
alignment in the x-y plane. Finally, registration along the direction
orthogonal to the x-y plane (the z-direction) is guided by the segmentation of
two important anatomical features peculiar to mouse b-scans, the Internal
Limiting Membrane (ILM) and the hyaloid remnant (HR). Both subjective and
objective evaluation results demonstrate that our framework outperforms other
well-established methods on mouse OCT images within a reasonable execution
time.


  Mobile edge computing has become an effective and fundamental paradigm for
futuristic autonomous vehicles to offload computing tasks. However, due to the
high mobility of vehicles, the dynamics of the wireless conditions, and the
uncertainty of the arrival computing tasks, it is difficult for a single
vehicle to determine the optimal offloading strategy. In this paper, we propose
a Digital Twin (DT) empowered task offloading framework for Internet of
Vehicles. As a software agent residing in the cloud, a DT can obtain both
global network information by using communications among DTs, and historical
information of a vehicle by using the communications within the twin. The
global network information and historical vehicular information can
significantly facilitate the offloading. In specific, to preserve the precious
computing resource at different levels for most appropriate computing tasks, we
integrate a learning scheme based on the prediction of futuristic computing
tasks in DT. Accordingly, we model the offloading scheduling process as a
Markov Decision Process (MDP) to minimize the long-term cost in terms of a
trade off between task latency, energy consumption, and renting cost of clouds.
Simulation results demonstrate that our algorithm can effectively find the
optimal offloading strategy, as well as achieve the fast convergence speed and
high performance, compared with other existing approaches.


  Context: Ideal MHD simulations have revealed catastrophic magnetic braking
(MB) in the protostellar phase, which prevents the formation of a centrifugal
disk around a nascent protostar. Aims: We determine if non-ideal MHD, including
the effects of ambipolar diffusion and Ohmic dissipation determined from a
detailed chemical network model, allows for disk formation at the earliest
stages of star formation (SF). Methods: We employ the axisymmetric thin-disk
approximation in order to resolve a dynamic range of 9 orders of magnitude in
length and 16 in density, while also calculating partial ionization using up to
19 species in a detailed chemical equilibrium model. MB is applied using a
steady-state approximation, and a barotropic relation is used to capture the
thermal evolution. Results: We resolve the formation of the first and second
cores, with expansion waves at the periphery of each, a magnetic diffusion
shock, and prestellar infall profiles at larger radii. Power-law profiles in
each region can be understood analytically. After the formation of the second
core, centrifugal support rises rapidly and a low-mass disk of radius ~10 R_Sun
is formed, when the second core has mass ~0.001 M_Sun. The mass-to-flux ratio
is ~10,000 times the critical value in the central region. Conclusions: A small
centrifugal disk can form in the earliest stage of SF, due to a shut-off of MB
caused by magnetic field dissipation in the first core region. There is enough
angular momentum loss to allow the second collapse to occur directly, and a
low-mass stellar core to form with a surrounding disk. The disk mass and size
will depend upon how the angular momentum transport mechanisms within the disk
can keep up with mass infall onto the disk. We estimate that the disk will
remain <~10 AU, undetectable even by ALMA, in the early Class 0 phase.


  Using ab-initio non-Born-Oppenheimer simulations, we demonstrate
amplification of XUV radiation in a high-harmonic generation type process using
the example of the hydrogen molecular ion. A small fraction of the molecules is
pumped to a dissociative Rydberg state from which IR-assisted XUV amplification
is observed. We show that starting at sufficiently high IR driving field
intensities the ground state molecules become quasi-transparent for XUV
radiation, while due to stabilization gain from Rydberg states is maintained,
thus leading to lasing from strongly driven Rydberg states. Further increase of
the IR intensity even leads to gain by initially unexcited molecules, which are
quickly excited by the driving IR pulse.


  In this paper, we present a downlink pilot design scheme for Deep Learning
(DL) based channel estimation (ChannelNet) in orthogonal frequency-division
multiplexing (OFDM) systems. Specifically, in the proposed scheme, a feature
selection method named Concrete Autoencoder (ConcreteAE) is used to find the
most informative locations for pilot transmission. This autoencoder consists of
a concrete layer as the encoder and a multilayer perceptron (MLP) as the
decoder. During the training, the concrete layer selects the most informative
pilot locations, and the decoder reconstructs an approximate estimation of the
channel. Eventually, the ChannelNet is trained on the output of the ConcreteAE
aiming to reconstruct the ideal channel response. The estimation error results
show that this approach outperforms the previously presented ChannelNet with a
uniformly distributed pilot pattern, and its performance is comparable to the
minimum mean square error (MMSE).


  We present an improved analytic parametrisation of the complex in-medium
heavy quark potential derived rigorously from the generalised Gauss law. To
this end we combine in a self-consistent manner a non-perturbative vacuum
potential with a weak-coupling description of the QCD medium. The resulting
Gauss-law parametrisation is able to reproduce full lattice QCD data by using
only a single temperature dependent parameter, the Debye mass $m_D$. Using this
parametrisation we model the in-medium potential at finite baryo-chemical
potential, which allows us to estimate the $\Psi^\prime$/$J/\Psi$ ratio in
heavy-ion collisions at different beam energies.


  Using both halo model calculations and a large sample of simulated SZ maps,
we demonstrate that high-mass clusters add significant non-Gaussian variance to
measurements of the SZ power spectrum amplitude. The difficulty in correctly
accounting theoretically for the contribution of these objects to the
uncertainty in C_l leads to a reduced sensitivity to \sigma_8. We show that a
simple solution is to mask out the brightest clusters in the map before
measuring the power spectrum. We demonstrate that fairly conservative masking
can reduce the variance and Gaussianize the statistics significantly, thus
increasing the sensitivity to cosmological parameters. Choosing which objects
to mask is non-trivial; we found that using a fixed sky density produced a
well-defined and well-behaved estimate that can easily be applied to real maps.
For example, masking the 10 (90) brightest clusters in a 100 deg^2 SZ map will
improve the sensitivity to C_l by a factor of two at l = 1000 (2000) and 1.5 at
l = 2000 (4000). We show that even in the presence of astrophysical foregrounds
(primary CMB and point sources) and instrument noise, one can increase the
precision on measurements of \sigma_8 by masking up to 0.9 clusters/deg^2.


  We study two coupled active rotators with Kuramoto-type coupling and focus
our attention to specific transitional regimes where the coupling is neither
attractive nor repulsive. We show that certain such situations at the edge of
synchronization can be characterized by the existence of a time-reversal
symmetry of the system. We identify two different cases with such a
time-reversal symmetry. The first case is characterized by a non-reciprocal
attractive/repulsive coupling. The second case is a reciprocal coupling exactly
at the edge between attraction and repulsion. We give a detailed description of
possible different types of dynamics and bifurcations for both cases. In
particular, we show how the time-reversible coupling can induce both
oscillation death and oscillation birth to the active rotators. Moreover, we
analyse the coexistence of conservative and dissipative regions in phase space,
which is a typical feature of systems with a time-reversal symmetry. We show
also, how perturbations breaking the time-reversal symmetry and destroying the
conservative regions can lead to complicated types of dissipative dynamics such
as the emergence of long-period cycles showing a bursting-like behavior.


  Reduction of the left regular representation of quantum algebra $sl_q(3)$ is
studied and ~$q$-difference intertwining operators are constructed. The
irreducible representations correspond to the spaces of local sections of
certain line bundles over the q-flag manifold.


  We prove the Lefschetz property for a certain class of finite-dimensional
Gorenstein algebras associated to matroids. Our result implies the Sperner
property of the vector space lattice. More generally, it is shown that the
modular geometric lattice has the Sperner property. We also discuss the
Gr\"obner fan of the defining ideal of our Gorenstein algebra.


  The study of Coulomb excitation of 11Be to the first excited state in
intermediate energy collisions with heavy targets is presented. The existing
experimental data are reanalised by including the probability of projectile
survival into the calculation of Coulomb excitation cross sections. The
survival probabilities are calculated using a recently developed global optical
model potential tailored in line with the double folding model. The extracted
B(E1) values for the transition 1/2+ --> 1/2- in 11Be are found to be slightly
larger than those obtained so far using the b_0-recipe in Coulomb excitation
theory.


  Generative models have enabled the creation of contents that are
indistinguishable from those taken from nature. Open-source development of such
models raised concerns about the risks of their misuse for malicious purposes.
One potential risk mitigation strategy is to attribute generative models via
fingerprinting. Current fingerprinting methods exhibit a significant tradeoff
between robust attribution accuracy and generation quality while lacking design
principles to improve this tradeoff. This paper investigates the use of latent
semantic dimensions as fingerprints, from where we can analyze the effects of
design variables, including the choice of fingerprinting dimensions, strength,
and capacity, on the accuracy-quality tradeoff. Compared with previous SOTA,
our method requires minimum computation and is more applicable to large-scale
models. We use StyleGAN2 and the latent diffusion model to demonstrate the
efficacy of our method.


  Nano-size drones hold enormous potential to explore unknown and complex
environments. Their small size makes them agile and safe for operation close to
humans and allows them to navigate through narrow spaces. However, their tiny
size and payload restrict the possibilities for on-board computation and
sensing, making fully autonomous flight extremely challenging. The first step
towards full autonomy is reliable obstacle avoidance, which has proven to be
technically challenging by itself in a generic indoor environment. Current
approaches utilize vision-based or 1-dimensional sensors to support nano-drone
perception algorithms. This work presents a lightweight obstacle avoidance
system based on a novel millimeter form factor 64 pixels multi-zone
Time-of-Flight (ToF) sensor and a generalized model-free control policy.
Reported in-field tests are based on the Crazyflie 2.1, extended by a custom
multi-zone ToF deck, featuring a total flight mass of 35g. The algorithm only
uses 0.3% of the on-board processing power (210uS execution time) with a frame
rate of 15fps, providing an excellent foundation for many future applications.
Less than 10% of the total drone power is needed to operate the proposed
perception system, including both lifting and operating the sensor. The
presented autonomous nano-size drone reaches 100% reliability at 0.5m/s in a
generic and previously unexplored indoor environment. The proposed system is
released open-source with an extensive dataset including ToF and gray-scale
camera data, coupled with UAV position ground truth from motion capture.


  We investigate the formation and evolution of z=0 massive compact galaxies
(MCGs) in the IllustrisTNG cosmological simulation. We found that, as in
observations, MCGs are mainly old (median age $\sim 10.8$ Gyr), have
super-solar metallicities (median $\log Z/Z_{\odot}\sim0.35$) and are
$\alpha$-enhanced (median $[\alpha/Fe]\sim0.25$). The age distribution extends
to younger ages, however, and a few MCGs are as young as $\sim7$ Gyr. In
general, MCGs assemble their mass early and accrete low angular momentum gas,
significantly increasing their mass while growing their size much slower. A
small fraction of MCGs follow another evolutionary path, going through a
compaction event, with their sizes shrinking by 40% or more. The accretion of
low angular momentum gas leads to enhanced SMBH growth, and MCGs reach the
threshold SMBH mass of $\log M_\mathrm{BH}\sim10^{8.5} M_\odot$ - when kinetic
AGN feedback kicks in and quenches the galaxy - earlier than non-compact
galaxies. Comparing MCGs to a sample of median-sized quiescent galaxies matched
in effective velocity dispersion, we find that their accretion histories are
very different. 71% of MCGs do not merge after quenching compared to 37% of
median-sized quiescent galaxies. Moreover, tracing these populations back in
time, we find that at least a third of median-sized quiescent galaxies do not
have a compact progenitor, underscoring that both dry mergers and progenitor
bias effects are responsible for the differences in the kinematics and stellar
population properties of MCGs and median-sized quiescent galaxies.


  We develop a statistical physics theory for solid-solid phase transitions in
which a metamaterial undergoes longitudinal contraction in response to increase
in external tension. Such transitions, which are forbidden in thermodynamic
equilibrium, have recently been shown to be possible during the decay of
metastable, super-strained states. We present a first-principles model to
predict these transitions and validate it using molecular dynamics simulations.
Aside from its immediate mechanical implications, our theory points to a wealth
of analogous inverted responses, such as inverted susceptibility or
heat-capacity transitions, allowed when considering realistic scales.


  Species or population that proliferate faster than others become dominant in
numbers. Catalysis allows catalytic sets within a molecular reaction network to
dominate the non catalytic parts of the network by processing most of the
available substrate. As a consequence one may consider a 'catalytic fitness' of
sets of molecular species. The fittest sets emerge as the expressed chemical
backbone or sub-network of larger chemical reaction networks employed by
organisms. However, catalytic fitness depends on the systemic context and the
stability of systemic dynamics. Unstable reaction networks would easily be
reshaped or destroyed by fluctuations of the chemical environment. In this
paper we therefore focus on recognizing systemic stability as an evolutionary
selection criterion. In fact, instabilities of regulatory systems dynamics
become predictive for associated evolutionary forces driving the emergence
large reaction networks that avoid or control inherent instabilities. Systemic
instabilities can be identified and analyzed using relatively simple
mathematical random networks models of complex regulatory systems. Using a
statistical ensemble approach one can identify fundamental causes of instable
dynamics, infer evolutionary preferred network properties, and predict
evolutionary emergent control mechanisms and their entanglement with cell
differentiation processes. Surprisingly, what systemic stability tells us here
is that cells (or other non-linear regulatory systems) never had to learn how
to differentiate, but rather how to avoid and control differentiation. For
example, in this framework we can predict that regulatory systems will
evolutionary favor networks where the number of catalytic enhancers is not
larger than the number of suppressors.


  This paper describes measurements of the sum of the transverse energy of
particles as a function of particle pseudorapidity, eta, in proton-proton
collisions at a centre-of-mass energy, sqrt(s) = 7 TeV using the ATLAS detector
at the Large Hadron Collider. The measurements are performed in the region
|eta| < 4.8 for two event classes: those requiring the presence of particles
with a low transverse momentum and those requiring particles with a significant
transverse momentum. In the second dataset measurements are made in the region
transverse to the hard scatter. The distributions are compared to the
predictions of various Monte Carlo event generators, which generally tend to
underestimate the amount of transverse energy at high |eta|.


  The energy content of the vacuum condensate induced by the neutrino mixing is
interpreted as dynamically evolving dark energy.


  We consider the spacetime presented by Bonnor \cite{Bonnor98}, whose matter
content is a spheroid of electrically counterpoised dust, in the context of the
geometrical inequalities between area and charge. We determine numerically the
constant mean curvature surfaces that are candidates to be stable isoperimetric
surfaces and analyze the relation between area and charge for them, showing
that a previously proved inequality is far from being saturated. We also show
that the maximal initial data has a cylindrical limit where the minimum of the
area-charge relation is attained.


  Dense video captioning is a fine-grained video understanding task that
involves two sub-problems: localizing distinct events in a long video stream,
and generating captions for the localized events. We propose the Joint Event
Detection and Description Network (JEDDi-Net), which solves the dense video
captioning task in an end-to-end fashion. Our model continuously encodes the
input video stream with three-dimensional convolutional layers, proposes
variable-length temporal events based on pooled features, and generates their
captions. Proposal features are extracted within each proposal segment through
3D Segment-of-Interest pooling from shared video feature encoding. In order to
explicitly model temporal relationships between visual events and their
captions in a single video, we also propose a two-level hierarchical captioning
module that keeps track of context. On the large-scale ActivityNet Captions
dataset, JEDDi-Net demonstrates improved results as measured by standard
metrics. We also present the first dense captioning results on the
TACoS-MultiLevel dataset.


  The leading spectrographs used for exoplanets' sceince offer online data
reduction softwares (DRS) that yield as an ancillary result the full-width at
half-maximum (FWHM) of the cross-correlation function (CCF) that is used to
estimate the radial velocity of the host star. The FWHM also contains
information on the stellar projected rotational velocity vsini We wanted to
establish a simple relationship to derive the vsini directly from the FWHM
computed by the HARPS-N DRS in the case of slow-rotating solar-like stars. This
may also help to recover the stellar inclination i, which in turn affects the
exoplanets' parameters. We selected stars with an inclination of the spin axis
compatible with 90 deg by looking at exoplanetary transiting systems with known
small sky-projected obliquity: for these stars, we can presume that vsini is
equal to stellar equatorial velocity veq. We derived their rotational periods
from photometric time-series and their radii from SED fitting. This allowed us
to recover their veq, which we could compare to the FWHM values of the CCFs
obtained both with G2 and K5 spectral type masks. We obtained an empirical
relation for each mask, useful for slow rotators (FWHM < 20 km/s). We applied
them to 273 exoplanet-host stars observed with HARPS-N, obtaining homogeneous
vsini measurements. We compared our results with the literature ones to confirm
the reliability of our work, and we found a good agreement with the values
found with more sophisticated methods for stars with log g > 3.5. We also tried
our relations on HARPS and SOPHIE data, and we conclude that they can be used
also on FWHM derived by HARPS DRS with G2 and K5 mask, and they may be adapted
to the SOPHIE data as long as the spectra are taken in the high-resolution
mode. We were also able to recover or constrain i for 12 objects with no prior
vsini estimation.


  The algebraic method of renormalization is applied to the standard model of
electroweak interactions. We present the most important modifications compared
to theories with simple groups.


  We construct three-dimensional N=1 QED with N_f flavors using branes of type
IIB string theory. This theory has a mirror, which can be realized using the
S-dual brane configuration. As in examples with more supersymmetry, the Higgs
branch of the original theory gets mapped into the Coulomb branch of the
mirror. We use parity invariance to argue that these branches cannot be lifted
by quantum corrections.


  Astrophysical images issued from different instruments and/or spectral bands
often require to be processed together, either for fitting or comparison
purposes. However each image is affected by an instrumental response, also
known as PSF, that depends on the characteristics of the instrument as well as
the wavelength and the observing strategy. Given the knowledge of the PSF in
each band, a straightforward way of processing images is to homogenise them all
to a target PSF using convolution kernels, so that they appear as if they had
been acquired by the same instrument. We propose an algorithm that generates
such PSF-matching kernels, based on Wiener filtering with a tunable
regularisation parameter. This method ensures all anisotropic features in the
PSFs to be taken into account. We compare our method to existing procedures
using measured Herschel/PACS and SPIRE PSFs and simulated JWST/MIRI PSFs.
Significant gains up to two orders of magnitude are obtained with respect to
the use of kernels computed assuming Gaussian or circularised PSFs.


  A recent burst of dynamic single-cell growth-division data makes it possible
to characterize the stochastic dynamics of cell division control in bacteria.
Different modeling frameworks were used to infer specific mechanisms from such
data, but the links between frameworks are poorly explored, with relevant
consequences for how well any particular mechanism can be supported by the
data. Here, we describe a simple and generic framework in which two common
formalisms can be used interchangeably: (i) a continuous-time division process
described by a hazard function and (ii) a discrete-time equation describing
cell size across generations (where the unit of time is a cell cycle). In our
framework, this second process is a discrete-time Langevin equation with a
simple physical analogue. By perturbative expansion around the mean initial
size (or inter-division time), we show explicitly how this framework describes
a wide range of division control mechanisms, including combinations of time and
size control, as well as the constant added size mechanism recently found to
capture several aspects of the cell division behavior of different bacteria. As
we show by analytical estimates and numerical simulation, the available data
are characterized with great precision by the first-order approximation of this
expansion. Hence, a single dimensionless parameter defines the strength and the
action of the division control. However, this parameter may emerge from several
mechanisms, which are distinguished only by higher-order terms in our
perturbative expansion. An analytical estimate of the sample size needed to
distinguish between second-order effects shows that this is larger than what is
available in the current datasets. These results provide a unified framework
for future studies and clarify the relevant parameters at play in the control
of cell division.


  Using the MIRI/MRS spectrometer on JWST, we have detected pure rotational,
suprathermal OH emissions from the vicinity of the intermediate-mass protostar
HOPS 370 (OMC2/FIR3). These emissions are observed from shocked knots in a
jet/outflow, and originate in states of rotational quantum number as high as 46
that possess excitation energies as large as $E_U/k = 4.65 \times 10^4$ K. The
relative strengths of the observed OH lines provide a powerful diagnostic of
the ultraviolet radiation field in a heavily-extinguished region ($A_V \sim 10
- 20$) where direct UV observations are impossible. To high precision, the OH
line strengths are consistent with a picture in which the suprathermal OH
states are populated following the photodissociation of water in its $\tilde B
- X$ band by ultraviolet radiation produced by fast ($\sim 80\,\rm km\,s^{-1}$)
shocks along the jet. The observed dominance of emission from symmetric
($A^\prime$) OH states over that from antisymmetric ($A^{\prime\prime}$) states
provides a distinctive signature of this particular population mechanism.
Moreover, the variation of intensity with rotational quantum number suggests
specifically that Ly$\alpha$ radiation is responsible for the photodissociation
of water, an alternative model with photodissociation by a 10$^4$ K blackbody
being disfavored at a high level of significance. Using measurements of the
Br$\alpha$ flux to estimate the Ly$\alpha$ production rate, we find that $\sim
4\%$ of the Ly$\alpha$ photons are absorbed by water. Combined with direct
measurements of water emissions in the $\nu_2 = 1 -0$ band, the OH observations
promise to provide key constraints on future models for the diffusion of
Ly$\alpha$ photons in the vicinity of a shock front.


  Parallel jobs are different from sequential jobs and require a different type
of process management. We present here a process management system for parallel
programs such as those written using MPI. A primary goal of the system, which
we call MPD (for multipurpose daemon), is to be scalable. By this we mean that
startup of interactive parallel jobs comprising thousands of processes is
quick, that signals can be quickly delivered to processes, and that stdin,
stdout, and stderr are managed intuitively. Our primary target is parallel
machines made up of clusters of SMPs, but the system is also useful in more
tightly integrated environments. We describe how MPD enables much faster
startup and better runtime management of parallel jobs. We show how close
control of stdio can support the easy implementation of a number of convenient
system utilities, even a parallel debugger. We describe a simple but general
interface that can be used to separate any process manager from a parallel
library, which we use to keep MPD separate from MPICH.


  With the increasing multimedia information, multimodal recommendation has
received extensive attention. It utilizes multimodal information to alleviate
the data sparsity problem in recommendation systems, thus improving
recommendation accuracy. However, the reliance on labeled data severely limits
the performance of multimodal recommendation models. Recently, self-supervised
learning has been used in multimodal recommendations to mitigate the label
sparsity problem. Nevertheless, the state-of-the-art methods cannot avoid the
modality noise when aligning multimodal information due to the large
differences in the distributions of different modalities. To this end, we
propose a Multi-level sElf-supervised learNing for mulTimOdal Recommendation
(MENTOR) method to address the label sparsity problem and the modality
alignment problem. Specifically, MENTOR first enhances the specific features of
each modality using the graph convolutional network (GCN) and fuses the visual
and textual modalities. It then enhances the item representation via the item
semantic graph for all modalities, including the fused modality. Then, it
introduces two multilevel self-supervised tasks: the multilevel cross-modal
alignment task and the general feature enhancement task. The multilevel
cross-modal alignment task aligns each modality under the guidance of the ID
embedding from multiple levels while maintaining the historical interaction
information. The general feature enhancement task enhances the general feature
from both the graph and feature perspectives to improve the robustness of our
model. Extensive experiments on three publicly available datasets demonstrate
the effectiveness of our method. Our code is publicly available at
https://github.com/Jinfeng-Xu/MENTOR.


  The purpose of this paper is to develop a suitable notion of continuous
L_infinity morphism between DG Lie algebras, and to study twists of such
morphisms.


  We summarize several results based on the velocity data-set for cluster
galaxies provided by ENACS (the ESO Nearby Abell Cluster Survey). We describe
the distribution of velocity dispersions of a complete sample of rich galaxy
clusters, and compare it to the distribution of cluster X-ray temperatures, and
with predictions of theoretical models. We then address the issue of the
existence of a Fundamental Plane (FP) for rich clusters, first suggested by
Schaeffer et al. We confirm the existence of this FP with the ENACS data-set.
The cluster FP is different from the FP of elliptical galaxies, and from the
virial prediction. Some implications of the cluster FP are discussed. Finally,
we describe the phase-space distributions of different populations of cluster
galaxies. Different galaxy classes are defined according to their morphological
or spectral type, and the presence of emission-lines. Star-forming (late-type)
galaxies have a velocity dispersion profile that (in combination with their
wider spatial distribution) is suggestive of first infall into the cluster. On
the contrary, quiescent (early-type) galaxies show evidence of a dynamically
relaxed distribution.


  The identification of relevance with little textual context is a primary
challenge in passage retrieval. We address this problem with a
representation-based ranking approach that: (1) explicitly models the
importance of each term using a contextualized language model; (2) performs
passage expansion by propagating the importance to similar terms; and (3)
grounds the representations in the lexicon, making them interpretable. Passage
representations can be pre-computed at index time to reduce query-time latency.
We call our approach EPIC (Expansion via Prediction of Importance with
Contextualization). We show that EPIC significantly outperforms prior
importance-modeling and document expansion approaches. We also observe that the
performance is additive with the current leading first-stage retrieval methods,
further narrowing the gap between inexpensive and cost-prohibitive passage
ranking approaches. Specifically, EPIC achieves a MRR@10 of 0.304 on the
MS-MARCO passage ranking dataset with 78ms average query latency on commodity
hardware. We also find that the latency is further reduced to 68ms by pruning
document representations, with virtually no difference in effectiveness.


  We report on a study of all major solar eruptions that occurred on the
front-side of the Sun during the rise to peak phase of cycle 24 (first 62
months) in order to understand the key factors affecting the occurrence of
large solar energetic particle events (SEPs) and the ground levels enhancement
(GLE) events. The eruptions involve major flares with soft X-ray peak flux >/=
5.0 x10-5 Wm-2 (i.e., flare size >/= M5.0) and accompanying coronal mass
ejections (CMEs). The selection criterion was based on the fact that the only
front-side GLE in cycle 24 (GLE 71) had a flare size of M5.1. Only ~37% of the
major eruptions from the western hemisphere resulted in large SEP events.
Almost the same number of large SEP events was produced in weaker eruptions
(flare size <M5.0), suggesting that the soft X-ray flare is not a good
indicator of SEP or GLE events. On the other hand, the CME speed is a better
indicator of SEP and GLE events because it is consistently high supporting the
shock acceleration mechanism for SEPs and GLEs. We found the CME speed,
magnetic connectivity to Earth, and ambient conditions as the main factors that
contribute to the lack of high energy particle events during cycle 24. Several
eruptions poorly connected to Earth (eastern-hemisphere or behind-the-west-limb
events) resulted in very large SEP events detected by the STEREO spacecraft.
Some very fast CMEs, likely to have accelerated particles to GeV energies, did
not result in a GLE event because of poor latitudinal connectivity. The
stringent latitudinal requirement suggests that the highest energy particles
are likely accelerated in the nose part of shocks. There were also
well-connected fast CMEs, which did not seem to have accelerated high energy
particles due to possible unfavorable ambient conditions (high Alfven speed,
overall reduction in acceleration efficiency in cycle 24).


  We study the off-equilibrium critical dynamics of the three dimensional
diluted Ising model. We compute the dynamical critical exponent $z$ and we show
that it is independent of the dilution only when we take into account the
scaling-corrections to the dynamics. Finally we will compare our results with
the experimental data.


  The angular power spectrum and polarization of the cosmic microwave
background radiation (CMB), the relative abundances of primordial hydrogen,
deuterium and helium isotopes, and the large-scale structure of the universe
all indicate that 4.5% of the current mass density of the universe consists of
baryons. However, only a small fraction of these baryons can be accounted for
in stars and gas inside galaxies, galaxy groups and galaxy clusters, and in
spectral-line absorbing gas in the intergalactic medium (IGM). Too hot to show
up in Lyman-absorption, too cool to cause detectable spectral distortions of
the cosmic microwave background radiation, and too diffused to emit detectable
X-rays, about 90% of the cosmic baryons remain missing in the local universe
(redshift z~0). Here, we report on prevalent, isotropic, source independent,
and fairly uniform soft X-ray absorption along the lines of sight to high-z
gamma-ray bursts (GRBs) and quasars. It has the magnitude, redshift and energy
dependence that are expected from a hot IGM that contains the missing
cosmological baryons and has a mean metallicity similar to that in the
intracluster medium (ICM) of galaxy clusters.


  A detailed derivation from first principles is given for the unambiguous and
slice-independent formula for the two-loop superstring chiral measure which was
announced in the first paper of this series. Supergeometries are projected onto
their super period matrices, and the integration over odd supermoduli is
performed by integrating over the fibers of this projection. The subtleties
associated with this procedure are identified. They require the inclusion of
some new finite-dimensional Jacobian superdeterminants, a deformation of the
worldsheet correlation functions using the stress tensor, and perhaps
paradoxically, another additional gauge choice, ``slice \hat\mu choice'', whose
independence also has to be established. This is done using an important
correspondence between superholomorphic notions with respect to a supergeometry
and holomorphic notions with respect to its super period matrix. Altogether,
the subtleties produce precisely the corrective terms which restore the
independence of the resulting gauge-fixed formula under infinitesimal changes
of gauge-slice. This independence is a key criterion for any gauge-fixed
formula and hence is verified in detail.


  Measurements of electroweak precision observables at future electron-positron
colliders, such as the CEPC, FCC-ee, and ILC, will be sensitive to physics at
multi-TeV scales. To achieve this sensitivity, precise predictions for the
Standard Model expectations of these observables are needed, including
corrections at the three- and four-loop level. In this article, results are
presented for the calculation of a subset of three-loop mixed electroweak-QCD
corrections, stemming from diagrams with a gluon exchange and two closed
fermion loops. The numerical impact of these corrections is illustrated for a
number of applications: the prediction of the W-boson mass from the Fermi
constant, the effective weak mixing angle, and the partial and total widths of
the Z boson. Two alternative renormalization schemes for the top-quark mass are
considered, on-shell and $\overline{\mbox{MS}}$.


  Recent studies on semantic communication commonly rely on neural network (NN)
based transceivers such as deep joint source and channel coding (DeepJSCC).
Unlike traditional transceivers, these neural transceivers are trainable using
actual source data and channels, enabling them to extract and communicate
semantics. On the flip side, each neural transceiver is inherently biased
towards specific source data and channels, making different transceivers
difficult to understand intended semantics, particularly upon their initial
encounter. To align semantics over multiple neural transceivers, we propose a
distributed learning based solution, which leverages split learning (SL) and
partial NN fine-tuning techniques. In this method, referred to as SL with layer
freezing (SLF), each encoder downloads a misaligned decoder, and locally
fine-tunes a fraction of these encoder-decoder NN layers. By adjusting this
fraction, SLF controls computing and communication costs. Simulation results
confirm the effectiveness of SLF in aligning semantics under different source
data and channel dissimilarities, in terms of classification accuracy,
reconstruction errors, and recovery time for comprehending intended semantics
from misalignment.


  An automorphism $\alpha$ of a group $G$ is called a commuting automorphism if
each element $x$ in $G$ commutes with its image $\alpha(x)$ under $\alpha$. Let
$A(G)$ denote the set of all commuting automorphisms of $G$. Rai [Proc. Japan
Acad., Ser. A {\bf 91} (2015), no. 5, 57-60] has given some sufficient
conditions on a finite $p$-group $G$ such that $A(G)$ is a subgroup of Aut$(G)$
and, as a consequence, has proved that in a finite $p$-group $G$ of co-class 2,
where $p$ is an odd prime, $A(G)$ is a subgroup of Aut$(G)$. We give here very
elementary and short proofs of main results of Rai.


  In cosmological context, classical scalar fields are important ingredients
for inflation models, many candidate models of dark energy, symmetry breaking
and phase transition epochs, and their consequences such as baryo and
lepto-genesis. We investigate the formation of these fields by studying the
production of a light quantum scalar field during the decay of a heavy
particle. For simplicity it is assumed to be a scalar too. We discuss the
effects of the decay mode, the thermodynamical state of the decaying field,
boundary conditions, and related physical parameters on the production and
evolution of a condensate. For a simplified version of this model we calculate
the asymptotic behaviour of the condensate and conditions for its contribution
to the dark energy with an equation of state close to a cosmological constant.
We also discus the role of the back-reaction from interactions with other
fields and expansion of the Universe on the evolution of the condensate.


  Off-diagonal upper bounds are established away from the diagonal for the
Bergman kernels associated to high powers of holomorphic line bundles over
compact complex manifolds, asymptotically as the power tends to infinity. The
line bundle is assumed to be equipped with a Hermitian metric with positive
curvature form, which is infinitely differentiable but not necessarily real
analytic. The bounds obtained are the best possible for this class of metrics.


  The nonequivariant coherent-costructible correspondence is a
microlocal-geometric interpretation of homological mirror symmetry for toric
varieties conjectured by Fang-Liu-Treumann-Zaslow. We prove a generalization of
this conjecture for a class of toric stacks which includes any toric varieties
and toric orbifolds. Our proof is based on gluing descriptions of
$\infty$-categories of both sides.


  Fluctuations in the brightness of the background radiation can lead to
confusion with real point sources. Such background emission confusion will be
important for infrared observations with relatively large beam sizes since the
amount of fluctuation tends to increase with angular scale. In order to
quantitively assess the effect of the background emission on the detection of
point sources for current and future far-infrared observations by space-borne
missions such as Spitzer, ASTRO-F, Herschel and SPICA, we have extended the
Galactic emission map to higher angular resolution than the currently available
data. Using this high resolution map, we estimate the sky confusion noise due
to the emission from interstellar dust clouds or cirrus, based on fluctuation
analysis and detailed photometry over realistically simulated images. We find
that the confusion noise derived by simple fluctuation analysis agrees well
with the result from realistic simulations. Although the sky confusion noise
becomes dominant in long wavelength bands (> 100 um) with 60 - 90cm aperture
missions, it is expected to be two order of magnitude smaller for the next
generation space missions with larger aperture sizes such as Herschel and
SPICA.


  Recently, live streaming platforms have gained immense popularity.
Traditional video highlight detection mainly focuses on visual features and
utilizes both past and future content for prediction. However, live streaming
requires models to infer without future frames and process complex multimodal
interactions, including images, audio and text comments. To address these
issues, we propose a multimodal transformer that incorporates historical
look-back windows. We introduce a novel Modality Temporal Alignment Module to
handle the temporal shift of cross-modal signals. Additionally, using existing
datasets with limited manual annotations is insufficient for live streaming
whose topics are constantly updated and changed. Therefore, we propose a novel
Border-aware Pairwise Loss to learn from a large-scale dataset and utilize user
implicit feedback as a weak supervision signal. Extensive experiments show our
model outperforms various strong baselines on both real-world scenarios and
public datasets. And we will release our dataset and code to better assess this
topic.


  In two preceding papers we have shown that, when reaction networks are
well-removed from equilibrium, explicit asymptotic and quasi-steady-state
approximations can give algebraically-stabilized integration schemes that rival
standard implicit methods in accuracy and speed for extremely stiff systems.
However, we also showed that these explicit methods remain accurate but are no
longer competitive in speed as the network approaches equilibrium. In this
paper we analyze this failure and show that it is associated with the presence
of fast equilibration timescales that neither asymptotic nor quasi-steady-state
approximations are able to remove efficiently from the numerical integration.
Based on this understanding, we develop a partial equilibrium method to deal
effectively with the approach to equilibrium and show that explicit asymptotic
methods, combined with the new partial equilibrium methods, give an integration
scheme that plausibly can deal with the stiffest networks, even in the approach
to equilibrium, with accuracy and speed competitive with that of implicit
methods. Thus we demonstrate that such explicit methods may offer alternatives
to implicit integration of even extremely stiff systems, and that these methods
may permit integration of much larger networks than have been possible before
in a number of fields.


  In this paper we discuss the spin-equilibrium of accreting neutron stars in
LMXBs. We demonstrate that, when combined with a naive spin-up torque, the
observed data leads to inferred magnetic fields which are at variance with
those of galactic millisecond radiopulsars. This indicates the need for either
additional spin-down torques (eg. gravitational radiation) or an improved
accretion model. We show that a simple consistent accretion model can be
arrived at by accounting for radiation pressure in rapidly accreting systems
(above a few percent of the Eddington accretion rate). In our model the inner
disk region is thick and significantly sub-Keplerian, and the estimated
equilibrium periods are such that the LMXB neutron stars have properties that
accord well with the galactic millisecond radiopulsar sample. The implications
for future gravitational-wave observations are also discussed briefly.


  We compute the index and associated spectral density for fluctuation
operators which are defined via the Lagrangian of N=2 SQCD in the background of
non-abelian confined multimonopoles. To this end we generalize the standard
index calculations of Callias and Weinberg to the case of asymptotically
nontrivial backgrounds. The resulting index is determined by topological
charges. We conjecture that this index counts one quarter of the dimension of
the moduli space of confined multimonopoles.


  The aim of this work is to make a further step towards the understanding of
the near-critical reflection of internal gravity waves from a slope in the more
general and realistic context where the size of viscosity $\nu$ and the size of
diffusivity $\kappa$ are different. In particular, we provide a systematic
characterization of boundary layers (boundary layer wave packets) decays and
sizes depending on the order of magnitude of viscosity and diffusivity. We can
construct an $L^2$ stable approximate solution to the linear near-critical
reflection problem under the scaling assumption of Dauxois \& Young JFM 1999,
where either viscosity of diffusivity satisfies a precise scaling law in terms
of the criticality parameter.