  We present an analysis of a new, large sample of field blue-straggler stars
(BSSs) in the thick disk and halo system of the Galaxy, based on stellar
spectra obtained during the Sloan Digital Sky Survey (SDSS) and the Sloan
Extension for Galactic Understanding and Exploration (SEGUE). Using estimates
of stellar atmospheric parameters obtained from application of the SEGUE
Stellar Parameter Pipeline, we obtain a sample of some 8000 BSSs, which are
considered along with a previously selected sample of some 4800 blue
horizontal-branch (BHB) stars. We derive the ratio of BSSs to BHB stars,
F$_{\rm BSS/BHB}$, as a function of Galactocentric distance and distance from
the Galactic plane. The maximum value found for F$_{\rm BSS/BHB}$ is $\sim~$4.0
in the thick disk (at 3 kpc $<$ $|$Z$|$ $<$ 4 kpc), declining to on the order
of $\sim~1.5-2.0$ in the inner-halo region; this ratio continues to decline to
$\sim~$1.0 in the outer-halo region. We associate a minority of field BSSs with
a likely extragalactic origin; at least 5$\%$ of the BSS sample exhibit radial
velocities, positions, and distances commensurate with membership in the
Sagittarius Stream.


  Richmond and Richmond (Amer. Math. Monthly 104 (1997), 713--719) proved the
following theorem: If, in a metric space with at least five points, all
triangles are degenerate, then the space is isometric to a subset of the real
line. We prove that the hypothesis is unnecessarily strong: In fact,
$\Theta(n^2)$ suitably placed degenerate triangles suffice.


  We consider the problem of Reinforcement Learning for nonlinear stochastic
dynamical systems. We show that in the RL setting, there is an inherent ``Curse
of Variance" in addition to Bellman's infamous ``Curse of Dimensionality", in
particular, we show that the variance in the solution grows
factorial-exponentially in the order of the approximation. A fundamental
consequence is that this precludes the search for anything other than ``local"
feedback solutions in RL, in order to control the explosive variance growth,
and thus, ensure accuracy. We further show that the deterministic optimal
control has a perturbation structure, in that the higher order terms do not
affect the calculation of lower order terms, which can be utilized in RL to get
accurate local solutions.


  Dissolved ions can alter the local permittivity of water, nevertheless most
theories and simulations ignore this fact. We present a novel algorithm for
treating spatial and temporal variations in the permittivity and use it to
measure the equivalent conductivity of a salt-free polyelectrolyte solution.
Our new approach quantitatively reproduces experimental results unlike
simulations with a constant permittivity that even qualitatively fail to
describe the data. We can relate this success to a change in the ion
distribution close to the polymer due to the built-up of a permittivity
gradient.


  In our recent paper, we studied periodic billiard trajectories in the regular
pentagon and closed geodesic on the double pentagon, a translation surface of
genus two. In particular, we made a number of conjectures concerning symbolic
periodic trajectories. In this paper, we prove two of these conjectures.


  A parafermionic conformal theory with the symmetry Z_5 is constructed, based
on the second solution of Fateev-Zamolodchikov for the corresponding
parafermionic chiral algebra.
  The primary operators of the theory, which are the singlet, doublet 1,
doublet 2, and disorder operators, are found to be accommodated by the weight
lattice of the classical Lie algebra B_2. The finite Kac tables for unitary
theories are defined and the formula for the conformal dimensions of primary
operators is given.


  Vaccine hesitancy continues to be a main challenge for public health
officials during the COVID-19 pandemic. As this hesitancy undermines vaccine
campaigns, many researchers have sought to identify its root causes, finding
that the increasing volume of anti-vaccine misinformation on social media
platforms is a key element of this problem. We explored Twitter as a source of
misleading content with the goal of extracting overlapping cultural and
political beliefs that motivate the spread of vaccine misinformation. To do
this, we have collected a data set of vaccine-related Tweets and annotated them
with the help of a team of annotators with a background in communications and
journalism. Ultimately we hope this can lead to effective and targeted public
health communication strategies for reaching individuals with anti-vaccine
beliefs. Moreover, this information helps with developing Machine Learning
models to automatically detect vaccine misinformation posts and combat their
negative impacts. In this paper, we present Vax-Culture, a novel Twitter
COVID-19 dataset consisting of 6373 vaccine-related tweets accompanied by an
extensive set of human-provided annotations including vaccine-hesitancy stance,
indication of any misinformation in tweets, the entities criticized and
supported in each tweet and the communicated message of each tweet. Moreover,
we define five baseline tasks including four classification and one sequence
generation tasks, and report the results of a set of recent transformer-based
models for them. The dataset and code are publicly available at
https://github.com/mrzarei5/Vax-Culture.


  The effect from quark masses and transversal motion on the Gottfried,
Bjorken, and Ellis-Jaffe sum rules is examined by using a quark-parton model of
nucleon structure functions based on an improved scaling variable. Its use
results in corrections to the Gottfried, Bjorken, and Ellis-Jaffe sum rules. We
use the Brodsky-Huang-Lepage prescription of light-cone wavefunctions to
estimate the size of the corrections. We constrain our choice of parameters by
the roughly known higher twist corrections to the Bjorken sum rule and find
that the resulting corrections to the Gottfried and Ellis-Jaffe sum rules are
relevant, though not large enough to explain the observed sum rule violations.


  We propose a general method to analytically solve transport equations during
a cosmic phase transition without making approximations based on the assumption
that any transport coefficient is large. Using the MSSM as an example we derive
the solutions to a set of $3$ transport equations derived under the assumption
of supergauge equilibrium and the diffusion approximation. The result is then
rederived efficiently using a technique we present involving a parametrized
ansatz which turns the process of deriving a solution into an almost elementary
problem. We then show how both the derivation and the parametrized ansatz
technique can be generalized to solve an arbitrary number of transport
equations. Finally we derive a perturbative series that relaxes the usual
approximation that inactivates VEV dependent relaxation and CP violating source
terms at the bubble wall and through the symmetric phase.


  We investigate a higher-group structure of massless axion electrodynamics in
$(3+1)$ dimensions. By using the background gauging method, we show that the
higher-form symmetries necessarily have a global semistrict 3-group (2-crossed
module) structure, and exhibit 't Hooft anomalies of the 3-group. In
particular, we find a cubic mixed 't Hooft anomaly between 0-form and 1-form
symmetries, which is specific to the higher-group structure.


  We show that the ideas related to integrability and symmetry play an
important role not only in the string T-duality story but also in its point
particle counterpart. Applying those ideas, we find that the T-duality seems to
be a more widespread phenomenon in the context of the point particle dynamics
than it is in the string one; moreover, it concerns physically very relevant
point particle dynamical systems and not just somewhat exotic ones fabricated
for the purpose. As a source of T-duality examples, we consider maximally
superintegrable spherically symmetric electro-gravitational backgrounds in $n$
dimensions. We then describe in detail four such spherically symmetric
dynamical systems which are all mutually interconnected by a web of point
particle T-dualities. In particular, the dynamics of a charged particle
scattered by a repulsive Coulomb potential in a flat space is T-dual to the
dynamics of the Coulomb scattering in the space of constant negative curvature,
but it is also T-dual to the (conformal) Calogero-Moser inverse square dynamics
both in flat and hyperbolic spaces. Thus knowing just the Hamiltonian dynamics
of the scattered particle cannot give us an information about the curvature of
the space in which the particle moves.


  We explore using the Suggested Upper Merged Ontology (SUMO) to develop a
semantic simulation. We provide two proof-of-concept demonstrations modeling
transitions in a simulated gasoline engine using a general-purpose programming
language. Rather than focusing on computationally highly intensive techniques,
we explore a less computationally intensive approach related to familiar
software engineering testing procedures. In addition, we propose structured
representations of terms based on linguistic approaches to lexicography.


  A General Underwater Object Detector (GUOD) should perform well on most of
underwater circumstances. However, with limited underwater dataset,
conventional object detection methods suffer from domain shift severely. This
paper aims to build a GUOD with small underwater dataset with limited types of
water quality. First, we propose a data augmentation method Water Quality
Transfer (WQT) to increase domain diversity of the original small dataset.
Second, for mining the semantic information from data generated by WQT, DG-YOLO
is proposed, which consists of three parts: YOLOv3, DIM and IRM penalty.
Finally, experiments on original and synthetic URPC2019 dataset prove that
WQT+DG-YOLO achieves promising performance of domain generalization in
underwater object detection.


  Comprehensive results on the production of unidentified charged particles,
$\pi^{\pm}$, $\rm{K}^{\pm}$, $\rm{K}^{0}_{S}$, $\rm{K}$*(892)$^{0}$, $\rm{p}$,
$\overline{\rm{p}}$, $\phi$(1020), $\Lambda$, $\overline{\Lambda}$, $\Xi^{-}$,
$\overline{\Xi}^{+}$, $\Omega^{-}$ and $\overline{\Omega}^{+}$ hadrons in
proton-proton (pp) collisions at $\sqrt{s}$ = 7 TeV at midrapidity ($|y| <
0.5$) as a function of charged-particle multiplicity density are presented. In
order to avoid auto-correlation biases, the actual transverse momentum
($p_{\rm{T}}$) spectra of the particles under study and the event activity are
measured in different rapidity windows. In the highest multiplicity class, the
charged-particle density reaches about 3.5 times the value measured in
inelastic collisions. While the yield of protons normalized to pions remains
approximately constant as a function of multiplicity, the corresponding ratios
of strange hadrons to pions show a significant enhancement that increases with
increasing strangeness content. Furthermore, all identified particle to pion
ratios are shown to depend solely on charged-particle multiplicity density,
regardless of system type and collision energy. The evolution of the spectral
shapes with multiplicity and hadron mass shows patterns that are similar to
those observed in p-Pb and Pb-Pb collisions at LHC energies. The obtained
$p_{\rm{T}}$ distributions and yields are compared to expectations from
QCD-based pp event generators as well as to predictions from thermal and
hydrodynamic models. These comparisons indicate that traces of a collective,
equilibrated system are already present in high-multiplicity pp collisions.


  Quantum random number generators (QRNG) based on continuous variable (CV)
quantum fluctuations offer great potential for their advantages in measurement
bandwidth, stability and integrability. More importantly, it provides an
efficient and extensible path for significant promotion of QRNG generation
rate. During this process, real-time randomness extraction using information
theoretically secure randomness extractors is vital, because it plays critical
role in the limit of throughput rate and implementation cost of QRNGs. In this
work, we investigate parallel and real-time realization of several
Toeplitz-hashing extractors within one field-programmable gate array (FPGA) for
parallel QRNG. Elaborate layout of Toeplitz matrixes and efficient utilization
of hardware computing resource in the FPGA are emphatically studied. Logic
source occupation for different scale and quantity of Toeplitz matrices is
analyzed and two-layer parallel pipeline algorithm is delicately designed to
fully exploit the parallel algorithm advantage and hardware source of the FPGA.
This work finally achieves a real-time post-processing rate of QRNG above 8
Gbps. Matching up with integrated circuit for parallel extraction of multiple
quantum sideband modes of vacuum state, our demonstration shows an important
step towards chip-based parallel QRNG, which could effectively improve the
practicality of CV QRNGs, including device trusted, device-independent, and
semi-device-independent schemes.


  We investigate the following quasilinear parabolic and singular equation,
  {equation} \tag{{\rm P$_t$}} \{{aligned} & u_t-\Delta_p u
=\frac{1}{u^\delta}+f(x,u)\;\text{in}\,(0,T)\times\Omega, & u =0\,\text{on}
\;(0,T)\times\partial\Omega,\quad u>0 \text{in}\, (0,T)\times\Omega, &u(0,x)
=u_0(x)\;\text{in}\Omega, {aligned}. {equation} % where $\Omega$ is an open
bounded domain with smooth boundary in $\R^{\rm N}$, $1 < p< \infty$,
$0<\delta$ and $T>0$. We assume that $(x,s)\in\Omega\times\R^+\to f(x,s)$ is a
bounded below Caratheodory function, locally Lipschitz with respect to $s$
uniformly in $x\in\Omega$ and asymptotically sub-homogeneous, i.e. % {equation}
\label{sublineargrowth} 0 \leq\displaystyle\lim_{t\to
+\infty}\frac{f(x,t)}{t^{p-1}}=\alpha_f<\lambda_1(\Omega), {equation} % (where
$\lambda_1(\Omega)$ is the first eigenvalue of $-\Delta_p$ in $\Omega$ with
homogeneous Dirichlet boundary conditions) and $u_0\in L^\infty(\Omega)\cap
W^{1,p}_0(\Omega)$, satisfying a cone condition defined below. Then, for any
$\delta\in (0,2+\frac{1}{p-1})$, we prove the existence and the uniqueness of a
weak solution $u \in{\bf V}(Q_T)$ to $({\rm P_t})$. Furthermore, $u\in C([0,T],
W^{1,p}_0(\Omega))$ and the restriction $\delta<2+\frac{1}{p-1}$ is sharp.
Finally, in the last section we analyse the case $p=2$. Using the interpolation
spaces theory and the semigroup theory, we prove the existence and the
uniqueness of weak solutions to $({\rm P}_t)$ for any $\delta>0$ in $C([0,T],
L^2(\Omega))\cap L^\infty(Q_T)$ and under suitable assumptions on the initial
data we give additional regularity results. Finally, we describe their
asymptotic behaviour in $L^\infty(\Omega)\cap H^1_0(\Omega)$ when $\delta<3$.


  In this paper, we give an approach to the zeta values of a (proper regular)
arithmetic scheme X at the integers r>=d:=dim(X), using \'etale cohomology of X
with Q_p(r) and Z_p(r)-coefficients.


  We examine the evolution of highly eccentric, planet-crossing orbits in the
restricted three-body problem (Sun, planet, comet). We construct a simple
Keplerian map in which the comet energy changes instantaneously at perihelion,
by an amount depending only on the azimuthal angle between the planet and the
comet at the time of perihelion passage. This approximate but very fast mapping
allow us to explore the evolution of large ensembles of long-period comets. We
compare our results on comet evolution with those given by the diffusion
approximation and by direct integration of comet orbits. We find that at long
times the number of surviving comets is determined by resonance sticking rather
than a random walk.


  Starting from fitness correlation functions, we calculate exact expressions
for the amplitude spectra of fitness landscapes as defined by P.F. Stadler [J.
Math. Chem. 20, 1 (1996)] for common landscape models, including Kauffman's
NK-model, rough Mount Fuji landscapes and general linear superpositions of such
landscapes. We further show that correlations decaying exponentially with the
Hamming distance yield exponentially decaying spectra similar to those reported
recently for a model of molecular signal transduction. Finally, we compare our
results for the model systems to the spectra of various experimentally measured
fitness landscapes. We claim that our analytical results should be helpful when
trying to interpret empirical data and guide the search for improved fitness
landscape models.


  We discuss the hints for the disappearance of continuum space and time at
microscopic scale. These include arguments for a discrete nature of them or for
a fundamental non-locality, in a quantum theory of gravity. We discuss how
these ideas are realized in specific quantum gravity approaches. Turning then
the problem around, we consider the emergence of continuum space and time from
the collective behaviour of discrete, pre-geometric atoms of quantum space, and
for understanding spacetime as a kind of "condensate", and we present the case
for this emergence process being the result of a phase transition, dubbed
"geometrogenesis". We discuss some conceptual issues of this scenario and of
the idea of emergent spacetime in general. As a concrete example, we outline
the GFT framework for quantum gravity, and illustrate a tentative procedure for
the emergence of spacetime in this framework. Last, we re-examine the
conceptual issues raised by the emergent spacetime scenario in light of this
concrete example.


  We have measured the production rates and production cross sections for a
variety of radioactive isotopes which were produced from 124Xe, 48Ca, and 238U
beams at an energy of 345 MeV/nucleon using the BigRIPS separator at the RIKEN
Nishina Center RI Beam Factory (RIBF). Proton-rich isotopes with atomic numbers
Z = 40 to 52 and neutron-rich isotopes with Z = 5 to 16 were produced by
projectile fragmentation of the 124Xe and 48Ca beam on Be targets,
respectively. Neutron-rich isotopes with Z = 20 to 59 were produced by
in-flight fission of the 238U beam, in which both Be and Pb were used as
production targets. The measured production rates and production cross sections
were compared with those of the LISE++ calculations, and overall fairly good
agreement has been obtained. Furthermore, in the measurements with the 124Xe
beam, we have discovered four new isotopes on the proton-drip line, 85,86Ru and
81,82Mo, and obtained the clear evidence that 103Sb is particle unbound with an
upper limit of 49 ns for the half-life. The measurements of projectile-fragment
momentum distributions have been also performed with the 124Xe beam, in which
the low-momentum tails of the distributions have been measured for the first
time at the energy of 345 MeV/nucleon.


  We present timing solutions of PSR B0950+08, using 14 years of observations
at Nanshan 26-m Radio Telescope of Xinjiang Astronomical Observatory. The
braking index of PSR B0950+08 varies from --367 392 to 168 883, which shows an
oscillation with large amplitude ($\sim 10^5$) and uncertainty. Considering the
variation of braking indices and the most probable kinematic age of PSR
B0950+08, a model withe long-term magnetic field decay modulated by short-term
oscillations is proposed to explain the timing data. With this magnetic field
decay model, we discuss the spin and thermal evolution of PSR B0950+08. The
uncertainties of its age are also considered. The results show that
three-component oscillations are the more reasonable for the spin-frequency
derivative distributions of PSR B0950+08, and the initial spin period of PSR
B0950+08 must be shorter than $97\rm\ ms$ when the age is equal to the lower
bound of its kinematic age. The standard cooling model could explain the
surface temperature of PSR B0950+08 with its most probable kinematic age.
Vortex creep heating with a long-term magnetic field decay could maintain a
relatively high temperature at the later stages of evolution and explain the
thermal emission data of old and warm pulsars. Coupling with the long-term
magnetic field decay, an explanation of the temperature of PSR B0950+08 with
roto-chemical heating needs an implausibly short initial rotation period ($P_0
\lesssim 17\rm{ ms}$). The spin and thermal evolution of pulsars should be
studied simultaneously. Future timing, ultraviolet or X-ray observations are
essential for studying the evolution and interior properties of pulsars.


  Despite surveillance systems are becoming increasingly ubiquitous in our
living environment, automated surveillance, currently based on video sensory
modality and machine intelligence, lacks most of the time the robustness and
reliability required in several real applications. To tackle this issue, audio
sensory devices have been taken into account, both alone or in combination with
video, giving birth, in the last decade, to a considerable amount of research.
In this paper audio-based automated surveillance methods are organized into a
comprehensive survey: a general taxonomy, inspired by the more widespread video
surveillance field, is proposed in order to systematically describe the methods
covering background subtraction, event classification, object tracking and
situation analysis. For each of these tasks, all the significant works are
reviewed, detailing their pros and cons and the context for which they have
been proposed. Moreover, a specific section is devoted to audio features,
discussing their expressiveness and their employment in the above described
tasks. Differently, from other surveys on audio processing and analysis, the
present one is specifically targeted to automated surveillance, highlighting
the target applications of each described methods and providing the reader
tables and schemes useful to retrieve the most suited algorithms for a specific
requirement.


  We present analytical results for higher order corrections to the decay
spectra of inclusive semileptonic heavy hadron weak decays using the heavy
quark expansion (HQE). We compute analytically the spectrum of the leptonic
invariant mass for $B \rightarrow X_c \ell \bar{\nu}$ up to and including terms
of order $1/m_Q^3$ within the HQE at next-to-leading order (NLO) in $\alpha_s$.
The full dependence of the differential rate on the mass of the final-state
quark is taken into account. We discuss the implications of our results for the
precision determination of the CKM matrix element $|V_{cb}|$.


  We search for an axion-like particle (ALP) $a$ through the process
$\psi(3686)\rightarrow\pi^+\pi^-J/\psi$, $J/\psi\rightarrow\gamma a$,
$a\rightarrow\gamma\gamma$ in a data sample of $(2.71\pm0.01)\times10^9$
$\psi(3686)$ events collected by the BESIII detector. No significant ALP signal
is observed over the expected background, and the upper limits on the branching
fraction of the decay $J/\psi\rightarrow\gamma a$ and the ALP-photon coupling
constant $g_{a\gamma\gamma}$ are set at 95% confidence level in the mass range
of $0.165\leq m_a\leq2.84\,\mbox{GeV}/c^2$. The limits on
$B(J/\psi\rightarrow\gamma a)$ range from $8.3\times10^{-8}$ to
$1.8\times10^{-6}$ over the search region, and the constraints on the
ALP-photon coupling are the most stringent to date for $0.165\leq
m_a\leq1.468\,\mbox{GeV}/c^2$.


  In this work we compare different drag-reduction strategies that compute
their actuation based on the fluctuations at a given wall-normal location in
turbulent open channel flow. In order to perform this study, we implement and
describe in detail the reinforcement-learning interface to a
computationally-efficient, parallelized, high-fidelity solver for fluid-flow
simulations. We consider opposition control (Choi, Moin, and Kim, Journal of
Fluid Mechanics 262, 1994) and the policies learnt using deep reinforcement
learning (DRL) based on the state of the flow at two inner-scaled locations
($y^+ = 10$ and $y^+ = 15$). By using deep deterministic policy gradient (DDPG)
algorithm, we are able to discover control strategies that outperform existing
control methods. This represents a first step in the exploration of the
capability of DRL algorithm to discover effective drag-reduction policies using
information from different locations in the flow.


  Linear polarization angle, $\theta$, dependent measurements of the microwave
radiation-induced oscillatory magnetoresistance, $R_{xx}$, in high mobility
GaAs/AlGaAs 2D electron devices have shown a $\theta$ dependence in the
oscillatory amplitude along with magnetic field, frequency, and
extrema-dependent phase shifts, $\theta_{0}$. Here, we suggest a microwave
frequency dependence of $\theta_{0} (f)$ using an analysis that averages over
other smaller contributions, when those contributions are smaller than
estimates of the experimental uncertainty.


  Primordial black holes (PBHs) forming out of the collapse of enhanced
cosmological perturbations provide access to the early Universe through their
associated observational signatures. In particular, enhanced cosmological
perturbations collapsing to form PBHs are responsible for the generation of a
stochastic gravitational-wave background (SGWB) induced by second-order
gravitational interactions, usually called scalar induced gravitational waves
(SIGWs). This SGWB is sensitive to the underlying gravitational theory; hence
it can be used as a novel tool to test the standard paradigm of gravity and
constrain possible deviations from general relativity. In this work, we study
the aforementioned GW signal within modified teleparallel gravity theories,
developing a formalism for the derivation of the GW spectral abundance within
any form of gravitational action. At the end, working within viable $f(T,\phi)$
models without matter-gravity couplings, and accounting for the effect of
mono-parametric $f(T)$ gravity at the level of the source and the propagation
of the tensor perturbations, we show that the respective GW signal is
indistinguishable from that within GR. Interestingly, we find that in order to
break the degeneracy between different $f(T)$ theories through the portal of
SIGWs one should necessarily consider non-minimal matter-gravity couplings at
the level of the gravitational action.


  We consider energy sub-critical defocusing nonlinear wave equations on
$\mathbb{R}^3$ and establish the existence of unique global solutions almost
surely with respect to a unit-scale randomization of the initial data on
Euclidean space. In particular, we provide examples of initial data at
super-critical regularities which lead to unique global solutions. The proof is
based on probabilistic growth estimates for a new modified energy functional.
This work improves upon the authors' previous results in [25] by significantly
lowering the regularity threshold and strengthening the notion of uniqueness.


  Fluid phase behavior of charge-stabilized colloidal suspensions is explored
by applying a new variant of the Gibbs ensemble Monte Carlo simulation method
to a coarse-grained one-component model with implicit microions and solvent.
The simulations take as input linear-response approximations for effective
electrostatic interactions -- hard-sphere-Yukawa pair potential and one-body
volume energy. The conventional Gibbs ensemble trial moves are supplemented by
exchange of (implicit) salt between coexisting phases, with acceptance
probabilities influenced by the state dependence of the effective interactions.
Compared with large-scale simulations of the primitive model, with explicit
microions, our computationally practical simulations of the one-component model
closely match the pressures and pair distribution functions at moderate
electrostatic couplings. For macroion valences and couplings within the
linear-response regime, deionized aqueous suspensions with monovalent microions
exhibit separation into macroion-rich and macroion-poor fluid phases below a
critical salt concentration. The resulting pressures and phase diagrams are in
excellent agreement with predictions of a variational free energy theory based
on the same model.


  Quantum phase transitions in metals are often accompanied by violations of
Fermi liquid behavior in the quantum critical regime. Particularly fascinating
are transitions beyond the Landau-Ginzburg-Wilson concept of a local order
parameter. The breakdown of the Kondo effect in heavy-fermion metals
constitutes a prime example of such a transition. Here, the strongly correlated
f electrons become localized and disappear from the Fermi surface, implying
that the transition is equivalent to an orbital-selective Mott transition, as
has been discussed for multi-band transition-metal oxides. In this article,
available theoretical descriptions for orbital-selective Mott transitions will
be reviewed, with an emphasis on conceptual aspects like the distinction
between different low-temperature phases and the structure of the global phase
diagram. Selected results for quantum critical properties will be listed as
well. Finally, a brief overview is given on experiments which have been
interpreted in terms of orbital-selective Mott physics.


  We propose an asymmetric modification of the sand-pile-like cellular
automaton for earthquake modeling. The cumulative event distribution is shown
to be dependent on the asymmetry parameter.


  Spectral energy distributions (SEDs) from 0.4 to 4.7 microns are presented
for the two principal stellar components of HD~98800, A and B. The third major
component, an extensive planetary debris system (PDS), emits > 20% of the
luminosity of star B in a blackbody SED at 164 +/- 5K extending from mid-IR to
millimeter-wavelengths. At 0.95 microns a preliminary upper limit of < 0.06 is
obtained for the ratio of reflected light to the total from star B. This result
limits the albedo of the PDS to < 0.3. Values are presented for the
temperature, luminosity, and radius of each major systemic component.
Remarkable similarities are found between the PDS and the interplanetary debris
system around the Sun as it could have appeared a few million years after its
formation.


  Climate change has become an unavoidable problem in achieving sustainable
development. As one of the major industries worldwide, tourism can make a
significant contribution to mitigating climate change. The main objective of
the paper is to assess the development level of low-carbon tourism from
multi-aspect, using the Yellow River Basin as an example. Firstly, this study
quantified tourism carbon dioxide emissions and tourism economy, and analyzed
their evolution characteristics. The interaction and coordination degree
between tourism carbon dioxide emissions and tourism economy were then analyzed
using the improved coupling coordination degree model. Finally, this study
analyzed the change in total factor productivity of low-carbon tourism by
calculating the Malmquist-Luenberger productivity index. The results showed
that: (1) The tourism industry in the Yellow River Basin has the
characteristics of the initial environmental Kuznets curve. (2) There was a
strong interaction between tourism carbon dioxide emissions and tourism
economy, which was manifested as mutual promotion. (3) The total factor
productivity of low-carbon tourism was increasing. Based on the above results,
it could be concluded that the development level of low-carbon tourism in the
Yellow River Basin has been continuously improved from 2000 to 2019, but it is
still in the early development stage with the continuous growth of carbon
dioxide emissions.


  With the advent of the cloud computing era, the cost of creating, capturing
and managing information has gradually decreased. The amount of data in the
Internet is also showing explosive growth, and more and more scientific and
technological resources are uploaded to the network. Different from news and
social media data ubiquitous in the Internet, the main body of scientific and
technological resources is composed of academic-style resources or entities
such as papers, patents, authors, and research institutions. There is a rich
relationship network between resources, from which a large amount of
cutting-edge scientific and technological information can be mined. There are a
large number of management and classification standards for existing scientific
and technological resources, but these standards are difficult to completely
cover all entities and associations of scientific and technological resources,
and cannot accurately extract important information contained in scientific and
technological resources. How to construct a complete and accurate
representation of scientific and technological resources from structured and
unstructured reports and texts in the network, and how to tap the potential
value of scientific and technological resources is an urgent problem. The
solution is to construct accurate portraits of scientific and technological
resources in combination with knowledge graph related technologies.


  Graphs are structured data that models complex relations between real-world
entities. Heterophilous graphs, where linked nodes are prone to be with
different labels or dissimilar features, have recently attracted significant
attention and found many applications. Meanwhile, increasing efforts have been
made to advance learning from heterophilous graphs. Although there exist
surveys on the relevant topic, they focus on heterophilous GNNs, which are only
sub-topics of heterophilous graph learning. In this survey, we comprehensively
overview existing works on learning from graphs with heterophily.First, we
collect over 180 publications and introduce the development of this field.
Then, we systematically categorize existing methods based on a hierarchical
taxonomy including learning strategies, model architectures and practical
applications. Finally, we discuss the primary challenges of existing studies
and highlight promising avenues for future research.More publication details
and corresponding open-source codes can be accessed and will be continuously
updated at our
repositories:https://github.com/gongchenghua/Papers-Graphs-with-Heterophily.


  We consider the role of degeneracy in Parity-Time (PT) symmetry breaking for
non-hermitian wave equations beyond one dimension. We show that if the spectrum
is degenerate in the absence of T-breaking, and T is broken in a generic manner
(without preserving other discrete symmetries), then the standard PT-symmetry
breaking transition does not occur, meaning that the spectrum is complex even
for infinitesimal strength of gain and loss. However the realness of the entire
spectrum can be preserved over a finite interval if additional discrete
symmetries X are imposed when T is broken, if X decouple all degenerate modes.
When this is true only for a subset of the degenerate spectrum, there can be a
partial PT transition in which this subset remains real over a finite interval
of T-breaking. If the spectrum has odd-degeneracy, a fraction of the degenerate
spectrum can remain in the symmetric phase even without imposing additional
discrete symmetries, and they are analogous to dark states in atomic physics.
These results are illustrated by the example of different T-breaking
perturbations of a uniform dielectric disk and sphere, and a group theoretical
analysis is given in the disk case. Finally, we show that multimode coupling is
capable of restoring the T-symmetric phase at finite T-breaking. We also
analyze these questions when the parity operator is replaced by another spatial
symmetry operator and find that the behavior can be qualitatively different.


  Liquid scintillator detectors play a central role in the detection of
neutrinos from various sources. In particular, it is the only technique used so
far for the precision spectroscopy of sub-MeV solar neutrinos, as demonstrated
by the Borexino experiment at the Gran Sasso National Laboratory in Italy. The
benefit of a high light yield, and thus a low energy threshold and a good
energy resolution, comes at the cost of the directional information featured by
water Cherenkov detectors, measuring $^8$B solar neutrinos above a few MeV. In
this paper we provide the first directionality measurement of sub-MeV solar
neutrinos which exploits the correlation between the first few detected photons
in each event and the known position of the Sun for each event. This is also
the first signature of directionality in neutrinos elastically scattering off
electrons in a liquid scintillator target. This measurement exploits the
sub-dominant, fast Cherenkov light emission that precedes the dominant yet
slower scintillation light signal. Through this measurement, we have also been
able to extract the rate of $^{7}$Be solar neutrinos in Borexino. The
demonstration of directional sensitivity in a traditional liquid scintillator
target paves the way for the possible exploitation of the Cherenkov light
signal in future kton-scale experiments using liquid scintillator targets.
Directionality is important for background suppression as well as the
disentanglement of signals from various sources.


  We study methods for automated parsing of informal mathematical expressions
into formal ones, a main prerequisite for deep computer understanding of
informal mathematical texts. We propose a context-based parsing approach that
combines efficient statistical learning of deep parse trees with their semantic
pruning by type checking and large-theory automated theorem proving. We show
that the methods very significantly improve on previous results in parsing
theorems from the Flyspeck corpus.


  We develop a new simulation technique based on path-integral molecular
dynamics for calculating ground-state tunneling splitting patterns from ratios
of symmetrized partition functions. In particular, molecular systems are
rigorously projected onto their J = 0 rotational state by an "Eckart spring"
that connects two adjacent beads in a ring polymer. Using this procedure, the
tunneling splitting can be obtained from thermodynamic integration at just one
(sufficiently low) temperature. Converged results are formally identical to the
values that would have been obtained by solving the full rovibrational
Schr\"odinger equation on a given Born--Oppenheimer potential energy surface.
The new approach is showcased with simulations of hydronium and methanol, which
are in good agreement with wavefunction-based calculations and experimental
measurements. The method will be of particular use for the study of low-barrier
methyl rotations and other floppy modes, where instanton theory is not valid.


  A model of single photon detection, illustrated by a photon-absorbing
superfluid or superconducting microvolume, is formulated as a cascading pair of
quantum phase transitions. In the first, the microvolume transitions to the
normal state upon photon absorption, resulting in a superposition of
macrostates depending on whether the photon is absorbed or not. The second
enables subsequent "wavefunction collapse," producing a density matrix
implementing the Born probability rule. Next, EPR-type measurements on
space-like separated entangled photon pairs are considered. It is argued that
macro-entangled superposition indeed survives until such time as the component
states come into causal contact, following which the state rapidly collapses to
one or the other expected outcome. Apparent superluminal communication effects
are entirely avoided.


  An active learning procedure called Deep Potential Generator (DP-GEN) is
proposed for the construction of accurate and transferable machine
learning-based models of the potential energy surface (PES) for the molecular
modeling of materials. This procedure consists of three main components:
exploration, generation of accurate reference data, and training. Application
to the sample systems of Al, Mg and Al-Mg alloys demonstrates that DP-GEN can
produce uniformly accurate PES models with a minimal number of reference data.


  Lanthanum and yttrium compounds with composition RE2M2O7 (RE=Y, La; M = Ti,
Zr, Hf) have high density and high Z and can be doped with Ce onto the La and Y
sites. This makes these compounds good candidates for Ce activated scintillator
gamma-ray detectors particularly for the hafnate systems which have a very high
density. There is disagreement in the literature concerning La2Hf2O7:Ce as it
has been reported to show both bright as well as no Ce activated luminescence
by different experimental groups. We have performed first-principles electronic
structure calculations of these compounds doped with Ce using the
pseudopotential method based on the generalized gradient approximation in
density functional theory. The positions of the Ce 4f states relative to the
valence band maximum and the position of the Ce 5d states relative to the
conduction band minimum (CBM) of the host material are determined. We find,
unlike Ce activated La and Y compounds where the CBM is typically of La 5d or Y
4d character, that, in these systems the CBM is predominately of d character on
the Ti, Zr, Hf atoms. For all these compounds we also find that the Ce 5d state
lies above the CBM which would prevent any luminescence from the Ce site.


  Contextual bandits serve as a fundamental model for many sequential decision
making tasks. The most popular theoretically justified approaches are based on
the optimism principle. While these algorithms can be practical, they are known
to be suboptimal asymptotically. On the other hand, existing asymptotically
optimal algorithms for this problem do not exploit the linear structure in an
optimal way and suffer from lower-order terms that dominate the regret in all
practically interesting regimes. We start to bridge the gap by designing an
algorithm that is asymptotically optimal and has good finite-time empirical
performance. At the same time, we make connections to the recent literature on
when exploration-free methods are effective. Indeed, if the distribution of
contexts is well behaved, then our algorithm acts mostly greedily and enjoys
sub-logarithmic regret. Furthermore, our approach is adaptive in the sense that
it automatically detects the nice case. Numerical results demonstrate
significant regret reductions by our method relative to several baselines.


  In the supersymmetric SO(10) models, the doublet-triplet splitting problem
can be solved through the Dimopoulos-Wilczek mechanism. This mechanism is
extended in the non-renormalizable version. Improvement on the realistic model
is also made.


  Advancements in the domain of physical human-robot interaction (pHRI) have
tremendously improved the ability of humans and robots to communicate,
collaborate, and coexist. In particular, compliant robotic systems offer many
characteristics that can be leveraged towards enabling physical interactions
that more efficiently and intuitively communicate intent, making compliant
systems potentially useful in more physically demanding subsets of human-robot
collaborative scenarios. Tensegrity robots are an example of compliant systems
that are well-suited to physical interactions while still retaining useful
rigid properties that make them practical for a variety of applications. In
this paper, we present the design and preliminary testing of a 6-bar spherical
tensegrity with force-sensing capabilities. Using this prototype, we
demonstrate the ability of its force-sensor array to detect a variety of
physical interaction types that might arise in a human context. We then train
and test a series of classifiers using data from unique and representative
interactions in order to demonstrate the feasibility of using this physical
modality of sensing to reliably communicate goals and intents from a human
operator in a human-robot collaborative setting.


  Using a superfield generalization of the tadpole method, we study the
one-loop effective potential for a Wess Zumino model modified by a
higher-derivative term, inspired by the Lee-Wick model. The one-loop
K\"{a}hlerian potential is also obtained by other methods and compared with the
effective potential.


  We study the causal structure of a class of weakly nonlocal gravitational
theories (eventually coupled to matter) that are compatible with perturbative
unitarity and finiteness at quantum level. In particular, we show that in
nonlocal quantum gravity a Shapiro's time advance never occurs. Moreover, we
provide a recipe to construct a general ultraviolet complete gravitational
theory coupled to matter (with or without supersymmetry) compatible with
causality. Therefore, nonlocal gravity is consistent with causality, as well as
string theory.


  Brylawski's tensor product formula expresses the Tutte polynomial of the
tensor product of two graphs in terms of Tutte polynomials arising from the
tensor factors. We are concerned with extensions of Brylawski's tensor product
formula to the Bollobas-Riordan and transition polynomials of graphs embedded
in surfaces. We give a tensor product formula for the multimatroid transition
polynomial and show that Brylawski's formula and its topological analogues
arise as specialisations of this more general result.


  In this short note, we give the convergence analysis of the policy in the
recent famous policy mirror descent (PMD). We mainly consider the unregularized
setting following [11] with generalized Bregman divergence. The difference is
that we directly give the convergence rates of policy under generalized Bregman
divergence. Our results are inspired by the convergence of value function in
previous works and are an extension study of policy mirror descent. Though some
results have already appeared in previous work, we further discover a large
body of Bregman divergences could give finite-step convergence to an optimal
policy, such as the classical Euclidean distance.


  We define the extension group between an atom and an object in a locally
noetherian Grothendieck category as a module over a skew field. We show that
the dimension of the i-th extension group between an atom and an object
coincides with the i-th Bass number of the object with respect to the atom. As
an application, we give a bijection between the E-stable subcategories closed
under arbitrary direct sums and direct summands and the subsets of the atom
spectrum and show that such subcategories are also closed under extensions,
kernels of epimorphisms, and cokernels of monomorphisms. We show some
relationships to the theory of prime ideals in the case of noetherian algebras.


  Being dominant factors driving the human actions, personalities can be
excellent indicators in predicting the offline and online behavior of different
individuals. However, because of the great expense and inevitable subjectivity
in questionnaires and surveys, it is challenging for conventional studies to
explore the connection between personality and behavior and gain insights in
the context of large amount individuals. Considering the more and more
important role of the online social media in daily communications, we argue
that the footprint of massive individuals, like tweets in Weibo, can be the
inspiring proxy to infer the personality and further understand its functions
in shaping the online human behavior. In this study, a map from self-reports of
personalities to online profiles of 293 active users in Weibo is established to
train a competent machine learning model, which then successfully identifies
over 7,000 users as extroverts or introverts. Systematical comparisons from
perspectives of tempo-spatial patterns, online activities, emotion expressions
and attitudes to virtual honor surprisingly disclose that the extrovert indeed
behaves differently from the introvert in Weibo. Our findings provide solid
evidence to justify the methodology of employing machine learning to
objectively study personalities of massive individuals and shed lights on
applications of probing personalities and corresponding behaviors solely
through online profiles.


  Fibonacci connection between non-decreasing sequences of positive integers
producing maximum height Huffman trees and the Wythoff array has been proved.


  This volume contains the proceedings of RULE 2009: the tenth International
Workshop on Rule-Based Programming. It took place in June 28th 2009, Brasilia,
Brazil, as a satellite event of RDP 2009. The first Rule workshop was held in
Montreal in 2000, and subsequent editions took place in Firenze, Pittsburgh,
Valencia, Aachen, Nara, Seattle, Paris, and Hagenberg.


  Instability to high toroidal mode number ($n$) ballooning modes has been
proposed as the primary gradient-limiting mechanism for tokamak equilibria with
negative triangularity ($\delta$) shaping, preventing access to strong H-mode
regimes when $\delta\ll0$. To understand how this mechanism extrapolates to
reactor conditions, we model the infinite-$n$ ballooning stability as a
function of internal profiles and equilibrium shape using a combination of the
CHEASE and BALOO codes. While the critical $\delta$ required for avoiding
$2^\mathrm{nd}$ stability to high-$n$ modes is observed to depend in a
complicated way on various shaping parameters, including the equilibrium aspect
ratio, elongation and squareness, equilibria with negative triangularity are
robustly prohibited from accessing the $2^\mathrm{nd}$ stability region,
offering the prediction that that negative triangularity reactors should
maintain L-mode-like operation. In order to access high-$n$ $2^\mathrm{nd}$
stability, the local shear over the entire bad curvature region must be
sufficiently negative to overcome curvature destabilization on the low field
side. Scalings of the ballooning-limited pedestal height are provided as a
function of plasma parameters to aid future scenario design.


  We find the cross-over behavior for the spin-spin correlation function for
the 2D Ising and 3-states Potts model with random bonds at the critical point.
The procedure employed is the renormalisation approach of the perturbation
series around the conformal field theories representing the pure models. We
obtain a crossover in the amplitude for the correlation function for the Ising
model which doesn't change the critical exponent, and a shift in the critical
exponent produced by randomness in the case of the Potts model. A comparison
with numerical data is discussed briefly.


  We introduce a new Langevin dynamics based algorithm, called
e-TH$\varepsilon$O POULA, to solve optimization problems with discontinuous
stochastic gradients which naturally appear in real-world applications such as
quantile estimation, vector quantization, CVaR minimization, and regularized
optimization problems involving ReLU neural networks. We demonstrate both
theoretically and numerically the applicability of the e-TH$\varepsilon$O POULA
algorithm. More precisely, under the conditions that the stochastic gradient is
locally Lipschitz in average and satisfies a certain convexity at infinity
condition, we establish non-asymptotic error bounds for e-TH$\varepsilon$O
POULA in Wasserstein distances and provide a non-asymptotic estimate for the
expected excess risk, which can be controlled to be arbitrarily small. Three
key applications in finance and insurance are provided, namely, multi-period
portfolio optimization, transfer learning in multi-period portfolio
optimization, and insurance claim prediction, which involve neural networks
with (Leaky)-ReLU activation functions. Numerical experiments conducted using
real-world datasets illustrate the superior empirical performance of
e-TH$\varepsilon$O POULA compared to SGLD, TUSLA, ADAM, and AMSGrad in terms of
model accuracy.


  We use ultrafast pump-probe transmission spectroscopy to measure the
electronic relaxation time for electrons in cobalt nanoparticles embedded on
glass substrate using femtosecond laser pulses. We found that the plasmon
excitation is inhomogenously broadening with a fast excitation time of 23 fs.
and a plasmonic relaxation time of 97fs. The femtosecond laser pulses used in
this experiment were come from a Ti:Sapphire resonator that uses a
self-mode-locking mechanism based on the nonlinear Kerr effect. The pulses were
found to have repetition rate of 103.52MHz with a pulse width of 64.5 fs at
FWHM, and 810nm center wavelength.


  We present two-dimensional slab-jet simulations of jets in inhomogeneous
media consisting of a tenuous hot medium populated with a small filling factor
by warm, dense clouds. The simulations are relevant to the structure and
dynamics of sources such as Gigahertz Peak Spectrum and Compact Steep Spectrum
radio galaxies, High Redshift Radio Galaxies and radio galaxies in cooling
flows. The jets are disrupted to a degree depending upon the filling factor of
the clouds. With a small filling factor, the jet retains some forward momentum
but also forms a halo or bubble around the source. At larger filling factors
channels are formed in the cloud distribution through which the jet plasma
flows and a hierarchical structure consisting of nested lobes and an outer
enclosing bubble results. We suggest that the CSS quasar 3C48 is an example of
a low filling factor jet - interstellar medium interaction whilst M87 may be an
example of the higher filling factor type of interaction. Jet disruption occurs
primarily as a result of Kelvin-Helmholtz instabilities driven by turbulence in
the radio cocoon not through direct jet-cloud interactions, although there are
some examples of these. In all radio galaxies whose morphology may be the
result of jet interactions with an inhomogeneous interstellar medium we expect
that the dense clouds will be optically observable as a result of radiative
shocks driven by the pressure of the radio cocoon. We also expect that the
radio galaxies will possess faint haloes of radio emitting material well beyond
the observable jet structure.


  Detection of vaccine adverse events is crucial to the discovery and
improvement of problematic vaccines. To achieve it, traditionally formal
reporting systems like VAERS support accurate but delayed surveillance, while
recently social media have been mined for timely but noisy observations.
Utilizing the complementary strengths of these two domains to boost the
detection performance looks good but cannot be effectively achieved by existing
methods due to significant differences between their data characteristics,
including: 1) formal language v.s. informal language, 2) single-message per
user v.s. multi-messages per user, and 3) one class v.s. binary class. In this
paper, we propose a novel generic framework named Multi-instance Domain
Adaptation (MIDA) to maximize the synergy between these two domains in the
vaccine adverse event detection task for social media users. Specifically, we
propose a generalized Maximum Mean Discrepancy (MMD) criterion to measure the
semantic distances between the heterogeneous messages from these two domains in
their shared latent semantic space. Then these message-level generalized MMD
distances are synthesized by newly proposed mixed instance kernels to
user-level distances. We finally minimize the distances between the samples of
the partially-matched classes from these two domains. In order to solve the
non-convex optimization problem, an efficient Alternating Direction Method of
Multipliers (ADMM) based algorithm combined with the Convex-Concave Procedure
(CCP) is developed to optimize parameters accurately. Extensive experiments
demonstrated that our model outperformed the baselines by a large margin under
six metrics. Case studies showed that formal reports and extracted
adverse-relevant tweets by MIDA shared a similarity of keyword and description
patterns.


  We study a family of dissections of flow polytopes arising from the
subdivision algebra. To each dissection of a flow polytope, we associate a
polynomial, called the left-degree polynomial, which we show is invariant of
the dissection considered (proven independently by Grinberg). We prove that
left-degree polynomials encode integer points of generalized permutahedra.
Using that certain left-degree polynomials are related to Grothendieck
polynomials, we resolve special cases of conjectures by Monical, Tokcan, and
Yong regarding the saturated Newton polytope property of Grothendieck
polynomials.


  This work completes the classification of the cubic vertices for arbitrary
spin massless bosons in three dimensions started in a previous companion paper
by constructing parity-odd vertices. Similarly to the parity-even case, there
is a unique parity-odd vertex for any given triple $s_1\geq s_2\geq s_3\geq 2$
of massless bosons if the triangle inequalities are satisfied ($s_1<s_2+s_3$)
and none otherwise. These vertices involve two (three) derivatives for odd
(even) values of the sum $s_1+s_2+s_3$. A non-trivial relation between
parity-even and parity-odd vertices is found. Similarly to the parity-even
case, the scalar and Maxwell matter can couple to higher spins through current
couplings with higher derivatives. We comment on possible lessons for 2d CFT.
We also derive both parity-even and parity-odd vertices with Chern-Simons
fields and comment on the analogous classification in two dimensions.


  It is familiar that the Casimir self-energy of a homogeneous dielectric ball
is divergent, although a finite self-energy can be extracted through second
order in the deviation of the permittivity from the vacuum value. The exception
occurs when the speed of light inside the spherical boundary is the same as
that outside, so the self-energy of a perfectly conducting spherical shell is
finite, as is the energy of a dielectric-diamagnetic sphere with
$\varepsilon\mu=1$, a so-called isorefractive or diaphanous ball. Here we
re-examine that example, and attempt to extend it to an electromagnetic
$\delta$-function sphere, where the electric and magnetic couplings are equal
and opposite. Unfortunately, although the energy expression is superficially
ultraviolet finite, additional divergences appear that render it difficult to
extract a meaningful result in general, but some limited results are presented.


  Iron-based superconducting layered compounds have the second highest
transition temperature after cuprate superconductors. Their discovery is a
milestone in the history of high-temperature superconductivity and will have
profound implications for high-temperature superconducting mechanism as well as
industrial applications. Raman scattering has been extensively applied to
correlated electron systems including the new superconductors due to its unique
ability to probe multiple primary excitations and their coupling. In this
review, we will give a brief summary of the existing Raman experiments in the
iron-based materials and their implication for pairing mechanism in particular.
And we will also address some open issues from the experiments.


  This article proposes a concept called Condensed Electromagnetic Radiation
(CER) as the electromagnetic origin of mass particles. An overwhelming amount
of experimental evidence is consistent with the CER concept as a fundamental
explanation for the physical properties of mass particles. Among many others
cited, two well-established physical phenomena offer especially compelling
evidence: parametric down conversion of photons, and generation of leptons and
quarks.


  We prove that, if $n\geq 3$, a singular foliation $\mathcal{F}$ on $\mathbb
P^n$ which can be written as pull-back, where $\mathcal{G}$ is a foliation in $
{\mathbb P^2}$ of degree $d\geq2$ with one or three invariant lines in general
position and $f:{\mathbb P^n}--->{\mathbb P^2}$, $deg(f)=\nu\geq2,$ is an
appropriated rational map, is stable under holomorphic deformations. As a
consequence we conclude that the closure of the sets $\{\mathcal {F}=
f^{*}(\mathcal{G})\}$ are new irreducible components of the space of
holomorphic foliations of certain degrees.


  The realization of a functional quantum repeater is one of the major research
goals in long-distance quantum communication. Among the different approaches
that are being followed, the one relying on quantum memories interfaced with
deterministic quantum emitters is considered as among one of the most promising
solutions. In this work, we focus on memory-based quantum-repeater schemes that
rely on semiconductor quantum dots for the generation of polarization entangled
photons. Going through the most relevant figures of merit related to efficiency
of the photon source, we select significant developments in fabrication,
processing and tuning techniques aimed at combining high degree of entanglement
with on-demand pair generation, with a special focus on the progress achieved
in the representative case of the GaAs system. We proceed to offer a
perspective on integration with quantum memories, both highlighting preliminary
works on natural-artificial atomic interfaces and commenting a wide choice of
currently available and potentially viable memory solutions in terms of
wavelength, bandwidth and noise-requirements. To complete the overview, we also
present recent implementations of entanglement-based quantum communication
protocols with quantum dots and highlight the next challenges ahead for the
implementation of practical quantum networks.


  Electronic Intelligence (ELINT), often known as E-Intelligence, is
intelligence obtained through electronic sensors. Other than personal
communications, ELINT intelligence is usually obtained. The goal is usually to
determine a target's capabilities, such as radar placement. Active or passive
sensors can be employed to collect data. A provided signal is analyzed and
contrasted to collected data for recognized signal types. The information may
be stored if the signal type is detected; it can be classed as new if no match
is found. ELINT collects and categorizes data. In a military setting (and
others that have adopted the usage, such as a business), intelligence helps an
organization make decisions that can provide them a strategic advantage over
the competition. The term "intel" is frequently shortened. The two main
subfields of signals intelligence (SIGINT) are ELINT and Communications
Intelligence (COMINT). The US Department of Defense specifies the
terminologies, and intelligence communities use the categories of data reviewed
worldwide.


  We investigated the electronic structure of multiferroic hexagonal RMnO3 (R =
Gd, Tb, Dy, and Ho) thin films using both optical spectroscopy and
first-principles calculations. Using artificially stabilized hexagonal RMnO3,
we extended the optical spectroscopic studies on the hexagonal multiferroic
manganite system. We observed two optical transitions located near 1.7 eV and
2.3 eV, in addition to the predominant absorption above 5 eV. With the help of
first-principles calculations, we attribute the low-lying optical absorption
peaks to inter-site transitions from the oxygen states hybridized strongly with
different Mn orbital symmetries to the Mn 3d3z2-r2 state. As the ionic radius
of the rare earth ion increased, the lowest peak showed a systematic increase
in its peak position. We explained this systematic change in terms of a
flattening of the MnO5 triangular bipyramid.


  There is strong observational evidence indicating a time lag of order of some
100 Myr between the onset of starburst and AGN activity in galaxies. Dynamical
time lags have been invoked to explain this. We extend this approach by
introducing a viscous time lag the gas additionally needs to flow through the
AGN's accretion disc before it reaches the central black hole. Our calculations
reproduce the observed time lags and are in accordance with the observed
correlation between black hole mass and stellar velocity dispersion.


  Large-scale outflows driven by active galactic nuclei (AGN) can have a
profound influence on their host galaxies. The outflow properties themselves
depend sensitively on the history of AGN energy injection during the lifetime
of the outflow. Most observed outflows have dynamical timescales longer than
the typical AGN episode duration, i.e. they have been inflated by multiple AGN
episodes. Here, we present a neural-network based approach to inferring the
most likely duty cycle and other properties of AGN based on the observable
properties of their massive outflows. Our model recovers the AGN parameters of
simulated outflows with typical errors $< 25\%$. We apply the method to a
sample of 59 real molecular outflows and show that a large fraction of them
have been inflated by AGN shining with a rather high duty cycle $\delta_{\rm
AGN} > 0.2$. This result suggests that nuclear activity in galaxies is
clustered hierarchically in time, with long phases of more frequent activity
composed of many short activity episodes. We predict that $\sim \! 19\%$ of
galaxies should have AGN-driven outflows, but half of them are fossils - this
is consistent with currently available data. We discuss the possibilities to
investigate AGN luminosity histories during outflow lifetimes and suggest ways
to use our software to test other physical models of AGN outflows. The source
code of all of the software used here is made public.


  QuantEYE is designed to be the highest time-resolution instrument on ESO:s
planned Overwhelmingly Large Telescope, devised to explore astrophysical
variability on microsecond and nanosecond scales, down to the quantum-optical
limit. Expected phenomena include instabilities of photon-gas bubbles in
accretion flows, p-mode oscillations in neutron stars, and quantum-optical
photon bunching in time. Precise timescales are both variable and unknown, and
studies must be of photon-stream statistics, e.g., their power spectra or
autocorrelations. Such functions increase with the square of the intensity,
implying an enormously increased sensitivity at the largest telescopes.
QuantEYE covers the optical, and its design involves an array of
photon-counting avalanche-diode detectors, each viewing one segment of the OWL
entrance pupil. QuantEYE will work already with a partially filled OWL main
mirror, and also without [full] adaptive optics.


  Although real materials are finite in size, electronic structure theory is
built on the assumption of infinitely large solid, which led to a longstanding
controversy: where is the vacuum level? Here, we introduce an analytic
real-space potential-unfolding approach to uncover the vacuum level in
infinitely large solid. First-principles calculations show that, in the absence
of a physical surface, the bulk band structure, often measured with respect to
an average bulk potential, is offset by a hereto unknown and
orientation-dependent bulk quadrupole with respect to the vacuum level. By
identifying intrinsic contributions of a bulk solid to its surface and
interface properties, our theory eliminates the ambiguities surrounding the
physical origin of the band alignment between matters.


  We present a selection technique to detect Compton-thick (CT) active galactic
nuclei (AGNs) in the 3XMM/SDSS-DR7 cross-correlation. A subsample of 3481 X-ray
sources that are detected in the hard band (2-8 keV) and have photometric
redshifts constitute our parent sample. We first applied an automated
spectral-fitting procedure to select highly absorbed sources (N_H > 10^23
cm^-2). We found 184 highly absorbed candidates. Then, we performed the
Bayesian Monte Carlo Markov chains (MCMCs) selection technique to find CT AGNs.
We also tested the MCMC selection technique by applying Monte Carlo
simulations. We found that the method is accurate at 90 percent independently
of the nature of the underlying source. Our sample contains 52 bona fide CT
AGNs. The CT AGNs were selected to have a range > 0.75 of probability of being
CT when either fitting with the two models Torus and MYTorus. About 75 percent
of CT AGNs in our sample had probabilities > 90 percent. From the spectral
analysis, we significantly found an anticorrelation between the equivalent
width of the neutral Fe K_{\alpha} line and the X-ray luminosity at 2-10 keV,
the so-called X-ray Baldwin effect.


  The quark-antiquark bound states are discussed using the relativistic
spectator (Gross) equations. A relativistic covariant framework for analyzing
confined bound states is developed. The relativistic linear potential developed
in an earlier work is proven to give vanishing meson$\to$ $q+\bar{q}$ decay
amplitudes, as required by confinement. The regularization of the singularities
in the linear potential that are associated with nonzero energy transfers (i.e.
$q^2=0,q^{\mu}\neq0$) is improved. Quark mass functions that build chiral
symmetry into the theory and explain the connection between the current quark
and constituent quark masses are introduced. The formalism is applied to the
description of pions and kaons with reasonable results.


  Quantum Gravity framework motivates us to find new theories in which an
observer independent finite energy upper bound (preferably Planck Energy)
exists. We have studied the modifications in the thermodynamical properties of
a photon gas in such a scenario where we have an invariant energy scale. We
show that the density of states and the entropy in such a framework are less
than the corresponding quantities in Einstein's Special Relativity (SR) theory.
This result can be interpreted as a consequence of the deformed Lorentz
symmetry present in the particular model we have considered.


  We investigate the dynamics of electron spin qubits in quantum dots.
Measurement of the qubit state is realized by a charge current through the dot.
The dynamics is described in the framework of the quantum trajectory approach,
widely used in quantum optics, and we show that it can be applied successfully
to problems in condensed matter physics. The relevant master equation dynamics
is unravelled to simulate stochastic tunneling events of the current through
the dot.Quantum trajectories are then used to extract the counting statistics
of the current. We show how, in combination with an electron spin resonance
(ESR) field, counting statistics can be employed for quantum state tomography
of the qubit state. Further, it is shown how decoherence and relaxation time
scales can be estimated with the help of counting statistics, in the time
domain. Finally, we discuss a setup for single shot measurement of the qubit
state without the need for spin-polarized leads.


  Modern applications of survival analysis increasingly involve time-dependent
covariates. The Python package BoXHED2.0 is a tree-boosted hazard estimator
that is fully nonparametric, and is applicable to survival settings far more
general than right-censoring, including recurring events and competing risks.
BoXHED2.0 is also scalable to the point of being on the same order of speed as
parametric boosted survival models, in part because its core is written in C++
and it also supports the use of GPUs and multicore CPUs. BoXHED2.0 is available
from PyPI and also from www.github.com/BoXHED.


  How does connectivity impact network dynamics? We address this question by
linking network characteristics on two scales. On the global scale we consider
the coherence of overall network dynamics. We show that such \emph{global
coherence} in activity can often be predicted from the \emph{local structure}
of the network. To characterize local network structure we use "motif
cumulants," a measure of the deviation of pathway counts from those expected in
a minimal probabilistic network model.
  We extend previous results in three ways. First, we give a new combinatorial
formulation of motif cumulants that relates to the allied concept in
probability theory. Second, we show that the link between global network
dynamics and local network architecture is strongly affected by heterogeneity
in network connectivity. However, we introduce a network-partitioning method
that recovers a tight relationship between architecture and dynamics. Third,
for a particular set of models we generalize the underlying theory to treat
dynamical coherence at arbitrary orders (i.e. triplet correlations, and
beyond). We show that at any order only a highly restricted set of motifs
impact dynamical correlations.


  Multiplexed immuno-fluorescence tissue imaging, allowing simultaneous
detection of molecular properties of cells, is an essential tool for
characterizing the complex cellular mechanisms in translational research and
clinical practice. New image analysis approaches are needed because tissue
section stained with a mixture of protein, DNA and RNA biomarkers are
introducing various complexities, including spurious edges due to fluorescent
staining artifacts between touching or overlapping cells. We have developed the
RRScell method harnessing the stochastic random-reaction-seed (RRS) algorithm
and deep neural learning U-net to extract single-cell resolution profiling-map
of gene expression over a million cells tissue section accurately and
automatically. Furthermore, with the use of manifold learning technique UMAP
for cell phenotype cluster analysis, the AI-driven RRScell has equipped with a
marker-based image cytometry analysis tool (markerUMAP) in quantifying spatial
distribution of cell phenotypes from tissue images with a mixture of
biomarkers. The results achieved in this study suggest that RRScell provides a
robust enough way for extracting cytometric single cell morphology as well as
biomarker content in various tissue types, while the build-in markerUMAP tool
secures the efficiency of dimension reduction, making it viable as a general
tool in the spatial analysis of high dimensional tissue image.


  A moving mesh finite element method is studied for the numerical solution of
a phase-field model for brittle fracture. The moving mesh partial differential
equation approach is employed to dynamically track crack propagation.
Meanwhile, the decomposition of the strain tensor into tensile and compressive
components is essential for the success of the phase-field modeling of brittle
fracture but results in a non-smooth elastic energy and stronger nonlinearity
in the governing equation. This makes the governing equation much more
difficult to solve and, in particular, Newton's iteration often to fail to
converge. Three regularization methods are proposed to smooth out the
decomposition of the strain tensor. Numerical examples of fracture propagation
under quasi-static load demonstrate that all of the methods can effectively
improve the convergence of Newton's iteration for relatively small values of
the regularization parameter but without comprising the accuracy of the
numerical solution. They also show that the moving mesh finite element method
is able to adaptively concentrate the mesh elements around propagating cracks
and handle multiple and complex crack systems.


  We discovered that the Wolf-Rayet (WR)+OB star binary, WR 104, renowned for
its associated "dusty pinwheel nebula" recently spatially resolved with
infrared interferometry, exhibits strong quasi-periodic optical variations with
a full amplitude of 2.7 mag. Such a large-amplitude, continuous variation has
been unprecedented in a WR star. The optical quasi-period (~241 d) is in almost
perfect agreement with the interferometric period (243.5+/-3 d). The remarkable
agreement of the dominant period in optical variability with the orbital period
supports that the strongly varying dust obscuration is physically related to
the binary motion, rather than sporadic dust-forming episodes. Considering the
low orbital inclination (11+/-7 deg) and the nearly circular orbit inferred
from the interferometric observations, the strongly variable line-of-sight
extinction suggests that the highly structured extinction can be being formed
via an ejection of dust in the direction of the binary rotation axis. Another
viable explanation is that the three-dimensional structure of the shock front,
itself is the obscuring body. Depending on the geometry, the dusty shock front
near the conjunction phase of the binary can completely obscure the inner
WR-star wind and the OB star, which can explain the amplitude of optical fading
and the past observation of remarkable spectral variation.


  Due to the kinematic reversibility of Stokes flow, a body executing a
reciprocal motion (a motion in which the sequence of body configurations
remains identical under time reversal) cannot propel itself in a viscous fluid
in the limit of negligible inertia; this result is known as Purcell's scallop
theorem. In this limit, the Reynolds numbers based on the fluid inertia and on
the body inertia are all zero. Previous studies characterized the breakdown of
the scallop theorem with fluid inertia. In this paper we show that, even in the
absence of fluid inertia, certain dense bodies undergoing reciprocal motion are
able to swim. Using Lorentz's reciprocal theorem, we first derive the general
differential equations that govern the locomotion kinematics of a dense
swimmer. We demonstrate that no reciprocal swimming is possible if the body
motion consists only of tangential surface deformation (squirming). We then
apply our general formulation to compute the locomotion of four simple
swimmers, each with a different spatial asymmetry, that perform normal surface
deformations. We show that the resulting swimming speeds (or rotation rates)
scale as the first power of a properly defined "swimmer Reynolds number'',
demonstrating thereby a continuous breakdown of the scallop theorem with body
inertia.


  Heavy ions induced single event upset (SEU) sensitivity of three-dimensional
integrated SRAMs are evaluated by using Monte Carlo sumulation methods based on
Geant4. The cross sections of SEUs and Multi Cell Upsets (MCUs) for 3D SRAM are
simulated by using heavy ions with different energies and LETs. The results
show that the sensitivity of different die of 3D SRAM has obvious discrepancies
at low LET. Average percentage of MCUs of 3D SRAMs rises from 17.2% to 32.95%
when LET increases from 42.19 MeV cm2/mg to 58.57MeV cm2/mg. As for a certain
LET, the percentage of MCUs shows a notable distinction between face-to-face
structure and back-to-face structure. For back-to-face structure, the
percentage of MCUs increases with the deeper die. However, the face-to-face die
presents the relatively low percentage of MCUs. The comparison of SEU cross
sections for planar SRAMs and experiment data are conducted to indicate the
effectiveness of our simulation method. Finally, we compare the upset cross
sections of planar process and 3D integrated SRAMs. Results demonstrate that
the sensitivity of 3D SRAMs is not more than that of planar SRAMs and the 3D
structure can be become a great potential application for aerospace and
military domain.


  We propose a novel randomized linear programming algorithm for approximating
the optimal policy of the discounted Markov decision problem. By leveraging the
value-policy duality and binary-tree data structures, the algorithm adaptively
samples state-action-state transitions and makes exponentiated primal-dual
updates. We show that it finds an $\epsilon$-optimal policy using nearly-linear
run time in the worst case. When the Markov decision process is ergodic and
specified in some special data formats, the algorithm finds an
$\epsilon$-optimal policy using run time linear in the total number of
state-action pairs, which is sublinear in the input size. These results provide
a new venue and complexity benchmarks for solving stochastic dynamic programs.


  In an attempt to understand the role of the strong radial dependence of
thermal diffusivity on the properties of convection in sun-like stars, we mimic
that effect in non-Oberbeck-Boussinesq (NOB) convection in a
horizontally-extended rectangular domain (aspect ratio 16), by allowing the
thermal diffusivity $\kappa$ to increase with the temperature (as in the case
of stars). Direct numerical simulations (i.e., numerical solutions of the
governing equations by resolving up to the smallest scales without requiring
any modeling) show that, in comparison with Oberbeck-Boussinesq (OB)
simulations (two of which we perform for comparison purposes), the symmetry of
the temperature field about the mid-horizontal plane is broken, whereas the
velocity and heat flux profiles remain essentially symmetric. Our choice of
$\kappa(T)$, which resembles the variation in stars, results in the temperature
field that loses its fine structures towards the hotter part of the
computational domain, but the characteristic large scale of the turbulent
thermal `superstructures', which are structures whose size is typically larger
than the depth of the convection domain, continue to be largely independent of
the depth.


  This article introduces randomized block Gram-Schmidt process (RBGS) for QR
decomposition. RBGS extends the single-vector randomized Gram-Schmidt (RGS)
algorithm and inherits its key characteristics such as being more efficient and
having at least as much stability as any deterministic (block) Gram-Schmidt
algorithm.
  Block algorithms offer superior performance as they are based on BLAS3
matrix-wise operations and reduce communication cost when executed in parallel.
Notably, our low-synchronization variant of RBGS can be implemented in a
parallel environment using only one global reduction operation between
processors per block. Moreover, the block Gram-Schmidt orthogonalization is the
key element in the block Arnoldi procedure for the construction of a Krylov
basis, which in turn is used in GMRES, FOM and Rayleigh-Ritz methods for the
solution of linear systems and clustered eigenvalue problems. In this article,
we develop randomized versions of these methods, based on RBGS, and validate
them on nontrivial numerical examples.


  Sparse additive modeling is a class of effective methods for performing
high-dimensional nonparametric regression. This paper develops a sparse
additive model focused on estimation of treatment effect-modification with
simultaneous treatment effect-modifier selection. We propose a version of the
sparse additive model uniquely constrained to estimate the interaction effects
between treatment and pretreatment covariates, while leaving the main effects
of the pretreatment covariates unspecified. The proposed regression model can
effectively identify treatment effect-modifiers that exhibit possibly nonlinear
interactions with the treatment variable, that are relevant for making optimal
treatment decisions. A set of simulation experiments and an application to a
dataset from a randomized clinical trial are presented to demonstrate the
method.


  We present a space-efficient implementation of the quantum verification of
matrix products (QVMP) algorithm and demonstrate its functionality by running
it on the Aer simulator with two simulation methods: statevector and matrix
product state (MPS). We report circuit metrics (gate count, qubit count,
circuit depth), transpilation time, simulation time, and a proof of Grover
oracle correctness. Our study concludes that while QVMP can be simulated on
moderately sized inputs, it cannot scale to a degree where we can observe any
quantum advantage on current quantum hardware due to circuit depth and qubit
count constraints. Further, the choice of simulation method has a noticeable
impact on the size of the transpiled circuit which slows down development.


  This work analyzes the phase correlation of the three lunar cycles and the
Saros/Exeligmos cycle, after the study of the chapter About Exeligmos in
Introduction to the Phenomena by Geminus. Geminus, refers that each Exeligmos
cycle began on very specific and rare dates, when the Moon positioned at the
points of the three lunar cycles beginning: New moon at Apogee and at the Node.
The extremely large duration of the Annular Solar eclipse occurred on December
22 178BC (Saros series 58), marks the start of the Prominent Saros Cycle
Apokatastasis. The next day, 23 December 178BC, the Winter Solstice started.
During these two neighboring dates, the celebration of the religious festival
of Isia started in Egypt and the Hellenistic Greece. After the analysis of the
Mechanism's Parapegma events specific position, 22/23 December 178BC is an
ideal, functional and representative initial date, in order to calibrate the
initial position of the Mechanism's pointers.


  The fashion industry is looking forward to use artificial intelligence
technologies to enhance their processes, services, and applications. Although
the amount of fashion data currently in use is increasing, there is a large gap
in data exchange between the fashion industry and the related AI companies, not
to mention the different structure used for each fashion dataset. As a result,
AI companies are relying on manually annotated fashion data to build different
applications. Furthermore, as of this writing, the terminology, vocabulary and
methods of data representation used to denote fashion items are still ambiguous
and confusing. Hence, it is clear that the fashion industry and AI companies
will benefit from a protocol that allows them to exchange and organise fashion
information in a unified way. To achieve this goal we aim (1) to define a
protocol called DDOIF that will allow interoperability of fashion data; (2) for
DDOIF to contain diverse entities including extensive information on clothing
and accessories attributes in the form of text and various media formats; and
(3)To design and implement an API that includes, among other things, functions
for importing and exporting a file built according to the DDOIF protocol that
stores all information about a single item of clothing. To this end, we
identified over 1000 class and subclass names used to name fashion items and
use them to build the DDOIF dictionary. We make DDOIF publicly available to all
interested users and developers and look forward to engaging more collaborators
to improve and enrich it.


  We perform a theoretical study of nonlinear optical isolator devices based on
coupled microcavities with gain and loss. Using coupled-mode theory, we derive
a correspondence between the boundary of asymptotic stability in the nonlinear
regime, where gain saturation is present, and the PT-breaking transition in the
underlying linear system. For zero detuning and weak input intensity, the onset
of optical isolation can be rigorously derived, and corresponds precisely to
the PT transition point. When the couplings to the external ports are unequal,
the isolation ratio exhibits an abrupt jump at the transition point, determined
by the ratio of the couplings. This could be exploited to realize an actively
controlled nonlinear optical isolator, in which strong optical isolation can be
switched on or off using tiny variations in the inter-resonator separation.


  We present the second and last year of observations of our optical follow-up
programme 128-MULTIPLE-16/15B (LP15 )at Roque de los Muchachos Observatory (La
Palma), which has been developed with the aim of validating all the
unidentified PSZ2 sources in the northern sky, with declination above -15deg,
and with no correspondence in the first Planck catalogue PSZ1. We adopt a
robust confirmation criteria based on velocity dispersion and richness
estimations in order to carry out the final classification of the new galaxy
clusters as the optical counterparts of the PSZ2 detections. We also present
final results of the programme, showing an update of the purity and
completeness of the PSZ2 sample. After the LP15 programme, we find that the
purity of the PSZ2 has increased from 76.7% originally to 86.2%. In addition,
we study the possible reasons of having false detection, and we report a clear
correlation between the number of unconfirmed sources and galactic thermal dust
emission.


  Thermodynamic properties as well as low-energy magnon excitations of $S=1$
honeycomb-layered Na$_3$Ni$_2$SbO$_6$ have been investigated by high-resolution
dilatometry, static magnetisation, and high-frequency electron spin resonance
studies in magnetic fields up to 16 T. At $T_{\rm N}$ = 16.5 K, there is a
tricritical point separating two distinct antiferromagnetic phases AF1 and AF2
from the paramagnetic regime. In addition, our data imply short-range
antiferromagnetic correlations at least up to $\sim 5\cdot T_{\rm N}$. Well
below $T_{\rm N}$, the magnetic field $B_{\rm C1}\approx$ 9.5 T is needed to
stabilize AF2 against AF1. The thermal expansion and magnetostriction anomalies
at $T_{\rm N}$ and $B_{\rm C1}$ imply significant magnetoelastic coupling, both
of which associated with a sign change of $\partial L/\partial B$. The
transition at $B_{\rm C1}$ is associated with softening of the
antiferromagnetic resonance modes observed in the electron spin resonance
spectra. The anisotropy gap $\Delta = 360$ GHz implies considerable uniaxial
anisotropy. We conclude the crucial role of axial anisotropy favoring the AF1
spin structure over the AF2 one. While the magnetostriction data disprove a
simple spin-flop scenario at $B_{\rm C1}$, the nature of a second transition at
$B_{\rm C2}\approx$ 13 T remains unclear. Both the sign of the magnetostriction
and Gr\"uneisen analysis suggest the short-range correlations at high
temperatures to be of AF2-type.


  Swift has initiated a new era of understanding the extremes of active
galactic nuclei (AGN) variability, their drivers and underlying physics. This
is based on its rapid response, high sensitivity, good spatial resolution, and
its ability to collect simultaneously X--ray-to-optical SEDs. Here, we present
results from our recent monitoring campaigns with Swift of highly variable AGN,
including outbursts, deep low states, and unusual long-term trends in several
Seyfert galaxies including Mrk 335, WPVS007, and RXJ2314.9+2243. We also report
detection of a new X-ray and optical outburst of IC 3599 and our Swift
follow-ups. IC 3599 was previously known as one of the AGN with the
highest-amplitude outbursts. We briefly discuss implications of this second
outburst of IC 3599 for emission scenarios including accretion-disk
variability, repeat tidal disruption events, and the presence of a binary
supermassive black hole.


  We study chiral symmetry restoration and quark deconfinement beyond mean
field approximation in a magnetized PNJL model. The feedback from mesons to
quarks modifies the quark coupling constant and Polyakov potential. As a
result, the separate critical temperatures for the two phase transitions at
mean field level coincide and the magnetic catalysis becomes inverse magnetic
catalysis, when the meson contribution is included.


  The R package ecosystem is expanding fast and dependencies among packages in
the ecosystem are becoming more complex. In this study, we explored the package
dependencies from a new aspect. We applied a new metric named "dependency
heaviness" which measures the number of additional strong dependencies that a
package uniquely contributes to its child or downstream packages. It also
measures the total reduced dependencies in the ecosystem when the role of a
package is changed from a strong parent to a weak parent. We systematically
studied how the dependency heaviness spreads from parent to child packages, and
how it further spreads to remote downstream packages in the CRAN/Bioconductor
ecosystem. We extracted top packages and key paths that majorly transmit heavy
dependencies in the ecosystem. Additionally, the dependency heaviness analysis
on the ecosystem has been implemented as a web-based database that provides
comprehensive tools for querying dependencies of individual R packages.


  The surface granularity of small Solar System bodies is diverse through the
different types of planetary bodies and even for specific objects it is often
not known in detail. One of the physical properties that strongly depends on
the surface structure is the surface temperature. In highly porous media with
large voids, radiation can efficiently transport heat, whereas more compact,
micro-porous structures transport the heat primarily by conduction through the
solid material. In this work, we investigate under which conditions a
macro-porous surface can be distinguished from a micro-porous one by simply
measuring the surface temperature. In our numerical simulations, we included
circular and elliptical orbits with and without obliquity and varied the
rotation period of the considered objects. We found that daily temperature
cycles are rather insensitive to the specific surface granularity. However, the
surface temperature at sunrise shows significant dependency on the material
structure and this effect becomes even more pronounced when the solar intensity
increases. By measuring the sunrise temperature as a function of insolation at
noon, a differentiation between micro- and macro-granular surface structures is
possible. In this paper, we provide a strategy how remote sensing can be used
to derive the surface structure of small Solar System bodies.


  Inspired by the construction of the F{\"o}llmer process, we construct a
unit-time flow on the Euclidean space, termed the F{\"o}llmer flow, whose flow
map at time 1 pushes forward a standard Gaussian measure onto a general target
measure. We study the well-posedness of the F{\"o}llmer flow and establish the
Lipschitz property of the flow map at time 1. We apply the Lipschitz mapping to
several rich classes of probability measures on deriving dimension-free
functional inequalities and concentration inequalities for the empirical
measure.


  Quantum many-body physics simulation has important impacts on understanding
fundamental science and has applications to quantum materials design and
quantum technology. However, due to the exponentially growing size of the
Hilbert space with respect to the particle number, a direct simulation is
intractable. While representing quantum states with tensor networks and neural
networks are the two state-of-the-art methods for approximate simulations, each
has its own limitations in terms of expressivity and inductive bias. To address
these challenges, we develop a novel architecture, Autoregressive Neural
TensorNet (ANTN), which bridges tensor networks and autoregressive neural
networks. We show that Autoregressive Neural TensorNet parameterizes normalized
wavefunctions, allows for exact sampling, generalizes the expressivity of
tensor networks and autoregressive neural networks, and inherits a variety of
symmetries from autoregressive neural networks. We demonstrate our approach on
quantum state learning as well as finding the ground state of the challenging
2D $J_1$-$J_2$ Heisenberg model with different systems sizes and coupling
parameters, outperforming both tensor networks and autoregressive neural
networks. Our work opens up new opportunities for quantum many-body physics
simulation, quantum technology design, and generative modeling in artificial
intelligence.


  The eigenspectrum of the Koopman operator enables the decomposition of
nonlinear dynamics into a sum of nonlinear functions of the state space with
purely exponential and sinusoidal time dependence. For a limited number of
dynamical systems, it is possible to find these Koopman eigenfunctions exactly
and analytically. Here, this is done for the Korteweg-de Vries equation on a
periodic interval, using the periodic inverse scattering transform and some
concepts of algebraic geometry. To the authors' knowledge, this is the first
complete Koopman analysis of a partial differential equation which does not
have a trivial global attractor. The results are shown to match the frequencies
computed by the data-driven method of dynamic mode decomposition (DMD). We
demonstrate that in general DMD gives a large number of eigenvalues near the
imaginary axis, and show how these should be interpretted in this setting.


  The purpose of this paper is to generalize the classical Mazur's lemma from
the classical convex analysis to the framework of locally $L^0$-convex modules.
In this version an extra condition of countable concatenation is included. We
provide a counterexample showing that this condition cannot be removed.


  We propose and evaluate a neural point-based graphics method that can model
semi-transparent scene parts. Similarly to its predecessor pipeline, ours uses
point clouds to model proxy geometry, and augments each point with a neural
descriptor. Additionally, a learnable transparency value is introduced in our
approach for each point.
  Our neural rendering procedure consists of two steps. Firstly, the point
cloud is rasterized using ray grouping into a multi-channel image. This is
followed by the neural rendering step that "translates" the rasterized image
into an RGB output using a learnable convolutional network. New scenes can be
modeled using gradient-based optimization of neural descriptors and of the
rendering network.
  We show that novel views of semi-transparent point cloud scenes can be
generated after training with our approach. Our experiments demonstrate the
benefit of introducing semi-transparency into the neural point-based modeling
for a range of scenes with semi-transparent parts.


  An element of a ring is unique clean if it can be uniquely written as the sum
of an idempotent and a unit. A ring $R$ is uniquely $\pi$-clean if some power
of every element in $R$ is uniquely clean. In this article, we prove that a
ring $R$ is uniquely $\pi$-clean if and only if for any $a\in R$, there exists
an $m\in {\Bbb N}$ and a central idempotent $e\in R$ such that $a^m-e\in J(R)$,
if and only if $R$ is abelian; every idempotent lifts modulo $J(R)$; and $R/P$
is torsion for all prime ideals $P$ containing the Jacobson radical $J(R)$.
Further, we prove that a ring $R$ is uniquely $\pi$-clean and $J(R)$ is nil if
and only if $R$ is an abelian periodic ring, if and only if for any $a\in R$,
there exists some $m\in {\Bbb N}$ and a unique idempotent $e\in R$ such that
$a^m-e\in P(R)$, where $P(R)$ is the prime radical of $R$.