  The contributions of the vector leptoquarks of Pati-Salam type to the
branching ratios of $K_L^0, B^0, B_s \to l \, l^{\prime}$ decays are calculated
with account of the fermion mixing in the leptoguark currents of the general
type. Using the general parametrizations of the mixing matrices the lower
vector leptoquark mass limit $ m_V > 86 \,\, TeV $ is found from the current
experimental data on these decays. The branching ratios of the decays $B^0, B_s
\to l \, l^{\prime}$ predicted at $m_V = 86 \,\, TeV$ are calculated. These
branching ratios for the decays $ B^0, B_s \to \mu^+ \mu^-, e \mu $ are close
to the experimental data whereas those for the decays $B^0 \to e^+ e^-, e \tau,
\mu \tau$, and $B_s \to e^+ e^-$ are by order of $2\div4$ less than their
current experimental limits. For the decays $B_s \to e \tau, \mu \tau$ these
branching ratios are of order $10^{-10}$ and $10^{-9}$ respectively. The
predicted branching ratios will be usefull in the current and future
experimental searches for these decays.


  We consider a heteroscedastic regression model in which some of the
regression coefficients are zero but it is not known which ones. Penalized
quantile regression is a useful approach for analyzing such data. By allowing
different covariates to be relevant for modeling conditional quantile functions
at different quantile levels, it provides a more complete picture of the
conditional distribution of a response variable than mean regression. Existing
work on penalized quantile regression has been mostly focused on point
estimation. Although bootstrap procedures have recently been shown to be
effective for inference for penalized mean regression, they are not directly
applicable to penalized quantile regression with heteroscedastic errors. We
prove that a wild residual bootstrap procedure for unpenalized quantile
regression is asymptotically valid for approximating the distribution of a
penalized quantile regression estimator with an adaptive $L_1$ penalty and that
a modified version can be used to approximate the distribution of
$L_1$-penalized quantile regression estimator. The new methods do not need to
estimate the unknown error density function. We establish consistency,
demonstrate finite sample performance, and illustrate the applications on a
real data example.


  It is shown that if two transcendental entire functions permute, and if one
of them satisfies an algebraic differential equation, then so does the other
one.


  Given a training sample of size $m$ from a $d$-dimensional population, we
wish to allocate a new observation $Z\in \R^d$ to this population or to the
noise. We suppose that the difference between the distribution of the
population and that of the noise is only in a shift, which is a sparse vector.
For the Gaussian noise, fixed sample size $m$, and the dimension $d$ that tends
to infinity, we obtain the sharp classification boundary and we propose
classifiers attaining this boundary. We also give extensions of this result to
the case where the sample size $m$ depends on $d$ and satisfies the condition
$(\log m)/\log d \to \gamma$, $0\le \gamma<1$, and to the case of non-Gaussian
noise satisfying the Cram\'er condition.


  The Yukawa model in curved spacetime is considered. We consider a complex
scalar field coupled to a $U(1)$ gauge field and also interacting with Dirac
fields with a general Yukawa coupling. The local momentum space method is used
to obtain the one-loop effective action and we adopt the gauge condition
independent background field method introduced by Vilkovisky and DeWitt. The
pole parts of the one-loop effective action that depend on the background
scalar field, that we do not assume to be constant, are found and used to
calculate the counterterms and to determine the relevant renormalization group
functions. Terms in the effective action that involve the gradient terms in the
scalar field as well as the effective potential are found in the case where the
scalar field and Dirac fields are massless. We also discuss the anomaly that
arises if the pseudoscalar mass term for the Dirac fermions is removed by a
chiral transformation.


  The current study aims to quantify characteristic features of bipolar flux
appearance of solar intranetwork (IN) magnetic elements. To attack such a
problem, we use the Narrow-band Filter Imager (NFI) magnetograms from the Solar
Optical Telescope (SOT) on board \emph{Hinode}; these data are from quiet and
an enhanced network areas. Cluster emergence of mixed polarities and IN
ephemeral regions (ERs) are the most conspicuous forms of bipolar flux
appearance within the network. Each of the clusters is characterized by a few
well-developed ERs that are partially or fully co-aligned in magnetic axis
orientation. On average, the sampled IN ERs have total maximum unsigned flux of
several 10^{17} Mx, separation of 3-4 arcsec, and a lifetime of 10-15 minutes.
The smallest IN ERs have a maximum unsigned flux of several 10^{16} Mx,
separations less than 1 arcsec, and lifetimes as short as 5 minutes. Most IN
ERs exhibit a rotation of their magnetic axis of more than 10 degrees during
flux emergence. Peculiar flux appearance, e.g., bipole shrinkage followed by
growth or the reverse, is not unusual. A few examples show repeated
shrinkage-growth or growth-shrinkage, like magnetic floats in the dynamic
photosphere. The observed bipolar behavior seems to carry rich information on
magneto-convection in the sub-photospheric layer.


  We generalize the Hardy class H^2 of Dirichlet series studied by Hedenmalm,
Lindqvist, Olofsson, Olsen, Saksman, Seip and others to consider more general
Dirichlet series. We prove some results on this class, such as estimates for
its logarithmic L^1-norm in short intervals. We relate this to, and use these
results to make a recent nonvanishing result of Dirichlet series of ours more
explicit. In particular we give an application on the Hurwitz zeta-function.


  In manufacturing, a bottleneck workstation frequently emerges, complicating
production planning and escalating costs. To address this, Drum-Buffer-Rope
(DBR) is a widely recognized production planning and control method that
focuses on centralizing the bottleneck workstation, thereby improving
production system performance. Although DBR is primarily focused on cre-ating a
bottleneck schedule, the selection of planning parameters is crucial, as they
significantly influence the scheduling process. Conducting a compre-hensive
full factorial enumeration to identify the ideal planning parameters requires
substantial computational effort. Simulation Budget Management (SBM) offers an
effective concept to reduce this effort by skipping less promising parameter
combinations. This publication introduces a method for integrating SBM into
multi-stage multi-item DBR planned and controlled production system with
limited capacity, aimed at determining the optimal planning parameters.
Furthermore, we conduct a simulation study to analyze the effects of different
production system environments, i.e., varying levels of shop load and process
uncertainty, on both the performance and parame-terization of DBR and the
efficacy of SBM. Our results show significant re-duction in simulation budget
for identifying optimal planning parameters compared to traditional full
factorial enumeration.


  In 2013, Masson and Siljander determined a method to prove that the
$p$-minimal upper gradient $g_{f_\varepsilon}$ for the time mollification
$f_\varepsilon$, $\varepsilon>0$, of a parabolic Newton-Sobolev function $f\in
L^p_\mathrm{loc}(0,\tau;N^{1,p}_\mathrm{loc}(\Omega))$, with $\tau>0$ and
$\Omega$ open domain in a doubling metric measure space $(\mathbb{X},d,\mu)$
supporting a weak $(1,p)$-Poincar\'e inequality, $p\in(1,\infty)$, is such that
$g_{f-f_\varepsilon}\to0$ as $\varepsilon\to0$ in
$L^p_\mathrm{loc}(\Omega_\tau)$, $\Omega_\tau$ being the parabolic cylinder
$\Omega_{\tau}:=\Omega\times(0,\tau)$. Their approach involved the use of
Cheeger's differential structure, and therefore exhibited some limitations;
here, we shall see that the definition and the formal properties of the
parabolic Sobolev spaces themselves allow to find a more direct method to show
such convergence, which relies on $p$-weak upper gradients only and which is
valid regardless of structural assumptions on the ambient space, also in the
limiting case when $p=1$.


  A three-dimensional (3D) nodal-loop semimetal phase is exploited to engineer
a number of intriguing phases featuring different peculiar topological surface
states. In particular, by introducing various two-dimensional gap terms to a 3D
tight-binding model of a nodal-loop semimetal, we obtain a rich variety of
topological phases of great interest to ongoing theoretical and experimental
studies, including chiral insulator, degenerate-surface-loop insulator,
second-order topological insulator, as well as Weyl semimetal with tunable
Fermi arc profiles. The unique concept underlying our approach is to engineer
topological surface states that inherit their dispersion relations from a gap
term. The results provide one rather unified principle for the creation of
novel topological phases and can guide the search for new topological
materials. Two-terminal transport studies are also carried out to distinguish
the engineered topological phases.


  In this paper, we generalize several results of the article "Analytic
continuation of eigenvalues of a quartic oscillator" of A. Eremenko and A.
Gabrielov.
  We consider a family of eigenvalue problems for a Schr\"odinger equation with
even polynomial potentials of arbitrary degree d with complex coefficients, and
k<(d+2)/2 boundary conditions. We show that the spectral determinant in this
case consists of two components, containing even and odd eigenvalues
respectively.
  In the case with k=(d+2)/2 boundary conditions, we show that the
corresponding parameter space consists of infinitely many connected components.


  We study streaming submodular maximization subject to matching/$b$-matching
constraints (MSM/MSbM), and present improved upper and lower bounds for these
problems. On the upper bounds front, we give primal-dual algorithms achieving
the following approximation ratios.
  $\bullet$ $3+2\sqrt{2}\approx 5.828$ for monotone MSM, improving the previous
best ratio of $7.75$.
  $\bullet$ $4+3\sqrt{2}\approx 7.464$ for non-monotone MSM, improving the
previous best ratio of $9.899$.
  $\bullet$ $3+\epsilon$ for maximum weight b-matching, improving the previous
best ratio of $4+\epsilon$.
  On the lower bounds front, we improve on the previous best lower bound of
$\frac{e}{e-1}\approx 1.582$ for MSM, and show ETH-based lower bounds of
$\approx 1.914$ for polytime monotone MSM streaming algorithms.
  Our most substantial contributions are our algorithmic techniques. We show
that the (randomized) primal-dual method, which originated in the study of
maximum weight matching (MWM), is also useful in the context of MSM. To our
knowledge, this is the first use of primal-dual based analysis for streaming
submodular optimization. We also show how to reinterpret previous algorithms
for MSM in our framework; hence, we hope our work is a step towards unifying
old and new techniques for streaming submodular maximization, and that it paves
the way for further new results.


  We perform an evaluation of the p-wave amplitudes of meson-baryon scattering
in the strangeness S=-1 sector starting from the lowest order chiral
Lagrangians and introducing explicitly the Sigma^* field with couplings to the
meson-baryon states obtained using SU(6) symmetry. The N/D method of
unitarization is used, equivalent, in practice, to the use of the
Bethe-Salpeter equation with a cut-off. The procedure leaves no freedom for the
p-waves once the s-waves are fixed and thus one obtains genuine predictions for
the p-wave scattering amplitudes, which are in good agreement with experimental
results for differential cross sections, as well as for the width and partial
decay widths of the Sigma^*(1385).


  Recently, a new boson h has been discovered at the LHC which, so far, is
compatible with the properties of the SM Higgs. However, the SM is not the most
general low-energy dynamics for the minimal electroweak symmetry breaking
sector with three Goldstone bosons and one light scalar. By using non-linear
effective Lagrangian for these four particles we study different processes at
one-loop precision, identifying the counterterms needed to cancel the
divergences. Then we apply the IAM unitarization method on the partial waves,
both to make more realistic predictions which could be tested at the LHC and to
discuss the limitations of the one-loop computations. The studied processes are
the elastic scattering amplitude for both the longitudinal components of the
gauge bosons V = W, Z and the hh -> hh, as well as the inelastic VV -> hh.


  This paper statistically investigates the properties of C IV and Mg II narrow
absorption lines (NALs) to look for velocity cuts that can well constrain
quasar-associated NALs. The coverage fraction (f_c) is defined as the ratio
between the number of quasars exhibiting at least one detected absorber and the
total number of quasars that can be used to detect absorptions with given
criteria. We find that, for both C IV and Mg II absorbers, both the number
density of absorbers in given velocity intervals (dn/d\beta) and the f_c show
very significant excess at the low-velocity offset from the quasars, relative
to the random occurrence that is expected for cosmologically intervening
absorbers. These relative excess extensions for Mg II absorptions are not only
evidently related to absorption strength but also to quasar luminosity, while
they are mainly constrained within 2000 km/s no matter what quasar luminosity
and absorption strength are. In addition, we find that the redshift number
density (dn/dz) evolution of Mg II absorbers with v_abs <2000 km/s evidently
differs from that with v_abs >2000 km/s. Turning to C IV absorptions, the
relative excess extensions of both dn/d\beta and f_c are mainly limited within
v_abs<4000 km/s, and depend neither on absorption strength nor on quasar
luminosity. And also, the absorbers with v_abs<4000 km/s show obviously
different redshift number density evolution from those with v_abs>4000 km/s. We
suggest velocity cuts of 4000 km/s and 2000 km/s to define quasar C IV and Mg
II associated NALs, respectively.


  We show that, in presence of isometries and non-trivial topology, the
Einstein--Hilbert action is invariant under certain transformations of the
metric which are not diffeomorphisms. These transformations are similar to the
higher-form symmetries of field theories with $p$-form fields. In the context
of toroidal Kaluza--Klein compactifications, we show that these symmetries give
rise to some of the ``hidden symmetries'' (dualities) of the
dimensionally-reduced theories.


  The dynamical spin fluctuations in a two-dimensional square lattice in its
paramagnetic phase are examined within the framework of Random Phase
Approximation(RPA). Itinerant carriers with spin interact with each other via
an antiferromagnetic Heisenberg interaction. Then there appear three
fundamental scattering processes;a) scattering between parallel spins,b)
scattering between antiparallel spins and c) scattering with spin-flip. To
examine how these scattering processes affect the dynamical spin fluctuations,
we pick up carefully all possible combination of RPA diagrams in a consistent
manner and take the spin rotational symmetry into account. Then it becomes
clear that we have to take up a sequence of the irreducible single loop which
in itself is modified due to the particle-hole ladder type vertex correction.We
set up the Bethe-Salpeter equation for the vertex correction and show that this
can be solved in a closed form due to separable nature of the antiferromagnetic
interaction. We evaluated numerically the effectof the vertex correction and
found that the correction is negligibly small. Therefore we propose that in an
itinerant Heisenberg system, including the $t$-$J$ model as its derivertive,
the simplified RPA, where the irreducible single loop is unrenormalized, works
very well. This conclusion strongly support the simplified treatment which is
widely used in High-$T_{c}$ problem. Moreover the present formalism enables us
to proceed further microscopic calculations on the magnetic properties in the
current High-$T_{c}$ problem.


  In order to mitigate the long processing delay and high energy consumption of
mobile augmented reality (AR) applications, mobile edge computing (MEC) has
been recently proposed and is envisioned as a promising means to deliver better
quality of experience (QoE) for AR consumers. In this article, we first present
a comprehensive AR overview, including the indispensable components of general
AR applications, fashionable AR devices, and several existing techniques for
overcoming the thorny latency and energy consumption problems. Then, we propose
a novel hierarchical computation architecture by inserting an edge layer
between the conventional user layer and cloud layer. Based on the proposed
architecture, we further develop an innovated operation mechanism to improve
the performance of mobile AR applications. Three key technologies are also
discussed to further assist the proposed AR architecture. Simulation results
are finally provided to verify that our proposals can significantly improve the
latency and energy performance as compared against existing baseline schemes.


  We present several implementations of the Metropolis method, an adaptive
Monte Carlo algorithm, which allow for the calculation of multi-dimensional
integrals over arbitrary on-shell four-momentum phase space. The Metropolis
technique reveals itself very suitable for the treatment of high energy
processes in particle physics, particularly when the number of final state
objects and of kinematic constraints on the latter gets larger. We compare the
performances of the Metropolis algorithm with those of other programs widely
used in numerical simulations.


  In this paper, we study steady 2D periodic blood flow propagating along blood
vessels with free boundary conditions. In particular, we focus on the dynamic
behavior of flows with harmonic vorticity and time dependent body force. An
equivalent formulation with fix boundary is developed by utilizing flow force
functions. The local bifurcation result is obtained by Crandall-Rabinowitz
theorem. The existence of a local $C^1$-curve of small-amplitude solution is
strictly proved.


  A combined dynamics consisting of Brownian motion and L\'evy flights is
exhibited by a variety of biological systems performing search processes.
Assessing the search reliability of ever locating the target and the search
efficiency of doing so economically of such dynamics thus poses an important
problem. Here we model this dynamics by a one-dimensional fractional
Fokker-Planck equation combining unbiased Brownian motion and L\'evy flights.
By solving this equation both analytically and numerically we show that the
superposition of recurrent Brownian motion and L\'evy flights with stable
exponent $\alpha<1$, by itself implying zero probability of hitting a point on
a line, lead to transient motion with finite probability of hitting any point
on the line. We present results for the exact dependence of the values of both
the search reliability and the search efficiency on the distance between the
starting and target positions as well as the choice of the scaling exponent
$\alpha$ of the L\'evy flight component.


  Magnetic semiconductor quantum dots with a few carriers represent an
interesting model system where ferromagnetic interactions can be tuned by
voltage. By designing the geometry of a doped quantum dot, one can tailor the
anisotropic quantum states of magnetic polarons. The strong anisotropy of
magnetic polaron states in disk-like quantum dots with holes comes from the
spin splitting in the valence band. The binding energy and spontaneous
magnetization of quantum dots oscillate with the number of particles and
reflect the shell structure. Due to the Coulomb interaction, the maximum
binding energy and spin polarization of magnetic polarons occur in the regime
of Hund's rule when the total spin of holes in a quantum dot is maximum. With
increasing number of particles in a quantum dot and for certain orbital
configurations, the ferromagnetic state becomes especially stable or may have
broken symmetry. In quantum dots with a strong ferromagnetic interaction, the
ground state can undergo a transition from a magnetic to a nonmagnetic state
with increasing temperature or decreasing exchange interaction. The
characteristic temperature and fluctuations of magnetic polarons depend on the
binding energy and degeneracy of the shell. The capacitance spectra of magnetic
quantum dots with few particles reveal the formation of polaron states.


  We review the state space decomposition techniques for the assessment of the
noise properties of autonomous oscillators, a topic of great practical and
theoretical importance for many applications in many different fields, from
electronics, to optics, to biology. After presenting a rigorous definition of
phase, given in terms of the autonomous system isochrons, we provide a
generalized projection technique that allows to decompose the oscillator
fluctuations in terms of phase and amplitude noise, pointing out that the very
definition of phase (and orbital) deviations depends of the base chosen to
define the aforementioned projection. After reviewing the most advanced
theories for phase noise, based on the use of the Floquet basis and of the
reduction of the projected model by neglecting the orbital fluctuations, we
discuss the intricacies of the phase reduction process pointing out the
presence of possible variations of the noisy oscillator frequency due to
amplitude-related effects.


  The high momentum tail (HMT) in the momentum distribution of nucleons above
the Fermi surface has been regarded as an evidence of short-range correlations
(SRCs) in atomic nuclei. It has been showcased recently that the np
Bremsstrahlung radiation in heavy ion reactions can be used to extract HMT
information. The Richardson-Lucy (RL) algorithm is introduced to the
reconstruction of the original Bremsstrahlung {\gamma}-ray energy spectrum from
experimental measurements. By solving the inverse problem of the detector
response to the {\gamma}-rays, the original energy spectrum of the
Bremsstrahlung {\gamma} in 25 MeV/u 86Kr + 124Sn has been reconstructed and
compared to the isospin- and momentum-dependent Boltzmann-Uehling-Uhlenbeck
(IBUU) simulations. The analysis based on hypothesis test suggests the
existence of the HMT of nucleons in nuclei, in accordance with the previous
conclusions. With its effectiveness being demonstrated, it is feasible to apply
the RL algorithm in future experiments of measuring the Bremsstrahlung
{\gamma}-rays in heavy ion reactions.


  This paper proposes a non-monetary traffic demand management scheme, named
CARMA, as a fair solution to the morning commute congestion. We consider
heterogeneous commuters traveling through a single bottleneck that differ in
both the desired arrival time and Value of Time (VOT). We consider a
generalized notion of VOT by allowing it to vary dynamically on each day (e.g.,
according to trip purpose and urgency), rather than being a static
characteristic of each individual. In our CARMA scheme, the bottleneck is
divided into a fast lane that is kept in free flow and a slow lane that is
subject to congestion. We introduce a non-tradable mobility credit, named
karma, that is used by commuters to bid for access to the fast lane. Commuters
who get outbid or do not participate in the CARMA scheme instead use the slow
lane. At the end of each day, karma collected from the bidders is
redistributed, and the process repeats day by day. We model the collective
commuter behaviors under CARMA as a Dynamic Population Game (DPG), in which a
Stationary Nash Equilibrium (SNE) is guaranteed to exist. Unlike existing
monetary schemes, CARMA is demonstrated, both analytically and numerically, to
achieve a) an equitable traffic assignment with respect to heterogeneous income
classes and b) a strong Pareto improvement in the long-term average travel
disutility with respect to no policy intervention. With extensive numerical
analysis, we show that CARMA is able to retain the same congestion reduction as
an optimal monetary tolling scheme under uniform karma redistribution and even
outperform tolling under a well-designed redistribution scheme. We also
highlight the privacy-preserving feature of CARMA, i.e., its ability to tailor
to the private preferences of commuters without centrally collecting the
information.


  Trace-wise noise is a type of noise often seen in seismic data, which is
characterized by vertical coherency and horizontal incoherency. Using
self-supervised deep learning to attenuate this type of noise, the conventional
blind-trace deep learning trains a network to blindly reconstruct each trace in
the data from its surrounding traces; it attenuates isolated trace-wise noise
but causes signal leakage in clean and noisy traces and reconstruction errors
next to each noisy trace. To reduce signal leakage and improve denoising, we
propose a new loss function and masking procedure in semi-blind-trace deep
learning. Our hybrid loss function has weighted active zones that cover masked
and non-masked traces. Therefore, the network is not blinded to clean traces
during their reconstruction. During training, we dynamically change the masks'
characteristics. The goal is to train the network to learn the characteristics
of the signal instead of noise. The proposed algorithm enables the designed
U-net to detect and attenuate trace-wise noise without having prior information
about the noise. A new hyperparameter of our method is the relative weight
between the masked and non-masked traces' contribution to the loss function.
Numerical experiments show that selecting a small value for this parameter is
enough to significantly decrease signal leakage. The proposed algorithm is
tested on synthetic and real off-shore and land datasets with different noises.
The results show the superb ability of the method to attenuate trace-wise noise
while preserving other events. An implementation of the proposed algorithm as a
Python code is also made available.


  We construct axially symmetric solutions of U(1) gauged Skyrme model.
Possessing a nonvanishing magnetic moment, these solitons have also a nonzero
angular momentum proportional to the electric charge.


  A catalog containing details of the highest-energy cosmic rays recorded
through the detection of extensive air-showers at the Pierre Auger Observatory
is presented with the aim of opening the data to detailed examination.
Descriptions of the 100 showers created by the highest-energy particles
recorded between 1 January 2004 and 31 December 2020 are given for cosmic rays
that have energies in the range 78 EeV to 166 EeV. Details are also given of a
further nine very-energetic events that have been used in the calibration
procedure adopted to determine the energy of each primary. A sky plot of the
arrival directions of the most energetic particles is shown. No interpretations
of the data are offered.


  Asking insightful questions is crucial for acquiring knowledge and expanding
our understanding of the world. However, the importance of questioning has been
largely overlooked in AI research, where models have been primarily developed
to answer questions. With the recent advancements of large language models
(LLMs) like ChatGPT, we discover their capability to ask high-quality questions
when provided with a suitable prompt. This discovery presents a new opportunity
to develop an automatic questioning system. In this paper, we introduce
ChatCaptioner, a novel automatic-questioning method deployed in image
captioning. Here, ChatGPT is prompted to ask a series of informative questions
about images to BLIP-2, a strong vision question-answering model. By keeping
acquiring new visual information from BLIP-2's answers, ChatCaptioner is able
to generate more enriched image descriptions. We conduct human-subject
evaluations on common image caption datasets such as COCO, Conceptual Caption,
and WikiArt, and compare ChatCaptioner with BLIP-2 as well as ground truth. Our
results demonstrate that ChatCaptioner's captions are significantly more
informative, receiving three times as many votes from human evaluators for
providing the most image information. Besides, ChatCaptioner identifies 53%
more objects within the image than BLIP-2 alone measured by WordNet synset
matching. Code is available at https://github.com/Vision-CAIR/ChatCaptioner


  It is shown that thermally excited plasmon-polariton modes can strongly
mediate, enhance and \emph{tune} the near-field radiation transfer between two
closely separated graphene sheets. The dependence of near-field heat exchange
on doping and electron relaxation time is analyzed in the near infra-red within
the framework of fluctuational electrodynamics. The dominant contribution to
heat transfer can be controlled to arise from either interband or intraband
processes. We predict maximum transfer at low doping and for plasmons in two
graphene sheets in resonance, with orders-of-magnitude enhancement (e.g. $10^2$
to $10^3$ for separations between $0.1\mu m$ to $10nm$) over the
Stefan-Boltzmann law, known as the far field limit. Strong, tunable, near-field
transfer offers the promise of an externally controllable thermal switch as
well as a novel hybrid graphene-graphene thermoelectric/thermophotovoltaic
energy conversion platform.


  The Tur\'an density \pi(H) of a family H of k-graphs is the limit as n tends
to infinity of the maximum edge density of an H-free k-graph on n vertices. Let
I^k consist of all possible Tur\'an densities and let F^k be the set of Tur\'an
densities of finite k-graph families.
  Here we prove that F^k contains every density obtained from an arbitrary
finite construction by optimally blowing it up and using recursion inside the
specified set of parts. As an application, we show that F^k contains an
irrational number for each k\ge 3.
  Also, we show that I^k has cardinality of the continuum. In particular, I^k
is not equal to F^k.


  This work is the first step towards understanding thermionic transport
properties of graphene/phosphorene/graphene van der Waals heterostructures in
contact with gold electrodes by using density functional theory based first
principles calculations combined with real space Green's function formalism. We
show that for monolayer phosphorene in the heterostructure, quantum tunneling
dominates the transport. By adding more phosphorene layers, one can switch from
tunneling dominated transport to thermionic dominated transport, resulting in
transporting more heat per charge carrier, thus, enhancing the cooling
coefficient of performance. The thermionic coefficient of performance for the
proposed device is 18.5 at 600 K corresponding to an equivalent ZT of 0.13,
which is significant for nanoscale devices.


  We demonstrate a method for training a convolutional neural network with
simulated images for usage on real-world experimental data. Modern machine
learning methods require large, robust training data sets to generate accurate
predictions. Generating these large training sets requires a significant
up-front time investment that is often impractical for small-scale
applications. Here we demonstrate a `full-stack' computational solution, where
the training data set is generated on-the-fly using a noise injection process
to produce simulated data characteristic of the experimental system.


  In this work we provide a survey of Fuglede's flux extensions of first order
partial differential operators, a concept largely forgotten today. A long the
way we also survey the classical weak and strong extensions of PDE operators
and the works of Friedrichs and H\"ormander. We give several applications of
this theory showing its usefulness, as well as connecting it to more recent
developments in connection to various sharp versions of the divergence theorem.
In particular, we use it to prove a generalization of Morera's theorem valid
for general first order operators. Using this theory we also prove a new local
limit formula for the maximal extension of a first order operator. We initiate
a study of this limit and connect it to the wave cone of the operator, a
concept that first arose in the theory of compensated compactness. Hopefully,
this will contribute to a rival of Fuglede's beautiful ideas.


  The structure of the Cabibbo-Kobayashi-Maskawa (CKM) matrix is analyzed from
the standpoint of a composite model. A model is constructed with three families
of quarks, by taking tensor products of sufficient numbers of spin-1/2
representations and imagining the dominant terms in the mass matrix to arise
from spin-spin interactions. Generic results then obtained include the familiar
relation $|V_{us}| = (m_d/m_s)^{1/2} - (m_u/m_c)^{1/2}$, and a less frequently
seen relation $|V_{cb}| = \sqrt{2} [(m_s/m_b) - (m_c/m_t)]$. The magnitudes of
$V_{ub}$ and $V_{td}$ come out naturally to be of the right order. The phase in
the CKM matrix can be put in by hand, but its origin remains obscure.


  An ultra-compact wearable antenna, for electronic travel aid (ETA)
applications, is presented. An AMC-backed twin arrow antenna, operative in the
24.05-24.25 GHz frequency band, has been designed for imaging systems
supporting ETA. Artificial Magnetic Conductor (AMC) is combined with the
antenna with the aim of reducing the backward radiation to the wearing person
while improving its radiation properties and bandwidth, all this without
increasing the initial area of the antenna. Prototypes of the AMC-antenna have
been fabricated and measured. In order to test its performance for the
application, imaging have been conducted by means of synthetic aperture radar
(SAR) techniques by placing the antenna in the arm of a user to take advantage
of natural body movement. Electromagnetic images have been obtained and the
target has been identified, demonstrating the suitability of the AMC-antenna
for the ETA system.


  We consider two multi-armed bandit problems with $n$ arms: (i) given an
$\epsilon > 0$, identify an arm with mean that is within $\epsilon$ of the
largest mean and (ii) given a threshold $\mu_0$ and integer $k$, identify $k$
arms with means larger than $\mu_0$. Existing lower bounds and algorithms for
the PAC framework suggest that both of these problems require $\Omega(n)$
samples. However, we argue that these definitions not only conflict with how
these algorithms are used in practice, but also that these results disagree
with intuition that says (i) requires only $\Theta(\frac{n}{m})$ samples where
$m = |\{ i : \mu_i > \max_{i \in [n]} \mu_i - \epsilon\}|$ and (ii) requires
$\Theta(\frac{n}{m}k)$ samples where $m = |\{ i : \mu_i > \mu_0 \}|$. We
provide definitions that formalize these intuitions, obtain lower bounds that
match the above sample complexities, and develop explicit, practical algorithms
that achieve nearly matching upper bounds.


  We present a multiwavelength study of the formation and ejection of a plasma
blob and associated EUV waves in AR NOAA 11176, observed by SDO/AIA and STEREO
on 25 March 2011. SDO/AIA images clearly show the formation and ejection of a
plasma blob from the lower solar atmosphere at ~9 min prior to the onset of the
M1.0 flare. This onset of the M-class flare happened at the site of the blob
formation, while the blob was rising in a parabolic path with an average speed
of ~300 km/s. The blob also showed twisting and de-twisting motion in the lower
corona, and the blob speed varied from ~10-540 km/s. The faster and slower EUV
wavefronts were observed in front of the plasma blob during its impulsive
acceleration phase. The faster EUV wave propagated with a speed of ~785 to 1020
km/s, whereas the slower wavefront speed varied in between ~245 and 465 km/s.
The timing and speed of the faster wave match the shock speed estimated from
the drift rate of the associated type II radio burst. The faster wave
experiences a reflection by the nearby AR NOAA 11177. In addition, secondary
waves were observed (only in the 171 \AA channel), when the primary fast wave
and plasma blob impacted the funnel-shaped coronal loops. The HMI magnetograms
revealed the continuous emergence of new magnetic flux along with shear flows
at the site of the blob formation. It is inferred that the emergence of twisted
magnetic fields in the form of arch-filaments/"anemone-type" loops is the
likely cause for the plasma blob formation and associated eruption along with
the triggering of M-class flare. Furthermore, the faster EUV wave formed ahead
of the blob shows the signature of fast-mode MHD wave, whereas the slower wave
seems to be generated by the field line compression by the plasma blob. The
secondary wave trains originated from the funnel-shaped loops are probably the
fast magnetoacoustic waves.


  In an ever-expanding world of domain-specific knowledge, the increasing
complexity of consuming, and storing information necessitates the generation of
summaries from large information repositories. However, every persona of a
domain has different requirements of information and hence their summarization.
For example, in the healthcare domain, a persona-based (such as Doctor, Nurse,
Patient etc.) approach is imperative to deliver targeted medical information
efficiently. Persona-based summarization of domain-specific information by
humans is a high cognitive load task and is generally not preferred. The
summaries generated by two different humans have high variability and do not
scale in cost and subject matter expertise as domains and personas grow.
Further, AI-generated summaries using generic Large Language Models (LLMs) may
not necessarily offer satisfactory accuracy for different domains unless they
have been specifically trained on domain-specific data and can also be very
expensive to use in day-to-day operations. Our contribution in this paper is
two-fold: 1) We present an approach to efficiently fine-tune a domain-specific
small foundation LLM using a healthcare corpus and also show that we can
effectively evaluate the summarization quality using AI-based critiquing. 2) We
further show that AI-based critiquing has good concordance with Human-based
critiquing of the summaries. Hence, such AI-based pipelines to generate
domain-specific persona-based summaries can be easily scaled to other domains
such as legal, enterprise documents, education etc. in a very efficient and
cost-effective manner.


  From 23 - 27 July 2001 in the Institute of Nuclear Research and Nuclear
Energy, Bulgarian Academy of Sciences, Sofia was held a seminar under the
title: "Possible correlations between electromagnetic earth fields and future
earthquakes" organized by the Institute's Department of "Astrophysical Objects
and Environment".
  As a main result of the first two days seminar work was the prediction of the
direction and the day of the Skyros, Greece earthquake, that was confirned in
the next day: Aeg. Sea, 07/26 00:21:37, 39.06N 24.34E, Depth 19 km, Mag 6.3-
http://www.noa.gr/English/home-en.html.
  Analogously, a month later the day of Yambol, Bulgaria eartquake was
predicted. The papers of A.M.Galper et al (2001), "High- energy charged
particle flux variations in vicinity of Earth as earthquakes precursors",
http://www.pereplet.ru/pops/quakes.html, and
http://science.rambler.ru/db/msg.html?mid=1168269&uri=galper.html, the analysis
of NASA data from http://www.sel.noaa.gov, explained why the Seminar main
hypothesis works and give an optimism the combined earth and satellite
monitoring for earthquakes "prediction" will succeed this time.
  The authors are looking forward and waiting with respect for opinions,
suggestions, and possible collaboration.


Resubmitted due to LATEXing problems


  Virtual try-on is a promising computer vision topic with a high commercial
value wherein a new garment is visually worn on a person with a photo-realistic
effect. Previous studies conduct their shape and content inference at one
stage, employing a single-scale warping mechanism and a relatively
unsophisticated content inference mechanism. These approaches have led to
suboptimal results in terms of garment warping and skin reservation under
challenging try-on scenarios. To address these limitations, we propose a novel
virtual try-on method via progressive inference paradigm (PGVTON) that
leverages a top-down inference pipeline and a general garment try-on strategy.
Specifically, we propose a robust try-on parsing inference method by
disentangling semantic categories and introducing consistency. Exploiting the
try-on parsing as the shape guidance, we implement the garment try-on via
warping-mapping-composition. To facilitate adaptation to a wide range of try-on
scenarios, we adopt a covering more and selecting one warping strategy and
explicitly distinguish tasks based on alignment. Additionally, we regulate
StyleGAN2 to implement re-naked skin inpainting, conditioned on the target skin
shape and spatial-agnostic skin features. Experiments demonstrate that our
method has state-of-the-art performance under two challenging scenarios. The
code will be available at https://github.com/NerdFNY/PGVTON.


  In this paper, we discuss questions related to the renormalizability of the
classical statistical approximation, an approximation scheme that has been used
recently in several studies of out-of-equilibrium problems in Quantum Field
Theory. Although the ultraviolet power counting in this approximation scheme is
identical to that of the unapproximated quantum field theory, this
approximation is not renormalizable. The leading cause of this
non-renormalizability is the breakdown of Weinberg's theorem in this
approximation. We also discuss some practical implications of this negative
result for simulations that employ this approximation scheme, and we speculate
about a possible modification of the classical statistical approximation in
order to systematically subtract the leading residual divergences.


  The physics underlying spectral redshift of thermally generated surface
phonon-polaritons (SPhPs) observed in near-field thermal spectroscopy is
investigated. Numerically exact fluctuational electrodynamics simulations of
the thermal near field emitted by a silicon carbide surface scattered in the
far zone by an intrinsic silicon probe show that SPhP resonance redshift is a
physical phenomenon. A maximum SPhP redshift of 19 cm-1 is predicted for a
200-nm-diameter hemispherical probing tip and a vacuum gap of 10 nm. Resonance
redshift is mediated by electromagnetic gap modes excited in the vacuum gap
separating the probe and the surface when the probing tip is much larger than
the gap size. The impact of gap modes on the scattered field can be mitigated
with a probing tip size approximately equal to or smaller than the vacuum gap.
However, sharp probing tips induce important spectral broadening of the
scattered field. It is also demonstrated that a dipole approximation with
multiple reflections cannot be used for explaining the physics and predicting
the amount of redshift in near-field thermal spectroscopy. This work shows that
the scattered field in the far zone is a combination of the thermal near field
emitted by the surface, and electromagnetic interactions between the probe and
the surface. Spectroscopic analysis of near-field thermal emission thus
requires a numerically exact fluctuational electrodynamics framework for
modeling probe-surface interactions.


  We report the realization of correlated, density-dependent tunneling for
fermionic 40K atoms trapped in an optical lattice. By appropriately tuning the
frequency difference between a pair of Raman beams applied to a spin-polarized
gas, simultaneous spin transitions and tunneling events are induced that depend
on the relative occupations of neighboring lattice sites. Correlated spin-flip
tunneling is spectroscopically resolved using gases prepared in opposite spin
states, and the inferred Hubbard interaction energy is compared with a
tight-binding prediction. We show that the laser-induced correlated tunneling
process generates doublons via loss induced by light-assisted collisions.
Furthermore, by controllably introducing vacancies to a spin-polarized gas, we
demonstrate that correlated tunneling is suppressed when neighboring lattice
sites are unoccupied.


  Barkhausen current noise is used to probe the slow field-driven conversion of
the glassy relaxor ferroelectric state to an ordered ferroelectric (FE) state.
The frequent presence of distinct micron-scale Barkhausen events well before
the polarization current starts to speed up shows that the process is not a
conventional nucleation-limited one. The prevalence of reverse switching events
near the onset of the rapid part of the transition strongly indicates that
electric dipole interactions play a key role. The combination of Barkhausen
noise changes and changes in the complex dielectric response indicate that the
process consists of an initial mixed-alignment domain formation stage followed
by growth of the domains aligned with the applied field.


  A nonlinear unified fluid model that describes the Equatorial Electrojet,
including the Farley-Buneman and gradient-drift plasma instabilities, is
defined and shown to be a noncanonical Hamiltonian system. Two geometric
constants of motion for the model are obtained and shown to be Casimir
invariants. A reformulation of the model shows the roles of the
density-gradient scale-length ($L_n$) and the cross-field drift-velocity
(${\upsilon}_E$) in controlling the dynamics of unstable modes in the growing,
transition, and saturation phases of a simulation.


  X (formerly Twitter) has evolved into a contemporary agora, offering a
platform for individuals to express opinions and viewpoints on current events.
The majority of the topics discussed on Twitter are directly related to ongoing
events, making it an important source for monitoring public discourse. However,
linking tweets to specific news presents a significant challenge due to their
concise and informal nature. Previous approaches, including topic models,
graph-based models, and supervised classifiers, have fallen short in
effectively capturing the unique characteristics of tweets and articles.
  Inspired by the success of the CLIP model in computer vision, which employs
contrastive learning to model similarities between images and captions, this
paper introduces a contrastive learning approach for training a representation
space where linked articles and tweets exhibit proximity. We present our
contrastive learning approach, CATBERT (Contrastive Articles Tweets BERT),
leveraging pre-trained BERT models. The model is trained and tested on a
dataset containing manually labeled English and Polish tweets and articles
related to the Russian-Ukrainian war. We evaluate CATBERT's performance against
traditional approaches like LDA, and the novel method based on OpenAI
embeddings, which has not been previously applied to this task. Our findings
indicate that CATBERT demonstrates superior performance in associating tweets
with relevant news articles. Furthermore, we demonstrate the performance of the
models when applied to finding the main topic -- represented by an article --
of the whole cascade of tweets. In this new task, we report the performance of
the different models in dependence on the cascade size.


  In this paper we first introduce quermassintegrals for free boundary
hypersurfaces in the $(n+1)$-dimensional Euclidean unit ball. Then we solve
some related isoperimetric type problems for convex free boundary
hypersurfaces, which lead to new Alexandrov-Fenchel inequalities. In
particular, for $n=2$ we obtain a Minkowski-type inequality and for $n=3$ we
obtain an optimal Willmore-type inequality. To prove these estimates, we employ
a specifically designed locally constrained inverse harmonic mean curvature
flow with free boundary.


  The trigger system for the Auger fluorescence telescopes is implemented in
hard- and software for an efficient selection of fluorescence light tracks
induced by high-energy extensive air showers. The algorithm of the third stage
uses the multiplicity signal of the hardware for fast rejection of lightning
events with above 99% efficiency. In a second step direct muon hits in the
camera and random triggers are rejected by analyzing the space-time correlation
of the pixels. The trigger algorithm was tested with measured and simulated
showers and implemented in the electronics of the fluorescence telescopes. A
comparison to a prototype trigger without multiplicity shows the superiority of
this approach, e.g. the false rejection rate is a factor 10 lower.


  This work explores the degree to which grammar acquisition is driven by
language `simplicity' and the source modality (speech vs. text) of data. Using
BabyBERTa as a probe, we find that grammar acquisition is largely driven by
exposure to speech data, and in particular through exposure to two of the
BabyLM training corpora: AO-Childes and Open Subtitles. We arrive at this
finding by examining various ways of presenting input data to our model. First,
we assess the impact of various sequence-level complexity based curricula. We
then examine the impact of learning over `blocks' -- covering spans of text
that are balanced for the number of tokens in each of the source corpora
(rather than number of lines). Finally, we explore curricula that vary the
degree to which the model is exposed to different corpora. In all cases, we
find that over-exposure to AO-Childes and Open Subtitles significantly drives
performance. We verify these findings through a comparable control dataset in
which exposure to these corpora, and speech more generally, is limited by
design. Our findings indicate that it is not the proportion of tokens occupied
by high-utility data that aids acquisition, but rather the proportion of
training steps assigned to such data. We hope this encourages future research
into the use of more developmentally plausible linguistic data (which tends to
be more scarce) to augment general purpose pre-training regimes.


  We study the dipole for a redshift sample of Abell/ACO clusters. To elucidate
the constraints it places on dark matter models, we use numerical simulations
based on the Zel'dovich approximation. We run 20 realizations of each of six
different dark matter models: four of these have a density parameter
$\Omega_0=1$, while the other two have $\Omega_0=0.2$, one with and one without
a cosmological constant term. For the Abell/ACO sample, we evaluate the
parameter $\beta=\Omega_0^{0.6}/b_{ cl}$, which reaches its asymptotic value at
$R=160 Mpc/h$. We find $\beta=0.15\pm 0.04$ and $0.25\pm 0.06$ in LG and CMB
frames respectively. After identifying in the simulations LG-like observers, we
construct mock cluster samples. We find that an alignment between the cluster
dipole and observer velocity, such as that observed (about 20 degrees) should
not be expected necessarily in the simulations. This, together with the large
observer-to-observer variance estimates of $\beta$, makes it difficult to place
any firm constraints on cosmological models. Our results demonstrate that the
large amplitude and convergence depth of the cluster dipole cannot be taken as
strong evidence either for or against a low--density Universe.


  A small volume of space, nearly on-axis behind a gravitational lens with
respect to a given source, will receive a greatly increased radiation flux. In
the idealized case of a point mass lens acting on a point source in complete
isolation, the volume will approach zero only as the flux tends to infinity; in
fact, the volume weighted rms flux is divergent. In realistic cases, finite
source size and the effects of other gravitational deflections (i.e., non-zero
shear) limit the maximum flux and considerably complicate the physics, but very
large fluxes are still produced in small volumes. We consider the physics and
statistics of these Extreme Gravitational Lensing Events (EGLE) and present an
initial examination of their possible astrophysical effects for various known
and putative populations of lensing objects and sources, with particular
attention to the case in which finite source size is important but shear is
not.


  Future colliders are an essential component of a strategic vision for
particle physics. Conceptual studies and technical developments for several
exciting future collider options are underway internationally. In order to
realize a future collider, a concerted accelerator R\&D program is required.
The U.S. HEP accelerator R\&D program currently has no direct effort in
collider-specific R\&D area. This shortcoming greatly compromises the U.S.
leadership role in accelerator and particle physics. In this white paper, we
propose a new national accelerator R\&D program on future colliders and outline
the important characteristics of such a program.


  The observation that concepts from quantum information has generated many
alternative indicators of quantum phase transitions hints that quantum phase
transitions possess operational significance with respect to the processing of
quantum information. Yet, studies on whether such transitions lead to quantum
phases that differ in their capacity to process information remain limited.
Here We show that there exist quantum phase transitions that cause a distinct
qualitative change in our ability to simulate certain quantum systems under
perturbation of an external field by local operations and classical
communication. In particular, we show that in certain quantum phases of the XY
model, adiabatic perturbations of the external magnetic field can be simulated
by local spin operations, whereas the resulting effect within other phases
results in coherent non-local interactions. We discuss the potential
implications to adiabatic quantum computation, where a computational advantage
exists only when adiabatic perturbation results in coherent multi-body
interactions.


  In this article, we present the multi-viewpoint and multi-wavelength analysis
of an atypical solar jet based on the data from Solar Dynamics Observatory,
SOlar, and Heliospheric Observatory, and Solar TErrestrial RElations
Observatory. It is usually believed that the coronal mass ejections (CMEs) are
developed from the large scale solar eruptions in the lower atmosphere.
However, the kinematical and spatial evolution of the jet on 2013 April 28
guide us that the jet was clearly associated with a narrow CME having a width
of approx 25 degrees with a speed of 450 km/s. To better understand the link
between the jet and the CME, we did the coronal potential field extrapolation
from the line of sight magnetogram of the AR. The extrapolations present that
the jet eruption follows exactly the same path of the open magnetic field lines
from the source region which provides the route for the jet material to escape
from the solar surface towards the outer corona.


  Following the logic of the great Chinese warrior-philosopher Master Sun Tzu,
  "The rules of the military are five: measurement, assessment, calculation,
comparison and victory", we address the problem of what we know, think we know,
and think about the QCD coupling.


  We study how the eightfold-degeneracy in the ($\theta_{13},\delta$) plane
observed in $\gamma \sim 100$ $\beta$-beams can be reduced by periodically
changing the ions in the storage ring. This ``ions cocktail'' allows to change
the neutrino energy, at fixed $\gamma$, by choosing ions with different decay
energies. We propose to combine the standard $^6$He and $^{18}$Ne beams with
$^8$Li and $^8$B ones. These latter two ions have peaked $\nu_e \to \nu_\mu$
oscillation probabilities for $\gamma = 100$ at a baseline $L \sim 700$ Km. At
this distance and this $\gamma$ the oscillation probability of $^6$He and
$^{18}$Ne neutrinos is at its second maximum. This setup is particularly suited
for large enough values of $\theta_{13}$ (within reach at T2K-I) and it allows
solving most of the eightfold-degeneracy, measuring $\theta_{13}, \delta$ and
the sign of the atmospheric mass difference for values of $\theta_{13} \geq
5^\circ$.


  It is shown that a significant measurement of the longitudinal structure
function $F_L(x,Q^2)$ can be performed at HERA, for $Q^2 = 2 GeV^2$ and $Q^2 =
5 GeV^2$ and for x around $10^{-4}$, using radiative events with hard photon
emission collinear to the incident lepton beam, under the present running
conditions and with an integrated luminosity of 10 $pb^{-1}$. The influence of
experimental conditions is discussed.


  In this paper we deal with the problem of classifying the genera of quotient
curves $\mathcal{H}_q/G$, where $\mathcal{H}_q$ is the
$\mathbb{F}_{q^2}$-maximal Hermitian curve and $G$ is an automorphism group of
$\mathcal{H}_q$. The groups $G$ considered in the literature fix either a point
or a triangle in the plane ${\rm PG}(2,q^6)$. In this paper, we give a complete
list of genera of quotients $\mathcal{H}_q/G$, when $G \leq {\rm
Aut}(\mathcal{H}_q) \cong {\rm PGU}(3,q)$ does not leave invariant any point or
triangle in the plane. As a result, the classification of subgroups $G$ of
${\rm PGU}(3,q)$ satisfying this property is given up to isomorphism.


  We present a method of calculating crystal field coefficients of
rare-earth/transition-metal (RE-TM) magnets within density-functional theory
(DFT). The principal idea of the method is to calculate the crystal field
potential of the yttrium analogue ("Y-analogue") of the RE-TM magnet, i.e. the
material where the lanthanide elements have been substituted with yttrium. The
advantage of dealing with Y-analogues is that the methodological and conceptual
difficulties associated with treating the highly-localized 4f electrons in DFT
are avoided, whilst the nominal valence electronic structure principally
responsible for the crystal field is preserved. In order to correctly describe
the crystal field potential in the core region of the atoms we use the
projector-augmented wave formalism of DFT, which allows the reconstruction of
the full charge density and electrostatic potential. The Y-analogue crystal
field potentials are combined with radial 4f charge densities obtained in
self-interaction-corrected calculations on the lanthanides to obtain crystal
field coefficients. We demonstrate our method on a test set of 10 materials
comprising 9 RE-TM magnets and elemental Tb. We show that the calculated easy
directions of magnetization agree with experimental observations, including a
correct description of the anisotropy within the basal plane of Tb and
NdCo$_5$. We further show that the Y-analogue calculations generally agree
quantitatively with previous calculations using the open-core approximation to
treat the 4f electrons, and argue that our simple approach may be useful for
large-scale computational screening of new magnetic materials.


  This paper is devoted to rejective sampling. We provide an expansion of joint
inclusion probabilities of any order in terms of the inclusion probabilities of
order one, extending previous results by H\'ajek (1964) and H\'ajek (1981) and
making the remainder term more precise. Following H\'ajek (1981), the proof is
based on Edgeworth expansions. The main result is applied to derive bounds on
higher order correlations, which are needed for the consistency and asymptotic
normality of several complex estimators.


  This paper describes the optimisation theory on which VPFIT, a non-linear
least-squares program for modelling absorption spectra, is based. Particular
attention is paid to precision. Voigt function derivatives have previously been
calculated using numerical finite difference approximations. We show how these
can instead be computed analytically using Taylor series expansions and look-up
tables. We introduce a new optimisation method for an efficient descent path to
the best-fit, combining the principles used in both the Gauss-Newton and
Levenberg-Marquardt algorithms. A simple practical fix for ill-conditioning is
described, a common problem when modelling quasar absorption systems. We also
summarise how unbiased modelling depends on using an appropriate information
criterion to guard against over- or under-fitting.
  The methods and the new implementations introduced in this paper are aimed at
optimal usage of future data from facilities such as ESPRESSO/VLT and
HIRES/ELT, particularly for the most demanding applications such as searches
for spacetime variations in fundamental constants and attempts to detect
cosmological redshift drift.


  It is shown that all nontrivial elements in higher $K$-groups of toric
varieties over a class of regular rings are annihilated by iterations of the
natural Frobenius type endomorphisms. This is a higher analog of the triviality
of vector bundles on affine toric varieties.


  We address the issue of the compositeness of hadronic states and demonstrate
that starting with a genuine state of nonmolecular nature, but which couples to
some meson-meson component to be observable in that channel, if that state is
blamed for a bound state appearing below the meson-meson threshold it gets
dressed with a meson cloud and it becomes pure molecular in the limit case of
zero binding. We discuss the issue of the scales, and see that if the genuine
state has a mass very close to threshold, the theorem holds, but the molecular
probability goes to unity in a very narrow range of energies close to
threshold. The conclusion is that the value of the binding does not determine
the compositeness of a state. However, in such extreme cases we see that the
scattering length gets progressively smaller and the effective range grows
indefinitely. In other words, the binding energy does not determine the
compositeness of a state, but the additional information of the scattering
length and effective range can provide an answer. We also show that the
consideration of a direct attractive interaction between the mesons in addition
to having a genuine component, increases the compositeness of the state.
Explicit calculations are done for the $T_{cc}(3875)$ state, but are easily
generalized to any hadronic system.


  Artificial intelligence algorithms largely build on multi-layered neural
networks. Coping with their increasing complexity and memory requirements calls
for a paradigmatic change in the way these powerful algorithms are run. Quantum
computing promises to solve certain tasks much more efficiently than any
classical computing machine, and actual quantum processors are now becoming
available through cloud access to perform experiments and testing also outside
of research labs.
  Here we show in practice an experimental realization of an artificial
feed-forward neural network implemented on a state-of-art superconducting
quantum processor using up to 7 active qubits. The network is made of quantum
artificial neurons, which individually display a potential advantage in storage
capacity with respect to their classical counterpart, and it is able to carry
out an elementary classification task which would be impossible to achieve with
a single node. We demonstrate that this network can be equivalently operated
either via classical control or in a completely coherent fashion, thus opening
the way to hybrid as well as fully quantum solutions for artificial
intelligence to be run on near-term intermediate-scale quantum hardware.


  Experiments in bulk water confirm the existence of two local arrangements of
water molecules with different densities, but, because of inevitable freezing
at low temperature $T$, can not ascertain whether the two arrangements separate
in two phases. To avoid the freezing, new experiments measure the dynamics of
water at low $T$ on the surface of proteins, finding a crossover from a
non-Arrhenius regime at high $T$ to a regime that is approximately Arrhenius at
low $T$. Motivated by these experiments, Kumar et al. [Phys. Rev. Lett. 100,
105701 (2008)] investigated, by Monte Carlo simulations and mean field
calculations, the relation of the dynamic crossover with the coexistence of two
liquid phases in a cell model for water and predict that: (i) the dynamic
crossover is isochronic, i.e. the value of the crossover time $\tau_{\rm L}$ is
approximately independent of pressure $P$; (ii) the Arrhenius activation energy
$E_{\rm A}(P)$ of the low-$T$ regime decreases upon increasing $P$; (iii) the
temperature $T^*(P)$ at which $\tau$ reaches a fixed macroscopic time
$\tau^*\geq \tau_{\rm L}$ decreases upon increasing $P$; in particular, this is
true also for the crossover temperature $T_{\rm L}(P)$ at which $\tau=\tau_{\rm
L}$. Here, we compare these predictions with recent quasi elastic neutron
scattering (QENS) experiments performed by X.-Q. Chu {\it et al.} on hydrated
proteins at different values of $P$. We find that the experiments are
consistent with these three predictions.


  The formation of supermassive Population III stars with masses $\gtrsim$
10,000 Msun in primeval galaxies in strong UV backgrounds at $z \sim$ 15 may be
the most viable pathway to the formation of supermassive black holes by $z
\sim$ 7. Most of these stars are expected to live for short times and then
directly collapse to black holes, with little or no mass loss over their lives.
But we have now discovered that non-rotating primordial stars with masses close
to 55,000 Msun can instead die as highly energetic thermonuclear supernovae
powered by explosive helium burning, releasing up to 10$ ^{55}$ erg, or about
10,000 times the energy of a Type Ia supernova. The explosion is triggered by
the general relativistic contribution of thermal photons to gravity in the core
of the star, which causes the core to contract and explosively burn. The energy
release completely unbinds the star, leaving no compact remnant, and about half
of the mass of the star is ejected into the early cosmos in the form of heavy
elements. The explosion would be visible in the near infrared at $z \lesssim$
20 to {\it Euclid} and the Wide-Field Infrared Survey Telescope (WFIRST),
perhaps signaling the birth of supermassive black hole seeds and the first
quasars.


  We derive the effective action for classical strings coupled to dilatonic,
gravitational, and axionic fields. We show how to use this effective action
for: (i) renormalizing the string tension, (ii) linking ultraviolet divergences
to the infrared (long-range) interaction between strings, (iii) bringing
additional light on the special cancellations that occur for fundamental
strings, and (iv) pointing out the limitations of Dirac's celebrated
field-energy approach to renormalization.


  Recently, [JHEP 20 131 (2020)] obtained (a similar, scaled version of) the
($a,b$)-phase diagram derived from the Kazakov--Zinn-Justin solution of the
Hermitian two-matrix model with interactions \[\mathrm{Tr\,}\Big\{\frac{a}{4}
(A^4+B^4)+\frac{b}{2} ABAB\Big\}\,,\] starting from Functional Renormalization.
We comment on something unexpected: the phase diagram of [JHEP 20 131 (2020)]
is based on a $\beta_b$-function that does not have the one-loop structure of
the Wetterich-Morris Equation. This raises the question of how to reproduce the
phase diagram from a set of $\beta$-functions that is, in its totality,
consistent with Functional Renormalization. A non-minimalist, yet simple
truncation that could lead to the phase diagram is provided. Additionally, we
identify the ensemble for which the result of op. cit. would be entirely
correct.


  Rear-end collision accounts for around 8% of all vehicle crashes in the UK,
with the failure to notice or react to a brake light signal being a major
contributory cause. Meanwhile traditional incandescent brake light bulbs on
vehicles are increasingly being replaced by a profusion of designs featuring
LEDs. In this paper, we investigate the efficacy of brake light design using a
novel approach to recording subject reaction times in a simulation setting
using physical brake light assemblies. The reaction times of 22 subjects were
measured for ten pairs of LED and incandescent bulb brake lights. Three events
were investigated for each subject, namely the latency of brake light
activation to accelerator release (BrakeAcc), the latency of accelerator
release to brake pedal depression (AccPdl), and the cumulative time from light
activation to brake pedal depression (BrakePdl). To our knowledge, this is the
first study in which reaction times have been split into BrakeAcc and AccPdl.
Results indicate that the two brake lights containing incandescent bulbs led to
significantly slower reaction times compared to the tested eight LED lights.
BrakeAcc results also show that experienced subjects were quicker to respond to
the activation of brake lights by releasing the accelerator pedal.
Interestingly, the analysis also revealed that the type of brake light
influenced the AccPdl time, although experienced subjects did not always act
quicker than inexperienced subjects. Overall, the study found that different
designs of brake light can significantly influence driver response times.


  We demonstrate that twisting one part of a chiral photonic structure about
its helical axis produces a single circularly polarized localized mode that
gives rise to an anomalous crossover in propagation. Up to a crossover
thickness, this defect results in a peak in transmission and exponential
scaling of the linewidth for a circularly polarized wave with the same
handedness as structure. Above the crossover, however, the linewidth saturates
and the defect mode can be excited only by the oppositely polarized wave,
resulting in a peak in reflection instead of transmission.


  In this note we consider a branching Brownian motion (BBM) on $\mathbb{R}$ in
which a particle at spatial position $y$ splits into two at rate $\beta y^2$,
where $\beta>0$ is a constant. This is a critical breeding rate for BBM in the
sense that the expected population size blows up in finite time while the
population size remains finite, almost surely, for all time. We find an
asymptotic for the almost sure rate of growth of the population.


  We study theories of type $D_4$ in class-S, with nonabelian
outer-automorphism twists around various cycles of the punctured Riemann
surface $C$. We propose an extension of previous formul\ae\ for the
superconformal index to cover this case and classify the SCFTs corresponding to
fixtures (3-punctured spheres). We then go on to study families of SCFTs
corresponding to once-punctured tori and 4-punctured spheres. These exhibit new
behaviours, not seen in previous investigations. In particular, the generic
theory with 4 punctures on the sphere from non-commuting $\mathbb{Z}_2$ twisted
sectors has six distinct weakly-coupled descriptions.


  We investigate quantitatively the extent to which having a primordial
leptonic asymmetry (n_nu \neq n_nubar) relaxes the bounds on light sterile
neutrinos imposed by BBN and LSS. We adopt a few assumptions that allow us to
solve the neutrino evolution equations over a broad range of mixing parameters
and asymmetries. For the general cases of sterile mixing with the electron or
muon neutrino, we identify the regions that can be reopened. For the particular
case of a LSND-like sterile neutrino, soon to be rejected or confirmed by
MiniBooNE, we find that an asymmetry of the order of 10^-4 is needed to lift
the conflicts with cosmology.


  In this note, we generalized Berndtsson's result about the Nakano positivity
of direct image sheaves to some special singular cases. We found this is the
case when the metric of twisted line bundle have logarithmic or Poincare type
singularities along the divisors.


  Recently, the Auger group has extracted the proton-air cross section from
observations of air showers produced by cosmic ray protons (and nuclei)
interacting in the atmosphere and converted it into measurements of the total
and inelastic $pp$ cross sections $\sigma_{\rm tot}$ and $\sigma_{\rm inel}$ at
the super-LHC energy of 57 TeV. Their results reinforce our earlier conclusions
that the proton becomes a black disk at asymptotic energies, a prediction
reached on the basis of sub-LHC $\pbar p$ and $pp$ measurements of $\sigma_{\rm
tot}$ and $\rho$, the ratio of the real to the imaginary part of the forward
scattering amplitude [M. M. Block and F. Halzen, Phys. Rev. Lett. {\bf 107},
212002 (2011)]. The same black disk description of the proton anticipated the
values of $\sigma_{\rm tot}$ and $\sigma_{\rm inel}$ measured by the TOTEM
experiment at the LHC cms (center of mass) energy of $\sqrt s=7$ TeV, as well
as those of $\sigma_{\rm inel}$ measured by ALICE, ATLAS and CMS, as well as
the ALICE measurement at 2.76 TeV. All data are consistent with a proton that
is asymptotically a black disk of gluons: (i) both $\sigma_{\rm tot}$ and
$\sigma_{\rm inel}$ behave as $\ln^2s$, saturating the Froissart bound, (ii)
the forward scattering amplitude becomes pure imaginary (iii) the ratio
$\sigma_{\rm inel}/\sigma_{\rm tot}=0.509 \pm 0.021$, compatible with the black
disk value of 1/2, and (iv) proton interactions become flavor blind.


  In the present review, we describe three hot topics in cancer research such
as circulating tumor cells, exosomes, and 3D environment models. The first
section is dedicated to microfluidic platforms for detecting circulating tumor
cells, including both affinity based methods that take advantage of antibodies
and aptamers, and label free approaches, exploiting cancer cells physical
features and, more recently, abnormal cancer metabolism. In the second section,
we briefly describe the biology of exosomes and their role in cancer, as well
as conventional techniques for their isolation and innovative microfluidic
platforms. In the third section, the importance of tumor microenvironment is
highlighted, along with techniques for modeling it in vitro. Finally, we
discuss limitations of two dimensional monolayer methods and describe
advantages and disadvantages of different three dimensional tumor systems for
cell cell interaction analysis and their potential applications in cancer
management.


  Two-dimensional (2D) spectroscopy provides information about dissipative
processes subsequent to electronic excitation, which play a functional role in
energy harvesting materials and devices. This technique is particularly
sensitive to electronic and vibronic coherence dynamics. While the theoretical
treatment of relaxation in the context of 2D-spectroscopy is well-developed
under the assumption of different timescales of population transfer and
fluctuation dynamics, the interplay between both kinds of processes lacks a
comprehensive description in terms of line shape functions. To bridge this gap,
we use the cumulant expansion approach to derive response functions, which
account for fluctuation dynamics and population transfer simultaneously. We
compare 2D-spectra from calculations with different model assumptions about
correlations between fluctuations and point out under which conditions a
simplified treatment is justified. Our study shows that population transfer and
dissipative fluctuation dynamics cannot be described independent of each other
in general. Advantages and limitations of the proposed calculation method and
its compatibility with the modified Redfield description are discussed.


  Strategies to achieve higher upper-critical-field superconductors
({\mu}0Hc2(0)) are of great interest for both fundamental science and practical
applications. While reducing the thickness of two-dimensional (2D) materials to
a few layers significantly enhances {\mu}0Hc2(0) with accompanied potential
unconventional pairing mechanisms, further dimensional reduction to 1D
compounds rarely exceeds the expected Pauli limit. Here, we report the
discovery of a 1D granular Ta-Te nanowire that becomes superconducting under
high pressure, with a maximum critical temperature (Tc) of 5.1 K. Remarkably,
the {\mu}0Hc2(0) reaches 16 T, which is twice the Pauli limit, setting a record
of {\mu}0Hc2 (0) in all the reported 1D superconductors. Our work demonstrates
that the Ta-Te nanowire not only is a potential candidate for applications in
high magnetic fields, but also provides an ideal platform for further
investigations of the mechanisms between nanowires and large {\mu}0Hc2(0).


  We solve the local lifting problem for the alternating group A_4, thus
showing that it is a local Oort group. Specifically, if k is an algebraically
closed field of characteristic 2, we prove that every A_4-extension of k[[s]]
lifts to characteristic zero. As a consequence, every A_4-branched cover of
smooth projective curves in characteristic 2 lifts to characteristic zero.


  $^{133}\text{Ba}^+$ has been identified as an attractive ion for quantum
information processing due to the unique combination of its spin-1/2 nucleus
and visible wavelength electronic transitions. Using a microgram source of
radioactive material, we trap and laser-cool the synthetic $A$ = 133
radioisotope of barium II in a radio-frequency ion trap. Using the same, single
trapped atom, we measure the isotope shifts and hyperfine structure of the $6^2
\text{P}_{1/2}$ $\leftrightarrow$ $6^2 \text{S}_{1/2}$ and $6^2 \text{P}_{1/2}$
$\leftrightarrow$ $5^2 \text{D}_{3/2}$ electronic transitions that are needed
for laser cooling, state preparation, and state detection of the clock-state
hyperfine and optical qubits. We also report the $6^2 \text{P}_{1/2}$
$\leftrightarrow$ $5^2 \text{D}_{3/2}$ electronic transition isotope shift for
the rare $A$ = 130 and 132 barium nuclides, completing the spectroscopic
characterization necessary for laser cooling all long-lived barium II isotopes.


  We demonstrate full integration of vertical optical ring resonators with
silicon nanophotonic waveguides on silicon-on-insulator substrates to
accomplish a significant step towards 3D photonic integration. The on-chip
integration is realized by rolling up 2D differentially strained TiO2
nanomembranes into 3D microtube cavities on a nanophotonic microchip. The
integration configuration allows for out of plane optical coupling between the
in-plane nanowaveguides and the vertical microtube cavities as a compact and
mechanically stable optical unit, which could enable refined vertical light
transfer in 3D stacks of multiple photonic layers. In this vertical
transmission scheme, resonant filtering of optical signals at telecommunication
wavelengths is demonstrated based on subwavelength thick walled microcavities.
Moreover, an array of microtube cavities is prepared and each microtube cavity
is integrated with multiple waveguides which opens up interesting perspectives
towards parallel and multi-routing through a single cavity device as well as
high-throughput optofluidic sensing schemes.


  The Vega planetary system hosts the archetype of extrasolar Kuiper belts, and
is rich in dust from the sub-au region out to 100's of au, suggesting intense
dynamical activity. We present ALMA mm observations that detect and resolve the
outer dust belt from the star for the first time. The interferometric
visibilities show that the belt can be fit by a Gaussian model or by power-law
models with a steep inner edge (at 60-80 au). The belt is very broad, extending
out to at least 150-200 au. We strongly detect the star and set a stringent
upper limit to warm dust emission previously detected in the infrared. We
discuss three scenarios that could explain the architecture of Vega's planetary
system, including the new {ALMA} constraints: no outer planets, a chain of
low-mass planets, and a single giant planet. The planet-less scenario is only
feasible if the outer belt was born with the observed sharp inner edge. If
instead the inner edge is currently being truncated by a planet, then the
planet must be $\gtrsim$6 M$_{\oplus}$ and at $\lesssim71$ au to have cleared
its chaotic zone within the system age. In the planet chain scenario, outward
planet migration and inward scattering of planetesimals could produce the hot
and warm dust observed in the inner regions of the system. In the single giant
planet scenario, an asteroid belt could be responsible for the warm dust, and
mean motion resonances with the planet could put asteroids on star-grazing
orbits, producing the hot dust.


  Graph Convolutional Networks (GCNs) are powerful models for node
representation learning tasks. However, the node representation in existing GCN
models is usually generated by performing recursive neighborhood aggregation
across multiple graph convolutional layers with certain sampling methods, which
may lead to redundant feature mixing, needless information loss, and extensive
computations. Therefore, in this paper, we propose a novel architecture named
Non-Recursive Graph Convolutional Network (NRGCN) to improve both the training
efficiency and the learning performance of GCNs in the context of node
classification. Specifically, NRGCN proposes to represent different hops of
neighbors for each node based on inner-layer aggregation and layer-independent
sampling. In this way, each node can be directly represented by concatenating
the information extracted independently from each hop of its neighbors thereby
avoiding the recursive neighborhood expansion across layers. Moreover, the
layer-independent sampling and aggregation can be precomputed before the model
training, thus the training process can be accelerated considerably. Extensive
experiments on benchmark datasets verify that our NRGCN outperforms the
state-of-the-art GCN models, in terms of the node classification performance
and reliability.


  For a polynomial $u=u(x)$ in $\mathbb{Z}[x]$ and $r\in\mathbb{Z}$, we
consider the orbit of $u$ at $r$ denoted and defined by
$\mathcal{O}_u(r):=\{u(r),u(u(r)),\ldots\}$. We ask two questions here: (i)
what are the polynomials $u$ for which $0\in \mathcal{O}_u(r)$, and (ii) what
are the polynomials for which $0\not\in \mathcal{O}_u(r)$ but, modulo every
prime $p$, $0\in \mathcal{O}_u(r)$? In this paper, we give a complete
classification of the polynomials for which (ii) holds for a given $r$. We also
present some results for some special values of $r$ where (i) can be answered.


  [Purpose] To develop a fully automated semantic placenta segmentation model
that integrates the U-Net and SegNeXt architectures through ensemble learning.
[Methods] A total of 218 pregnant women with suspected placental anomalies who
underwent magnetic resonance imaging (MRI) were enrolled, yielding 1090
annotated images for developing a deep learning model for placental
segmentation. The images were standardized and divided into training and test
sets. The performance of PlaNet-S, which integrates U-Net and SegNeXt within an
ensemble framework, was assessed using Intersection over Union (IoU) and
counting connected components (CCC) against the U-Net model. [Results] PlaNet-S
had significantly higher IoU (0.73 +/- 0.13) than that of U-Net (0.78 +/-
0.010) (p<0.01). The CCC for PlaNet-S was significantly higher than that for
U-Net (p<0.01), matching the ground truth in 86.0\% and 56.7\% of the cases,
respectively. [Conclusion]PlaNet-S performed better than the traditional U-Net
in placental segmentation tasks. This model addresses the challenges of
time-consuming physician-assisted manual segmentation and offers the potential
for diverse applications in placental imaging analyses.


  Quizlet is the most popular online learning tool in the United States, and is
used by over 2/3 of high school students, and 1/2 of college students. With
more than 95% of Quizlet users reporting improved grades as a result, the
platform has become the de-facto tool used in millions of classrooms. In this
paper, we explore the task of recommending suitable content for a student to
study, given their prior interests, as well as what their peers are studying.
We propose a novel approach, i.e. Neural Educational Recommendation Engine
(NERE), to recommend educational content by leveraging student behaviors rather
than ratings. We have found that this approach better captures social factors
that are more aligned with learning. NERE is based on a recurrent neural
network that includes collaborative and content-based approaches for
recommendation, and takes into account any particular student's speed, mastery,
and experience to recommend the appropriate task. We train NERE by jointly
learning the user embeddings and content embeddings, and attempt to predict the
content embedding for the final timestamp. We also develop a confidence
estimator for our neural network, which is a crucial requirement for
productionizing this model. We apply NERE to Quizlet's proprietary dataset, and
present our results. We achieved an R^2 score of 0.81 in the content embedding
space, and a recall score of 54% on our 100 nearest neighbors. This vastly
exceeds the recall@100 score of 12% that a standard matrix-factorization
approach provides. We conclude with a discussion on how NERE will be deployed,
and position our work as one of the first educational recommender systems for
the K-12 space.


  Liver zonation is a fundamental characteristic of hepatocyte spatial
heterogeneity, which is challenging to recapitulate in traditional cell
cultures. This study presents a novel microfluidic device designed to induce
zonation in liver cell cultures by establishing an oxygen gradient using
standard laboratory gases. The device consists of two layers; a bottom layer
containing a gas channel network that delivers high and low oxygenated gases to
create three distinct zones within the cell culture chamber in the layer above.
Computational simulations and ratiometric oxygen sensing were employed to
validate the oxygen gradient, demonstrating that stable oxygen levels were
achieved within two hours. Liver zonation was confirmed using
immunofluorescence staining, which showed zonated albumin production in HepG2
cells directly correlating with oxygen levels and mimicking in-vivo zonation
behavior. This user-friendly device supports studies on liver zonation and
related metabolic disease mechanisms in vitro. It can also be utilized for
experiments that necessitate precise gas concentration gradients, such as
hypoxia-related research areas focused on angiogenesis and cancer development.


  Quantum computers can in principle solve certain problems exponentially more
quickly than their classical counterparts. We have not yet reached the advent
of useful quantum computation, but when we do, it will affect nearly all
scientific disciplines. In this review, we examine how current quantum
algorithms could revolutionize computational biology and bioinformatics. There
are potential benefits across the entire field, from the ability to process
vast amounts of information and run machine learning algorithms far more
efficiently, to algorithms for quantum simulation that are poised to improve
computational calculations in drug discovery, to quantum algorithms for
optimization that may advance fields from protein structure prediction to
network analysis. However, these exciting prospects are susceptible to "hype",
and it is also important to recognize the caveats and challenges in this new
technology. Our aim is to introduce the promise and limitations of emerging
quantum computing technologies in the areas of computational molecular biology
and bioinformatics.


  Source-free domain adaptation (SFDA) aims to transfer knowledge learned from
a source domain to an unlabeled target domain, where the source data is
unavailable during adaptation. Existing approaches for SFDA focus on
self-training usually including well-established entropy minimization
techniques. One of the main challenges in SFDA is to reduce accumulation of
errors caused by domain misalignment. A recent strategy successfully managed to
reduce error accumulation by pseudo-labeling the target samples based on
class-wise prototypes (centroids) generated by their clustering in the
representation space. However, this strategy also creates cases for which the
cross-entropy of a pseudo-label and the minimum entropy have a conflict in
their objectives. We call this conflict the centroid-hypothesis conflict. We
propose to reconcile this conflict by aligning the entropy minimization
objective with that of the pseudo labels' cross entropy. We demonstrate the
effectiveness of aligning the two loss objectives on three domain adaptation
datasets. In addition, we provide state-of-the-art results using up-to-date
architectures also showing the consistency of our method across these
architectures.


  Using reflection positivity techniques we prove the existence of minimizers
for a class of mesoscopic free-energies representing 1D systems with competing
interactions. All minimizers are either periodic, with zero average, or of
constant sign. If the local term in the free energy satisfies a convexity
condition, then all minimizers are either periodic or constant. Examples of
both phenomena are given. This extends our previous work where such results
were proved for the ground states of lattice systems with ferromagnetic nearest
neighbor interactions and dipolar type antiferromagnetic long range
interactions.


  The paper aims to apply the complex-sedenions to explore the field equations
of four fundamental interactions, which are relevant to the classical mechanics
and quantum mechanics, in the curved spaces. J. C. Maxwell was the first to
utilize the quaternions to describe the property of electromagnetic fields.
Nowadays the scholars introduce the complex-octonions to depict the
electromagnetic and gravitational fields. And the complex-sedenions can be
applied to study the field equations of the four interactions in the classical
mechanics and quantum mechanics. Further, it is able to extend the field
equations from the flat space into the curved space described with the
complex-sedenions, by means of the tangent-frames and tensors. The research
states that a few physical quantities will make a contribution to certain
spatial parameters of the curved spaces. These spatial parameters may exert an
influence on some operators (such as, divergence, gradient, and curl),
impacting the field equations in the curved spaces, especially the field
equations of the four quantum-fields in the quantum mechanics. Apparently the
paper and General Relativity both confirm and succeed to the Cartesian academic
thought of `the space is the extension of substance'.


  Electronic Healthcare Records contain large volumes of unstructured data,
including extensive free text. Yet this source of detailed information often
remains under-used because of a lack of methodologies to extract interpretable
content in a timely manner. Here we apply network-theoretical tools to analyse
free text in Hospital Patient Incident reports from the National Health
Service, to find clusters of documents with similar content in an unsupervised
manner at different levels of resolution. We combine deep neural network
paragraph vector text-embedding with multiscale Markov Stability community
detection applied to a sparsified similarity graph of document vectors, and
showcase the approach on incident reports from Imperial College Healthcare NHS
Trust, London. The multiscale community structure reveals different levels of
meaning in the topics of the dataset, as shown by descriptive terms extracted
from the clusters of records. We also compare a posteriori against hand-coded
categories assigned by healthcare personnel, and show that our approach
outperforms LDA-based models. Our content clusters exhibit good correspondence
with two levels of hand-coded categories, yet they also provide further medical
detail in certain areas and reveal complementary descriptors of incidents
beyond the external classification taxonomy.


  We prove the existence and stability of flat steady states of the
Vlasov-Poisson system, which in astrophysics are used as models of disk-like
galaxies. We follow the variational approach developed by Guo and Rein for this
type of problems and extend previous results of Rein. In particular, we employ
a reduction procedure which relates the stability problem for the
Vlasov-Poisson system to the analogous question for the Euler-Poisson system.


  The crystalline solids with lack of orientational ordering serve the purpose
of studying the disordered systems with many fundamental applications in
contemporary research. Despite the orientational disorder, the constituent
particles sometime follow some conserved laws or correlation while maintaining
the translational order depicted by the crystal structure. Such phase is called
``correlated orientational disordered'' phase in the crystal. Polyhedral
particles in the presence of hard-core interaction provide a great opportunity
to study the orientational order and disorder in entropy driven self-assembly.
We report the computational evidence of the role of symmetry of the polyhedral
particles and cubic crystalline structures exhibiting the correlated disordered
phases, which are obtained from the simulations of single-component systems.
The point groups of the particle and crystal structure appear to be directly
connected with the existence of multiple unique orientations satisfying a few
other orientational features. In this phase, the systems exhibit
orientationally frozen states at sufficiently higher packing fractions and
discrete orientational hopping at comparatively lower ones while all the
signatures of the correlation are preserved. This symmetry relationship appears
to control all the aspects of orientational correlation in the crystalline
solids which might be useful to draw fundamental insights about the disordered
phases with orientational correlation as well as designing the disorder in the
crystals.


  Realization of the stationary integral solutions of steady state transonic
accretion flow in spherical symmetry helps to understand accretion phenomena on
various astrophysical objects. In recent years, attempts have been made to
study accreting black hole systems as an example of autonomous dynamical
systems. The fixed point analysis is used to study the transonic properties of
accretion flow onto an astrophysical black hole, hence the nature of the phase
orbits for the transonic flow solutions can be understood without constructing
the integral solutions. Since a large-scale astrophysical fluid flow is
vulnerable to external perturbation, one needs to ensure that the stationary
accretion solutions are stable under perturbation. By adopting a time-dependent
stability analysis scheme for the accretion flow, one demonstrates under which
condition the perturbation will not diverge. It has also been observed that a
space-time metric, dubbed the sonic metric, can be constructed to describe the
propagation of the perturbation embedded within the accreting fluid, which
mimics a black hole like spacetime within the accreting fluid, where the
transonic surfaces can be identified with a black hole like horizons. Such
identification is accomplished using the theory of causal structure - by
constructing Carter-Penrose diagrams. An accreting black hole system, thus, can
be perceived as a classical analogue gravity model naturally found in the
universe. Hence, accretion phenomena onto astrophysical black holes can be
looked upon from three apparently non-overlapping perspectives - astrophysical
processes, theory of dynamical systems, and emergent gravity (alternatively,
the analogue gravity) phenomena, respectively. The present article illustrates,
by taking the simplest possible accretion flow model, how one can study
astrophysical accretion processes from the aforementioned perspectives
(Abridged).


  Interface strain can significantly influence the mechanical, electronic and
magnetic properties of low-dimensional materials. Here we investigated by
scanning tunneling microscopy how the stress introduced by a mismatched
interface affects the structure of a growing graphene (Gr) layer on a Ni(100)
surface in real time during the process. Strain release appears to be the main
factor governing morphology, with the interplay of two simultaneous driving
forces: on the one side the need to obtain two-dimensional best registry with
the substrate, via formation of moir\'e patterns, on the other side the
requirement of optimal one-dimensional in-plane matching with the transforming
nickel carbide layer, achieved by local rotation of the growing Gr flake. Our
work suggests the possibility of tuning the local properties of two-dimensional
films at the nanoscale through exploitation of strain at a one-dimensional
interface.


  A subset $C$ of the vertex set of a graph $\Gamma$ is called a perfect code
in $\Gamma$ if every vertex of $\Gamma$ is at distance no more than $1$ to
exactly one vertex of $C$. A subset $C$ of a group $G$ is called a perfect code
of $G$ if $C$ is a perfect code in some Cayley graph of $G$. In this paper we
give sufficient and necessary conditions for a subgroup $H$ of a finite group
$G$ to be a perfect code of $G$. Based on this, we determine the finite groups
that have no nontrivial subgroup as a perfect code, which answers a question by
Ma, Walls, Wang and Zhou.


  A detailed study of inclusive deep inelastic scattering from mirror A = 3
nuclei at large values of Bjorken-x is presented. The main purpose is to
estimate the theoretical uncertainties on the extraction of F2n from such
measurements. Within the convolution approach we confirm the cancellation of
nuclear effects at the level of ~1 % for x < 0.75 in overall agreement with
previous findings. However, within models in which modifications of the bound
nucleon structure functions are accounted for to describe the EMC effect in
nuclei, we find that the nuclear effects may be canceled at a level of ~ 3 %
only, leading to an accuracy of ~ 12 % in the extraction of F2n / F2p at x ~
0.7 - 0.8. Another consequence of bound nucleon modifications is that the
iteration procedure does not improve the accuracy of the extraction of F2n /
F2p.