  The extreme values theory presents specific tools for modeling and predicting
extreme phenomena. In particular, risk assessment is often analyzed through
measures for tail dependence and high values clustering. Despite technological
advances allowing an increasingly larger and more efficient data collection,
there are sometimes failures in the records, which causes difficulties in
statistical inference, especially in the tail where data are scarcer. In this
article we present a model with a simple and intuitive failures scheme, where
each record failure is replaced by the last record available. We will study its
extremal behavior with regard to local dependence and high values clustering,
as well as the temporal dependence on the tail.


  Motivated by old and new applications, we investigate Datalog as a language
for sequence databases. We reconsider classical features of Datalog programs,
such as negation, recursion, intermediate predicates, and relations of higher
arities. We also consider new features that are useful for sequences, notably,
equations between path expressions, and "packing". Our goal is to clarify the
relative expressiveness of all these different features, in the context of
sequences. Towards our goal, we establish a number of redundancy and
primitivity results, showing that certain features can, or cannot, be expressed
in terms of other features. These results paint a complete picture of the
expressiveness relationships among all possible Sequence Datalog fragments that
can be formed using the six features that we consider.


  Linear time series modelling is dominated by the use of purely autoregressive
models even though incorporating moving average components can greatly improve
parsimony. We present a convex formulation for vector-ARMA system
identification which respects this fundamental property, thus granting access
to the nice properties afforded by convex programming. The identification
procedure is done purely in the time domain which can accommodate
non-stationarity through regime switching. As a proof of concept, we present
experimental results demonstrating this convex program in action. Next, we show
how to adapt the expectation-maximization algorithm to support regime switching
behavior.


  Nowadays social media (Twitter, Facebook, etc.), not only simply as
communication media, but also for promotion. Social networking media offers
many business benefits for companies and organizations. Research purposes is to
determine the model of social network media utilization as a promotional media
for handicraft business in Palembang city. Qualitative and quantitative
research design are used to know how handicraft business in Palembang city
utilizing social media networking as a promotional media. The research results
show 35% craft businesses already utilizing social media as a promotional
media. The social media used are blog development 15%, facebook 46%, and
twitter etc. are 39%. The reasons they use social media such as, 1) minimal
cost, 2) easily recognizable, 3) global distribution areas. Social media
emphasis on direct engagement with customers better. So that the marketing
method could be more personal through direct communication with customers.


  Once chosen the dynamics in one frame, the rest frame in this paper, the
Bakamjian and Thomas method allows to define relativistic quark models in any
frame. These models have been shown to provide, in the infinite quark mass
limit, fully covariant current form factors as matrix elements of the quark
current operator. In this paper we use the rest frame dynamics fitted from the
meson spectrum by various authors, already shown to provide a reasonable value
for $\rho^2$. From the general formulae for the scaling invariant form factors
$\xi^{(n)}(w)$, $\tau_{1/2}^{(n)}(w)$ and $\tau_{3/2}^{(n)}(w)$, we predict
quantitavely the $B$ semileptonic branching ratios to the ground state and
orbitally excited charmed mesons $D, D^\ast$ and $D^{\ast\ast}$. We check
Bjorken's sum rule and discuss the respective contributions to it. We find
$\xi(w)\simeq (2/(1+w)) ^2$, resulting from the fact that the ground state wave
function is Coulomb-like. We also find $\tau_{3/2}\simeq 0.5 (2/(1+w))^3$ and
$\tau_{1/2}(w)\ll \tau_{3/2}(w)$. Very small branching ratios into $j=1/2$
orbitally excited $D$'s results. The overall agreement with experiment is
rather good within the present accuracy which is poor for the orbitally excited
charmed mesons. We predict a ratio $Br(B\to D^\ast_2 l \nu)/Br(B\to D_1 l
\nu)=1.55\pm 0.15$ as a mere consequence of the heavy quark symmetry. If some
faint experimental indications that $Br(B\to D_1 l \nu)\simeq Br(B\to D^\ast_2
l \nu)$ were confirmed, it would indicate a sizeable $O(1/m_c)$ correction.


  The bottomonium spectrum up to $n = 3$ is studied within Non-Relativistic
Quantum Chromodynamics up to N$^3$LO. We consider finite charm quark mass
effects both in the QCD potential and the $\overline{\mathrm{MS}}$-pole mass
relation up to third order in the $\Upsilon$-scheme counting. The $u = 1/2$
renormalon of the static potential is canceled by expressing the bottom quark
pole mass in terms of the MSR mass. A careful investigation of scale variation
reveals that, while $n = 1, 2$ states are well behaved within perturbation
theory, $n = 3$ bound states are no longer reliable. We carry out our analysis
in the $n_\ell = 3$ and $n_\ell = 4$ schemes and conclude that, as long as
finite $m_c$ effects are smoothly incorporated in the MSR mass definition, the
difference between the two schemes is rather small. Performing a fit to
$b\bar{b}$ bound states we find $\overline{m}_b(\overline{m}_b) = 4.216\pm
0.039$ GeV. We extend our analysis to the lowest lying charmonium states
finding $\overline{m}_c(\overline{m}_c)=1.273 \pm 0.054$ GeV. Finally, we
perform simultaneous fits for $\overline{m}_b$ and $\alpha_s$ finding
$\alpha_s^{(n_f=5)}(m_Z)=0.1178\pm 0.0051$. Additionally, using a modified
version of the MSR mass with lighter massive quarks we are able to predict the
uncalculated $\mathcal{O}(\alpha_s^4)$ virtual massive quark corrections to the
relation between the $\overline{\mathrm{MS}}$ and pole masses.


  From the realization of $q-$oscillator algebra in terms of generalized
derivative, we compute the matrix elements from deformed exponential functions
and deduce generating functions associated with Rogers-Szeg\H{o} polynomials as
well as their relevant properties. We also compute the matrix elements
associated to the $(p,q)-$oscillator algebra (a generalization of the $q-$one)
and perform the Fourier-Gauss transform of a generalization of the deformed
exponential functions.


  Only a handful of quasars have been identified as kinetically dominated,
their long term time averaged jet power, $\overline{Q}$, exceeds the bolometric
thermal emission, $L_{bol}$, associated with the accretion flow. This letter
presents the first extreme ultraviolet (EUV) spectrum of a kinetically
dominated quasar, 3C 270.1. The EUV continuum flux density of 3C 270.1 is very
steep, $F_{\nu} \sim \nu^{-\alpha_{EUV}}$, $\alpha_{EUV} =2.98\pm 0.15$. This
value is consistent with the correlation of $\overline{Q}/L_{bol}$ and
$\alpha_{EUV}$ found in previous studies of the EUV continuum of quasars, the
EUV deficit of radio loud quasars. Curiously, although ultraviolet broad
absorption line (BAL) troughs in quasar spectra are anti-correlated with
$\overline{Q}$, 3C 270.1 has been considered a BAL quasar based on an SDSS
spectrum. This claim is examined in terms of the EUV spectrum of OVI 1and the
highest resolution CIV spectrum in the archival data and the SDSS spectrum.
First, from [OIII]4959,5007 (IR) observations and the UV spectral lines, it is
concluded that the correct redshift for 3C 270.1 is 1.5266. It is then found
that the standard measure of broad absorption, BALnicity = 0, for MgII 2800,
CIV 1549 and OVI 1032 in all epochs.


  We study the existence of a solution to the mixed boundary value problem for
Helmholtz and Poisson type equations in a bounded Lipschitz domain
$\Omega\subset\mathbb{R}^N$ and in $\mathbb{R}^N\setminus\Omega$ for $N\geq3$.
The boundary $\partial\Omega$ of $\Omega$ is the decomposition of
$\Gamma_1,\Gamma_2\subset\partial\Omega$ such that
$\partial\Omega=\Gamma=\overline{\Gamma}_1\cup\Gamma_2=\Gamma_1\cup\overline{\Gamma}_2$
and $\Gamma_1\cap\Gamma_2=\emptyset$. We have shown that if the Neumann data
$f_2\in H^{-\frac{1}{2}}(\Gamma_2)$ and the Dirichlet data $f_1\in
H^{\frac{1}{2}}(\Gamma_1)$ then the Helmholtz problem with mixed boundary data
admits a unique solution. We have also shown the existence of a weak solution
to a mixed boundary value problem governed by the Poisson equation with a
measure data and the Dirichlet, Neumann data belongs to $f_1\in
H^{\frac{1}{2}}(\Gamma_1)$, $f_2\in H^{-\frac{1}{2}}(\Gamma_2)$ respectively.


  This demo showcases a simple tool that utilizes AIGC technology, enabling
both professional designers and regular users to easily customize clothing for
their digital avatars. Customization options include changing clothing colors,
textures, logos, and patterns. Compared with traditional 3D modeling processes,
our approach significantly enhances efficiency and interactivity and reduces
production costs.


  We study the unknown coupling constants that appear at order $p^4$ in the
Chiral Perturbation Theory analysis of $K \to \pi \gamma^* \to \pi l^+ l^-$,
$K^{+-} \to \pi^{+-} \gamma \gamma$ and $K \to \pi \pi \gamma$ decays. To that
end, we compute the chiral realization of the $\Delta S \, = \, 1$ Hamiltonian
in the framework of the $1/N_c$-expansion of the low-energy action. The
phenomenological implications are also discussed.


  We report the analysis of HST WFPC2 F606W images of 40 spirals belonging to
the sample introduced in Carollo et al. (paper I), where 35 other targets were
discussed. We describe the optical morphology of the new 40 galaxies, derive
the surface brightness profiles for 25 of them, and present the results of
photometric decompositions of these profiles into a ``bulge'' (R^1/4 or
exponential) and a disk component. The analysis of the sample of 75 galaxies
puts on a statistically more solid ground the main results presented in paper
I. Furthermore, the analysis of the sample of 75 objects shows that: A. Several
of the non-classical inner structures are well fitted by an exponential
profile. These ``exponential bulges'' are fainter than R^1/4 bulges for given
total galaxy luminosity and (catalog) Hubble type later than Sab. B.
Irregular/exponential bulges typically host central compact sources. C. The
central sources are present in all types of disk galaxies, starting with
systems as early as S0a. About 60 % of Sb to Sc galaxies host a central compact
source. Many of the galaxies which host compact sources contain a barred
structure. D. Galaxies with apparent nuclear star formation and the brightest
compact sources, are preferentially the early- and intermediate- type (S0a-Sb)
systems. E. None of the features depends on environment: isolated and not
isolated galaxies show indistinguishable properties. Independently from the
physical nature of the non-classical inner structures, our main conclusion is
that a significant fraction of galaxies classified from the ground as
relatively early-type shows a rich variety of central properties, and little or
no morphological/photometric evidence for a smooth, R^1/4-law bulge.


  Binary matrix and ternary matrix are two types of popular sensing matrices in
compressed sensing for their competitive performance and low computation.
However, to the best of our knowledge, there seems no literature aiming at
evaluating their performances if they hold the same sparisty, though it is of
practical importance. Based on both RIP analysis and numerical simulations,
this paper, for the first time, discloses that {0, 1} binary matrix holds
better overall performance over {0, +1, -1} ternary matrix, if they share the
same distribution on nonzero positions.


  All mobile devices are energy-constrained. They use batteries that allows
using the device for a limited amount of time. In general, energy attacks on
mobile devices are denial of service (DoS) type of attacks. While previous
studies have analyzed the energy attacks in servers, no existing work has
analyzed the energy attacks on mobile devices. As such, in this paper, we
present the first systematic study on how to exploit the energy attacks on
smartphones. In particular, we explore energy attacks from the following
aspect: hardware components, software resources, and network communications
through the design and implementation of concrete malicious apps, and malicious
web pages. We quantitatively show how quickly we can drain the battery through
each individual attack, as well as their combinations. Finally, we believe
energy exploit will be a practical attack vector and mobile users should be
aware of this type of attacks.


  Material susceptibilities govern interactions between electromagnetic waves
and matter and are of a crucial importance for basic understanding of natural
phenomena and for tailoring practical applications. Here we present a new
calibration-free method for relative complex permittivity retrieval, which
allows using accessible and cheap apparatus and simplifies the measurement
process. The method combines advantages of resonant and non-resonant
techniques, allowing to extract parameters of liquids and solids in a broad
frequency range, where material's loss tangent is less than 0.5. The essence of
the method is based on exciting magnetic dipole resonance in a spherical sample
with variable dimensions. Size-dependent resonant frequencies and quality
factors of magnetic dipolar modes are mapped on real and imaginary parts of
permittivity by employing Mie theory. Samples are comprised of liquid
solutions, enclosed in stretchable covers, which allows changing the dimensions
continuously. This approach allows tuning magnetic dipolar resonance over a
wide frequency range, effectively making resonance retrieval method broadband.
The technique can be extended to powder and solid materials, depending on their
physical parameters, such as granularity and processability.


  We present predictions for the production cross section of t-quark pair
production in association with a Z boson at the next-to-leading order (NLO)
accuracy using matrix elements obtained from the HELAC-Oneloop package. We use
the subtraction method for computing the radiative corrections as implemented
in the POWHEG-Box, which was also used in several other computations of similar
complexity.


  In many areas, practitioners need to analyze large datasets that challenge
conventional single-machine computing. To scale up data analysis, distributed
and parallel computing approaches are increasingly needed.
  Here we study a fundamental and highly important problem in this area: How to
do ridge regression in a distributed computing environment? Ridge regression is
an extremely popular method for supervised learning, and has several optimality
properties, thus it is important to study. We study one-shot methods that
construct weighted combinations of ridge regression estimators computed on each
machine. By analyzing the mean squared error in a high dimensional
random-effects model where each predictor has a small effect, we discover
several new phenomena.
  1. Infinite-worker limit: The distributed estimator works well for very large
numbers of machines, a phenomenon we call "infinite-worker limit".
  2. Optimal weights: The optimal weights for combining local estimators sum to
more than unity, due to the downward bias of ridge. Thus, all averaging methods
are suboptimal.
  We also propose a new Weighted ONe-shot DistributEd Ridge regression (WONDER)
algorithm. We test WONDER in simulation studies and using the Million Song
Dataset as an example. There it can save at least 100x in computation time,
while nearly preserving test accuracy.


  In this paper, we present a Model-Based Reinforcement Learning (MBRL)
algorithm named \emph{Monte Carlo Probabilistic Inference for Learning COntrol}
(MC-PILCO). The algorithm relies on Gaussian Processes (GPs) to model the
system dynamics and on a Monte Carlo approach to estimate the policy gradient.
This defines a framework in which we ablate the choice of the following
components: (i) the selection of the cost function, (ii) the optimization of
policies using dropout, (iii) an improved data efficiency through the use of
structured kernels in the GP models. The combination of the aforementioned
aspects affects dramatically the performance of MC-PILCO. Numerical comparisons
in a simulated cart-pole environment show that MC-PILCO exhibits better data
efficiency and control performance w.r.t. state-of-the-art GP-based MBRL
algorithms. Finally, we apply MC-PILCO to real systems, considering in
particular systems with partially measurable states. We discuss the importance
of modeling both the measurement system and the state estimators during policy
optimization. The effectiveness of the proposed solutions has been tested in
simulation and on two real systems, a Furuta pendulum and a ball-and-plate rig.


  We investigate some modal operators of necessity and possibility in the
context of meet-complemented (not necessarily distributive) lattices. We
proceed in stages. We compare our operators with others.


  Nowadays, Breast cancer has risen to become one of the most prominent causes
of death in recent years. Among all malignancies, this is the most frequent and
the major cause of death for women globally. Manually diagnosing this disease
requires a good amount of time and expertise. Breast cancer detection is
time-consuming, and the spread of the disease can be reduced by developing
machine-based breast cancer predictions. In Machine learning, the system can
learn from prior instances and find hard-to-detect patterns from noisy or
complicated data sets using various statistical, probabilistic, and
optimization approaches. This work compares several machine learning
algorithm's classification accuracy, precision, sensitivity, and specificity on
a newly collected dataset. In this work Decision tree, Random Forest, Logistic
Regression, Naive Bayes, and XGBoost, these five machine learning approaches
have been implemented to get the best performance on our dataset. This study
focuses on finding the best algorithm that can forecast breast cancer with
maximum accuracy in terms of its classes. This work evaluated the quality of
each algorithm's data classification in terms of efficiency and effectiveness.
And also compared with other published work on this domain. After implementing
the model, this study achieved the best model accuracy, 94% on Random Forest
and XGBoost.


  The photoacoustic signal in a closed T-cell resonator is generated and
measured using laser based photoacoustic spectroscopy. The signal is modelled
using the amplitude mode expansion method, which is based on eigenmode
expansion and introduction of losses in form of loss factors. The measurement
reproduced almost all the calculated resonances from the numerical models with
fairly good agreement. The cause of the differences between the measured and
the simulated resonances are explained. In addition, the amplitude mode
expansion simulation model is established as a quicker and computationally less
demanding photoacoustic simulation alternative to the viscothermal model. The
resonance frequencies obtained from the two models deviate by less than 1.8%.
It was noted that the relative height of the amplitudes of the two models
depended on the location of the antinodes within the resonator.


  We apply the QCD factorization approach to exclusive, radiative B meson
decays in the region of small invariant photon mass. We calculate factorizable
and non-factorizable corrections to leading order in the heavy quark mass
expansion and next-to-leading order in the strong coupling constant.
Phenomenological consequences for the B -> K* gamma decay rate and the B -> K*
ell+ ell- forward-backward asymmetry are discussed.


  We present a theory of the phononic thermal (Kapitza) resistance at the
interface between graphene or another single-layer two-dimensional (2D) crystal
(e.g. MoS$_{2}$) and a flat substrate, based on a modified version of the
cross-plane heat transfer model by Persson, Volokitin and Ueba [J. Phys.:
Condens. Matter 23, 045009 (2011)]. We show how intrinsic flexural phonon
damping is necessary for obtaining a finite Kapitza resistance and also
generalize the theory to encased single-layer 2D crystals with a superstrate.
We illustrate our model by computing the thermal boundary conductance (TBC) for
bare and SiO$_{2}$-encased single-layer graphene and MoS$_{2}$ on a SiO$_{2}$
substrate, using input parameters from first-principles calculation. The
estimated room temperature TBC for bare (encased) graphene and MoS$_{2}$ on
SiO$_{2}$ are 34.6 (105) and 3.10 (5.07) MWK$^{-1}$m$^{-2}$, respectively. The
theory predicts the existence of a phonon frequency crossover point, below
which the low-frequency flexural phonons in the bare 2D crystal do not
dissipate energy efficiently to the substrate. We explain within the framework
of our theory how the encasement of graphene with a top SiO$_{2}$ layer
introduces new low-frequency transmission channels which significantly reduce
the graphene-substrate Kapitza resistance. We emphasize that the distinction
between bare and encased 2D crystals must be made in the analysis of
cross-plane heat dissipation to the substrate.


  Two positive scalar curvature metrics $g_0$, $g_1$ on a manifold $M$ are
psc-isotopic if they are homotopic through metrics of positive scalar
curvature. It is well known that if two metrics $g_0$, $g_1$ of positive scalar
curvature on a closed compact manifold $M$ are psc-isotopic, then they are
psc-concordant: i.e., there exists a metric $\bar{g}$ of positive scalar
curvature on the cylinder $M\times I$ which extends the metrics $g_0$ on
$M\times {0}$ and $g_1$ on $M\times {1}$ and is a product metric near the
boundary. The main result of the paper is that if psc-metrics $g_0$, $g_1$ on
$M$ are psc-concordant, then there exists a diffeomorphism $\Phi : M\times I
\to M\times I$ with $\Phi|_{M\times {0}}=Id$ (a pseudo-isotopy) such that the
metrics $g_0$ and $(\Phi|_{M\times {1}})^*g_1$ are psc-isotopic. In particular,
for a simply connected manifold $M$ with $\dim M\geq 5$, psc-metrics $g_0$,
$g_1$ are psc-isotopic if and only if they are psc-concordant. To prove these
results, we employ a combination of relevant methods: surgery tools related to
Gromov-Lawson construction, classic results on isotopy and pseudo-isotopy of
diffeomorphisms, standard geometric analysis related to the conformal
Laplacian, and the Ricci flow.


  Finding cohesive subgraphs in a network is a well-known problem in graph
theory. Several alternative formulations of cohesive subgraph have been
proposed, a notable example being $s$-club, which is a subgraph where each
vertex is at distance at most $s$ to the others. Here we consider the problem
of covering a given graph with the minimum number of $s$-clubs. We study the
computational and approximation complexity of this problem, when $s$ is equal
to 2 or 3. First, we show that deciding if there exists a cover of a graph with
three $2$-clubs is NP-complete, and that deciding if there exists a cover of a
graph with two $3$-clubs is NP-complete. Then, we consider the approximation
complexity of covering a graph with the minimum number of $2$-clubs and
$3$-clubs. We show that, given a graph $G=(V,E)$ to be covered, covering $G$
with the minimum number of $2$-clubs is not approximable within factor
$O(|V|^{1/2 -\varepsilon})$, for any $\varepsilon>0$, and covering $G$ with the
minimum number of $3$-clubs is not approximable within factor $O(|V|^{1
-\varepsilon})$, for any $\varepsilon>0$. On the positive side, we give an
approximation algorithm of factor $2|V|^{1/2}\log^{3/2} |V|$ for covering a
graph with the minimum number of $2$-clubs.


  We consider the moment map $m:\mathbb{P}V_n\rightarrow
\text{i}\mathfrak{u}(n)$ for the action of $\text{GL}(n)$ on
$V_n=\otimes^{2}(\mathbb{C}^{n})^{*}\otimes\mathbb{C}^{n}$, and study the
functional $F_n=\|m\|^{2}$ restricted to the projectivizations of the algebraic
varieties of all $n$-dimensional Leibniz algebras $L_n$ and all $n$-dimensional
symmetric Leibniz algebras $S_n$, respectively. Firstly, we give a description
of the maxima and minima of the functional $F_n: L_n \rightarrow \mathbb{R}$,
proving that they are actually attained at the symmetric Leibniz algebras.
Then, for an arbitrary critical point $[\mu]$ of $F_n: S_n \rightarrow
\mathbb{R}$, we characterize the structure of $[\mu]$ by virtue of the
nonnegative rationality. Finally, we classify the critical points of $F_n: S_n
\rightarrow \mathbb{R}$ for $n=2$, $3$, respectively.


  We prove that an outer action of a locally compact group $G$ on a full factor
$M$ is automatically strictly outer, meaning that the relative commutant of $M$
in the crossed product is trivial. If moreover the image of $G$ in the outer
automorphism group $\operatorname{Out} M$ is closed, we prove that the crossed
product remains full. We obtain this result by proving that the inclusion of
$M$ in the crossed product automatically has a spectral gap property. Such
results had only been proven for actions of discrete groups and for actions of
compact groups, by using quite different methods in both cases. Even for the
canonical Bogoljubov actions on free group factors or free Araki-Woods factors,
these results are new.


  The Transiting Exoplanet Survey Satellite (\textit{TESS}) mission was
designed to perform an all-sky search of planets around bright and nearby
stars. Here we report the discovery of two sub-Neptunes orbiting around the TOI
1062 (TIC 299799658), a V=10.25 G9V star observed in the TESS Sectors 1, 13, 27
& 28. We use precise radial velocity observations from HARPS to confirm and
characterize these two planets. TOI 1062b has a radius of
2.265^{+0.095}_{-0.091} Re, a mass of 11.8 +\- 1.4 Me, and an orbital period of
4.115050 +/- 0.000007 days. The second planet is not transiting, has a minimum
mass of 7.4 +/- 1.6 Me and is near the 2:1 mean motion resonance with the
innermost planet with an orbital period of 8.13^{+0.02}_{-0.01} days. We
performed a dynamical analysis to explore the proximity of the system to this
resonance, and to attempt at further constraining the orbital parameters. The
transiting planet has a mean density of 5.58^{+1.00}_{-0.89} g cm^-3 and an
analysis of its internal structure reveals that it is expected to have a small
volatile envelope accounting for 0.35% of the mass at maximum. The star's
brightness and the proximity of the inner planet to the "radius gap" make it an
interesting candidate for transmission spectroscopy, which could further
constrain the composition and internal structure of TOI 1062b.


  We investigate the parameters of global solar p-mode oscillations, namely
damping width $\Gamma$, amplitude $A$, mean squared velocity $\langle
v^2\rangle$, energy $E$, and energy supply rate $\mathrm{d}E/\mathrm{d} t$,
derived from two solar cycles' worth (1996 - 2018) of Global Oscillation
Network Group (GONG) time series for harmonic degrees $l=0 - 150$. We correct
for the effect of fill factor, apparent solar radius, and spurious jumps in the
mode amplitudes. We find that the amplitude of the activity related changes of
$\Gamma$ and $A$ depends on both frequency and harmonic degree of the modes,
with the largest variations of $\Gamma$ for modes with $2400\,\mu\text{Hz}\le
\nu \le 3300\,\mu\text{Hz}$ and $31\le l \le 60$ with a min-to-max variation of
$26.6\pm0.3\%$ and of $A$ for modes with $2400\,\mu\text{Hz}\le\nu\le
3300\,\mu\text{Hz}$ and $61\le l \le 100$ with a min-to-max variation of
$27.4\pm0.4\%$. The level of correlation between the solar radio flux
$F_{10.7}$ and mode parameters also depends on mode frequency and harmonic
degree. As a function of mode frequency, the mode amplitudes are found to
follow an asymmetric Voigt profile with
$\nu_{\text{max}}=3073.59\pm0.18\,\mu\text{Hz}$. From the mode parameters, we
calculate physical mode quantities and average them over specific mode
frequency ranges. This way, we find that the mean squared velocities $\langle
v^2\rangle$ and energies $E$ of p modes are anti-correlated with the level of
activity, varying by $14.7\pm0.3\%$ and $18.4\pm0.3\%$, respectively, and that
the mode energy supply rates show no significant correlation with activity.
With this study we expand previously published results on the temporal
variation of solar p-mode parameters. Our results will be helpful to future
studies of the excitation and damping of p modes, i.e., the interplay between
convection, magnetic field, and resonant acoustic oscillations.


  Theoretical treatments of non-equilibrium dynamics in strongly interacting
Bose-Fermi mixtures are complicated by the inherent non-Gaussian nature of the
vacuum two-body physics, invalidating the typical Hartree-Fock-Bogoliubov
approximation. Here, we apply the cumulant expansion to study non-equilibrium
Bose-Fermi mixtures, which allows us to explicitly include the missing
non-Gaussian quantum correlations, leading to a consistent dynamical theory of
a Bose-Fermi mixture near an interspecies Feshbach resonance. We first apply
our theory to a study of atom-pair coherence in the gas, which is significantly
enhanced by the competing influences of the Fermi sea and Bose-Einstein
condensation, in agreement with analytical calculations. Then, we study the
depletion of a degenerate Bose-Fermi mixture following a quench to the unitary
regime, characterizing the resulting depletion of the Bose-Einstein condensate,
the deformation of the Fermi surface, and the production of molecules. We find
that at early times, the population dynamics scale quadratically with the hold
time, and define an associated characteristic timescale set by the parameters
of the mixture and the width of the Feshbach resonance.


  Due to the low resolution of slitless spectroscopy, future surveys including
those made possible by the Roman and Euclid space telescopes will be prone to
line mis-identification, leading to interloper galaxies at the wrong redshifts
in the large-scale structure catalogues. The most pernicious of these have a
small displacement between true and false redshift such that the interloper
positions are correlated with the target galaxies. We consider how to correct
for such contaminants, focusing on $\rm H\beta$ interlopers in [OIII]
catalogues as will be observed by Roman, which are misplaced by $\Delta d = 97
\,h^{-1}\,{\rm Mpc}$ at redshift $z = 1$. Because this displacement is close to
the BAO scale, the peak in the interloper-target galaxy cross-correlation
function at the displacement scale can change the shape of the BAO peak in the
auto-correlation of the contaminated catalogue, and lead to incorrect
cosmological measurements if not accounted for properly. We consider how to
build a model for the monopole and quadrupole moments of the contaminated
correlation function, including an additional free parameter for the fraction
of interlopers. The key input to this model is the cross-correlation between
the population of galaxies forming the interlopers and the main target sample.
It will be important to either estimate this using calibration data or to use
the contaminated small-scale auto-correlation function to model it, which may
be possible if a number of requirements about the galaxy populations are met.
We find that this method is successful in measuring the BAO dilation parameters
without significant degradation in accuracy, provided the cross-correlation
function is accurately known.


  A Bose--Einstein condensate of exciton polaritons coexisting with a Fermi gas
of electrons has been recently proposed as a promising system for realisation
of room-temperature superconductivity [Phys. Rev. Lett., 104, 106402 (2010)].
In order to find the optimum conditions for exciton and exciton-polariton
mediated superconductivity, we study the attractive mechanism between electrons
of a Cooper pair mediated by the exciton and exciton-polariton condensate and
analyze the gap equation that follows. We specifically address microcavities
with embedded n-doped quantum wells as well as coupled quantum wells hosting a
condensate of spatially indirect excitons, put in contact with a
two-dimensional electron gas. We show that engineering of the interaction in
these peculiar Bose-Fermi mixtures is complex and sometimes counterintuitive,
but leaves much freedom for optimization, making promising the realization of
high-temperature superconductivity in multilayer semiconductor structures.


  This paper establishes a strict mathematical relationship between an
arbitrary continuous function on a compact set and its global minima, like the
well-known first order optimality condition for convex and differentiable
functions. By introducing a class of nascent minima distribution functions that
is only related to the target function and the given compact set, we construct
a sequence that monotonically converges to the global minima on that given
compact set. Then, we further consider some various sequences of sets where
each sequence monotonically shrinks from the original compact set to the set of
all global minimizers, and the shrink rate can be determined for continuously
differentiable functions. Finally, we provide a different way of constructing
the nascent minima distribution functions.


  Tissue microarray (TMA) images have been used increasingly often in cancer
studies and the validation of biomarkers. TACOMA---a cutting-edge automatic
scoring algorithm for TMA images---is comparable to pathologists in terms of
accuracy and repeatability. Here we consider how this algorithm may be further
improved. Inspired by the recent success of deep learning, we propose to
incorporate representations learnable through computation. We explore
representations of a group nature through unsupervised learning, e.g.,
hierarchical clustering and recursive space partition. Information carried by
clustering or spatial partitioning may be more concrete than the labels when
the data are heterogeneous, or could help when the labels are noisy. The use of
such information could be viewed as regularization in model fitting. It is
motivated by major challenges in TMA image scoring---heterogeneity and label
noise, and the cluster assumption in semi-supervised learning. Using this
information on TMA images of breast cancer, we have reduced the error rate of
TACOMA by about 6%. Further simulations on synthetic data provide insights on
when such representations would likely help. Although we focus on TMAs,
learnable representations of this type are expected to be applicable in other
settings.


  Foundation models contain a wealth of information from their vast number of
training samples. However, most prior arts fail to extract this information in
a precise and efficient way for small sample sizes. In this work, we propose a
framework utilizing reinforcement learning as a control for foundation models,
allowing for the granular generation of small, focused synthetic support sets
to augment the performance of neural network models on real data classification
tasks. We first allow a reinforcement learning agent access to a novel context
based dictionary; the agent then uses this dictionary with a novel prompt
structure to form and optimize prompts as inputs to generative models,
receiving feedback based on a reward function combining the change in
validation accuracy and entropy. A support set is formed this way over several
exploration steps. Our framework produced excellent results, increasing
classification accuracy by significant margins for no additional labelling or
data cost.


  The scrambling index of an $n\times n$ primitive matrix $A$ is the smallest
positive integer $k$ such that $A^k(A^{t})^k=J$, where $A^t$ denotes the
transpose of $A$ and $J$ denotes the $n\times n$ all ones matrix. For an
$m\times n$ Boolean matrix $M$, its {\it Boolean rank} $b(M)$ is the smallest
positive integer $b$ such that $M=AB$ for some $m \times b$ Boolean matrix $A$
and $b\times n$ Boolean matrix $B$. In this paper, we give an upper bound on
the scrambling index of an $n\times n$ primitive matrix $M$ in terms of its
Boolean rank $b(M)$. Furthermore we characterize all primitive matrices that
achieve the upper bound.


  As in such 2D systems as the XY model, topological (or singularity point)
defects are thought to play a crucial role in the phase transitions of 3D spin
systems. In double exchange (DE) ferromagnets, the conduction electrons are
strongly coupled with core spins through Hund's rule, and in the presence of
non-trivial spin texture, acquire a Berry phase contribution to the anomalous
Hall effect (AHE). We combine Hall and magnetization data on CrO$_2$ with a
thermodynamical scaling hypothesis to confirm that the critical behavior of the
topological-spin-defect density is consistent with that of the heat capacity.
This analysis is the first experimental confirmation of the topological
character of critical fluctuations.


  Recently observed oscillations in the solar atmosphere have been interpreted
and modeled as magnetohydrodynamic wave modes. This has allowed the estimation
of parameters that are otherwise hard to derive, such as the coronal
magnetic-field strength. This work crucially relies on the initial detection of
the oscillations, which is commonly done manually. The volume of Solar Dynamics
Observatory (SDO) data will make manual detection inefficient for detecting all
of the oscillating regions. An algorithm is presented which automates the
detection of areas of the solar atmosphere that support spatially extended
oscillations. The algorithm identifies areas in the solar atmosphere whose
oscillation content is described by a single, dominant oscillation within a
user-defined frequency range. The method is based on Bayesian spectral analysis
of time-series and image filtering. A Bayesian approach sidesteps the need for
an a-priori noise estimate to calculate rejection criteria for the observed
signal, and it also provides estimates of oscillation frequency, amplitude and
noise, and the error in all these quantities, in a self-consistent way. The
algorithm also introduces the notion of quality measures to those regions for
which a positive detection is claimed, allowing simple post-detection
discrimination by the user. The algorithm is demonstrated on two Transition
Region and Coronal Explorer (TRACE) datasets, and comments regarding its
suitability for oscillation detection in SDO are made.


  We present a composable security proof, valid against arbitrary attacks and
including finite-size effects, for a high dimensional time-frequency quantum
key distribution (TFQKD) protocol based upon spectrally entangled photons.
Previous works have focused on TFQKD schemes as it combines the impressive loss
tolerance of single-photon QKD with the large alphabets of continuous variable
(CV) schemes, which enables the potential for more than one bit of secret key
per transmission. However, the finite-size security of such schemes has only
been proven under the assumption of collective Gaussian attacks. Here, by
combining recent advances in entropic uncertainty relations for CVQKD with
decoy state analysis, we derive a composable security proof that predicts key
rates on the order of Mbits/s over metropolitan distances (40km or less) and
maximum transmission distances of up to 140km.


  Using the resolution quiver for a connected Nakayama algebra, a fast
algorithm is given to decide whether its global dimension is finite or not and
whether it is Gorenstein or not. The latter strengthens a result of Ringel.


  Understanding the characteristics of the solar magnetic field is essential
for interpreting solar activities and dynamo. In this research, we investigated
the asymmetric distribution of the solar photospheric magnetic field values,
using synoptic charts constructed from space-borne high-resolution
magnetograms. It is demonstrated that the Lorentzian function describes the
distribution of magnetic field values in the synoptic charts much better than
the Gaussian function, and this should reflect the gradual decay process from
strong to weak magnetic fields. The asymmetry values are calculated under
several circumstances, and the results generally show two periodicities related
to the variation of the solar B$_0$ angle and the solar cycle, respectively. We
argue that it is the small-scale magnetic fields, the inclination of the solar
axis, the emergence and evolution of magnetic flux, and the polar fields that
are responsible for the features of asymmetry values. We further determined the
polar field reversal time of solar cycles 23 and 24 with the flip of asymmetry
values. Specifically, for cycle 24, we assert that the polar polarities of both
hemispheres reversed at the same time - in March 2014; as to cycle 23, the
reversal time of the S-hemisphere is March 2001, while the determination of the
N-hemisphere is hampered by missing data.


  We describe in detail a previously published measurement of CP violation
induced by B0-anti B0 oscillations, based on an integrated luminosity of 425.7
fb-1 collected by the BABAR experiment at the PEPII collider. We apply a novel
technique to a sample of about 6 million B0bar -> D*+ l- nubar decays selected
with partial reconstruction of the D*+ meson. The charged lepton identifies the
flavor of one B meson at its decay time, the flavor of the other B is
determined by kaon tagging. We determine a CP violating asymmetry ACP = (0.0006
+- 0.0017 + 0.0038 - 0.0032). This measurement is consistent and competitive
with those obtained at the B factories with dilepton events.


  We compute scalar products and norms of Bethe vectors in the massless sector
of AdS_3 integrable superstring theories, by exploiting the general difference
form of the S-matrix of massless excitations in the pure Ramond-Ramond case,
and the difference form valid only in the BMN limit in the mixed-flux case. We
obtain determinant-like formulas for the scalar products, generalising a
procedure developed in previous literature for standard R-matrices to the
present non-conventional situation. We verify our expressions against explicit
calculations using Bethe vectors for chains of small length, and perform some
computer tests of the exact formulas as far as numerical accuracy sustains us.
This should be the first step towards the derivation of integrable form-factors
and correlation functions for the AdS_3 S-matrix theory.


  The large branching ratio for B-> K1 gamma recently measured at Belle implies
a large B -> K1 transition form factor and large branching ratios for non
leptonic B decays involving an axial-vector meson. In this paper we present an
analysis of two-body B decays with an axial-vector meson in the final state
using naive factorization and the B -> K1 form factors obtained from the
measured radiative decays. We find that the predicted B -> J/psi K1 branching
ratio is in agreement with experiment. We also suggest that the decay rates of
B -> K1 pi, B -> a1 K and B -> b1 K could be used to test the factorization
ansatz.


  We calculate the threshold singularities in one-dimensional models using the
universal low-energy formfactors obtained in the framework of the non-linear
Luttinger liquid model. We find the reason why the simplified picture of the
impurity moving in the Luttinger liquid leads to the correct results. We obtain
the prefactors of the singularities including their $k$- dependence at small
$k<<p_F$.


  We study modifications of the Viterbi Training (VT) algorithm to estimate
emission parameters in Hidden Markov Models (HMM) in general, and in mixure
models in particular. Motivated by applications of VT to HMM that are used in
speech recognition, natural language modeling, image analysis, and
bioinformatics, we investigate a possibility of alleviating the inconsistency
of VT while controlling the amount of extra computations. Specifically, we
propose to enable VT to asymptotically fix the true values of the parameters as
does the EM algorithm. This relies on infinite Viterbi alignment and an
associated with it limiting probability distribution. This paper, however,
focuses on mixture models, an important case of HMM, wherein the limiting
distribution can always be computed exactly; finding such limiting distribution
for general HMM presents a more challenging task under our ongoing
investigation.
  A simulation of a univariate Gaussian mixture shows that our central
algorithm (VA1) can dramatically improve accuracy without much cost in
computation time.
  We also present VA2, a more mathematically advanced correction to VT, verify
by simulation its fast convergence and high accuracy; its computational
feasibility remains to be investigated in future work.


  We study the dynamics of driven polymer translocation using both molecular
dynamics (MD) simulations and a theoretical model based on the non-equilibrium
tension propagation on the {\it cis} side subchain. We present theoretical and
numerical evidence that the non-universal behavior observed in experiments and
simulations are due to finite chain length effects that persist well beyond the
relevant experimental and simulation regimes. In particular, we consider the
influence of the pore-polymer interactions and show that they give a major
contribution to the non-universal effects. In addition, we present comparisons
between the theory and MD simulations for several quantities, showing extremely
good agreement in the relevant parameter regimes. Finally, we discuss the
potential limitations of the present theories.


  To measure the stellar and orbital properties of the metal-poor RS CVn binary
o Draconis (o Dra), we directly detect the companion using interferometric
observations obtained with the Michigan InfraRed Combiner at Georgia State
University's Center for High Angular Resolution Astronomy (CHARA) Array. The
H-band flux ratio between the primary and secondary stars is the highest
confirmed flux ratio (370 +/- 40) observed with long-baseline optical
interferometry. These detections are combined with radial velocity data of both
the primary and secondary stars, including new data obtained with the
Tillinghast Reflector Echelle Spectrograph on the Tillinghast Reflector at the
Fred Lawrence Whipple Observatory and the 2-m Tennessee State University
Automated Spectroscopic Telescope at Fairborn Observatory. We determine an
orbit from which we find model-independent masses and ages of the components
(M_A = 1.35 +\- 0.05 M_Sun, M_B = 0.99 +\- 0.02 M_Sun, system age = 3.0 -\+ 0.5
Gyr). An average of a 23-year light curve of o Dra from the Tennessee State
University Automated Photometric Telescope folded over the orbital period newly
reveals eclipses and the quasi-sinusoidal signature of ellipsoidal variations.
The modeled light curve for our system's stellar and orbital parameters confirm
these ellipsoidal variations due to the primary star partially filling its
Roche lobe potential, suggesting most of the photometric variations are not due
to stellar activity (starspots). Measuring gravity darkening from the average
light curve gives a best-fit of beta = 0.07 +\- 0.03, a value consistent with
conventional theory for convective envelope stars. The primary star also
exhibits an anomalously short rotation period, which, when taken with other
system parameters, suggests the star likely engulfed a low-mass companion that
had recently spun-up the star.


  The Adams conjecture states that the local theta correspondence sends a local
Arthur packet to another local Arthur packet. M{\oe}glin confirmed the
conjecture when lifting to groups of sufficiently high rank and also showed
that it fails in low rank. Recently, Baki\'c and Hanzer described when the
Adams conjecture holds in low rank for a representation in a fixed local Arthur
packet. However, a representation may lie in many local Arthur packets and each
gives a minimal rank for which the Adams conjecture holds. In this paper, we
study the interplay of intersections of local Arthur packets with the Adams
conjecture.


  Learned dynamics models combined with both planning and policy learning
algorithms have shown promise in enabling artificial agents to learn to perform
many diverse tasks with limited supervision. However, one of the fundamental
challenges in using a learned forward dynamics model is the mismatch between
the objective of the learned model (future state reconstruction), and that of
the downstream planner or policy (completing a specified task). This issue is
exacerbated by vision-based control tasks in diverse real-world environments,
where the complexity of the real world dwarfs model capacity. In this paper, we
propose to direct prediction towards task relevant information, enabling the
model to be aware of the current task and encouraging it to only model relevant
quantities of the state space, resulting in a learning objective that more
closely matches the downstream task. Further, we do so in an entirely
self-supervised manner, without the need for a reward function or image labels.
We find that our method more effectively models the relevant parts of the scene
conditioned on the goal, and as a result outperforms standard task-agnostic
dynamics models and model-free reinforcement learning.


  We derive a dielectric function tensor model approach to render the optical
response of monoclinic and triclinic symmetry materials with multiple uncoupled
infrared and farinfrared active modes. We apply our model approach to
monoclinic $\beta$-Ga$_2$O$_3$ single crystal samples. Surfaces cut under
different angles from a bulk crystal, (010) and ($\bar{2}$01), are investigated
by generalized spectroscopic ellipsometry within infrared and farinfrared
spectral regions. We determine the frequency dependence of 4 independent
$\beta$-Ga$_2$O$_3$ Cartesian dielectric function tensor elements by matching
large sets of experimental data using a point by point data inversion approach.
From matching our monoclinic model to the obtained 4 dielectric function tensor
components, we determine all infared and farinfrared active transverse optic
phonon modes with $A_u$ and $B_u$ symmetry, and their eigenvectors within the
monoclinic lattice. We find excellent agreement between our model results and
results of density functional theory calculations. We derive and discuss the
frequencies of longitudinal optical phonons in $\beta$-Ga$_2$O$_3$. We derive
and report density and anisotropic mobility parameters of the free charge
carriers within the tin doped crystals. We discuss the occurrence of
longitudinal phonon plasmon coupled modes in $\beta$-Ga$_2$O$_3$ and provide
their frequencies and eigenvectors. We also discuss and present monoclinic
dielectric constants for static electric fields and frequencies above the
reststrahlen range, and we provide a generalization of the Lyddane-Sachs-Teller
relation for monoclinic lattices with infrared and farinfrared active modes. We
find that the generalized Lyddane-Sachs-Teller relation is fulfilled
excellently for $\beta$-Ga$_2$O$_3$.


  This study aims to develop a new computational pathology approach that
automates the identification and quantification of myocardial inflammatory
infiltration in digital HE-stained images to provide a quantitative
histological diagnosis of myocarditis.898 HE-stained whole slide images (WSIs)
of myocardium from 154 heart transplant patients diagnosed with myocarditis or
dilated cardiomyopathy (DCM) were included in this study. An automated DL-based
computational pathology approach was developed to identify nuclei and detect
myocardial inflammatory infiltration, enabling the quantification of the
lymphocyte nuclear density (LND) on myocardial WSIs. A cutoff value based on
the quantification of LND was proposed to determine if the myocardial
inflammatory infiltration was present. The performance of our approach was
evaluated with a five-fold cross-validation experiment, tested with an internal
test set from the myocarditis group, and confirmed by an external test from a
double-blind trial group. An LND of 1.02/mm2 could distinguish WSIs with
myocarditis from those without. The accuracy, sensitivity, specificity, and
area under the receiver operating characteristic curve (AUC) in the five-fold
cross-validation experiment were 0.899 plus or minus 0.035, 0.971 plus or minus
0.017, 0.728 plus or minus 0.073 and 0.849 plus or minus 0.044, respectively.
For the internal test set, the accuracy, sensitivity, specificity, and AUC were
0.887, 0.971, 0.737, and 0.854, respectively. The accuracy, sensitivity,
specificity, and AUC for the external test set reached 0.853, 0.846, 0.858, and
0.852, respectively. Our new approach provides accurate and reliable
quantification of the LND of myocardial WSIs, facilitating automated
quantitative diagnosis of myocarditis with HE-stained images.


  We establish a one-to-one mapping between entanglement entropy, energy, and
temperature (quantum entanglement mechanics) with black hole entropy, Komar
energy, and Hawking temperature, respectively. We show this explicitly for 4-D
spherically symmetric asymptotically flat and non-flat space-times with single
and multiple horizons. We exploit an inherent scaling symmetry of entanglement
entropy and identify scaling transformations that generate an infinite number
of systems with the same entanglement entropy, distinguished only by their
respective energies and temperatures. We show that this scaling symmetry is
present in most well-known systems starting from the two-coupled harmonic
oscillator to quantum scalar fields in spherically symmetric space-time. The
scaling symmetry allows us to identify the cause of divergence of entanglement
entropy to the generation of (near) zero-modes in the systems. We
systematically isolate the zero-mode contributions using suitable boundary
conditions. We show that the entanglement entropy and energy of quantum scalar
field scale differently in space-times with horizons and flat space-time. The
relation $E=2TS$, in analogy with the horizon's thermodynamic structure, is
also found to be universally satisfied in the entanglement picture. We then
show that there exists a one-to-one correspondence leading to the Smarr-formula
of black hole thermodynamics for asymptotically flat and non-flat space-times.


  We address Bessel photonic lattices of radial symmetry imprinted in cubic
Kerr-type nonlinear media and show that they support families of stable
dipole-mode solitons featuring two out-of-phase light spots located in
different lattice rings. We show that the radial symmetry of the Bessel
lattices afford a variety of unique soliton dynamics including controlled
radiation-free rotation of the dipole-mode solitons.


  This paper presents the experiments accomplished as a part of our
participation in the MEDIQA challenge, an (Abacha et al., 2019) shared task. We
participated in all the three tasks defined in this particular shared task. The
tasks are viz. i. Natural Language Inference (NLI) ii. Recognizing Question
Entailment(RQE) and their application in medical Question Answering (QA). We
submitted runs using multiple deep learning based systems (runs) for each of
these three tasks. We submitted five system results in each of the NLI and RQE
tasks, and four system results for the QA task. The systems yield encouraging
results in all three tasks. The highest performance obtained in NLI, RQE and QA
tasks are 81.8%, 53.2%, and 71.7%, respectively.


  We investigate the production of magnetic flux from rotating black holes in
active galactic nuclei (AGNs) and compare it with the upper limit of ultrahigh
energy cosmic ray (UHECR) luminosities, calculated from observed integral flux
of GeV-TeV gamma rays for nine UHECR AGN sources. We find that, for the
expected range of black hole rotations (0.44<a<0.80), the corresponding bounds
of theoretical magnetic luminosities from AGNs coincides with the calculated
UHECR luminosity. We argue that such result possibly can contribute to
constrain AGN magnetic and dynamic properties as phenomenological tools to
explain the requisite conditions to proper accelerate the highest energy cosmic
rays.


  It was recently proposed to use the stray magnetic fields of superconducting
vortex lattices to trap ultracold atoms for building quantum emulators. This
calls for new methods for engineering and manipulating of the vortex states.
One of the possible routes utilizes type-1.5 superconducting layered systems
with multi-scale inter-vortex interactions. In order to explore the possible
vortex states that can be engineered, we present two phase diagrams of
phenomenological vortex matter models with multi-scale inter-vortex
interactions featuring several attractive and repulsive length scales. The
phase diagrams exhibit a plethora of phases, including conventional 2D lattice
phases, five stripe phases, dimer, trimer, and tetramer phases, void phases,
and stable low-temperature disordered phases. The transitions between these
states can be controlled by the value of an applied external field.


  The Potential Field (PF)-based path planning method is widely adopted for
autonomous vehicles (AVs) due to its real-time efficiency and simplicity. PF
often creates a rigid road boundary, and while this ensures that the ego
vehicle consistently operates within the confines of the road, it also brings a
lurking peril in emergency scenarios. If nearby vehicles suddenly switch lanes,
the AV has to veer off and brake to evade a collision, leading to the "blind
alley" effect. In such a situation, the vehicle can become trapped or confused
by the conflicting forces from the obstacle vehicle PF and road boundary PF,
often resulting in indecision or erratic behavior, even crashes. To address the
above-mentioned challenges, this research introduces an Emergency-Stopping Path
Planning (ESPP) that incorporates an adaptive PF (APF) and a clothoid curve for
urgent evasion. First, we design an emergency triggering estimation to detect
the "blind alley" problem by analyzing the PF distribution. Second, we
regionalize the driving scene to search the optimal breach point on the road PF
and the final stopping point for the vehicle by considering the possible motion
range of the obstacle. Finally, we use the optimized clothoid curve to fit
these calculated points under vehicle dynamics constraints to generate a smooth
emergency avoidance path. The proposed ESPP-based APF method was evaluated by
conducting the co-simulation between MATLAB/Simulink and CarSim Simulator in a
freeway scene. The simulation results reveal that the proposed method shows
increased performance in emergency collision avoidance and renders the vehicle
safer, in which the duration of wheel slip is 61.9% shorter, and the maximum
steering angle amplitude is 76.9% lower than other potential field-based
methods.


  A recent proof-of-principle study proposes an energy- and charge-conserving,
nonlinearly implicit electrostatic particle-in-cell (PIC) algorithm in one
dimension [Chen et al, J. Comput. Phys., 230 (2011) 7018]. The algorithm in the
reference employs an unpreconditioned Jacobian-free Newton-Krylov method, which
ensures nonlinear convergence at every timestep (resolving the dynamical
timescale of interest). Kinetic enslavement, which is one key component of the
algorithm, not only enables fully implicit PIC a practical approach, but also
allows preconditioning the kinetic solver with a fluid approximation. This
study proposes such a preconditioner, in which the linearized moment equations
are closed with moments computed from particles. Effective acceleration of the
linear GMRES solve is demonstrated, on both uniform and non-uniform meshes. The
algorithm performance is largely insensitive to the electron-ion mass ratio.
Numerical experiments are performed on a 1D multi-scale ion acoustic wave test
problem.


  Quantum Key Distribution with the BB84 protocol has been shown to be
unconditionally secure even using weak coherent pulses instead of single-photon
signals. The distances that can be covered by these methods are limited due to
the loss in the quantum channel (e.g. loss in the optical fiber) and in the
single-photon counters of the receivers. One can argue that the loss in the
detectors cannot be changed by an eavesdropper in order to increase the covered
distance. Here we show that the security analysis of this scenario is not as
easy as is commonly assumed, since already two-photon processes allow
eavesdropping strategies that outperform the known photon-number splitting
attack. For this reason there is, so far, no satisfactory security analysis
available in the framework of individual attacks.


  Making use of the nonrelativistic potential model for the description of
mesons, and working in the Shifman-Voloshin limit, we compare the integrated
rate $\Gamma(B\to X_cl\nu)$ calculated as a sum of the individual decay rates
to the quantum-mechanical analog of the OPE. In the case of a potential regular
at the origin, we find a well-defined duality violation, which is however
exponentially small. It corresponds to the charm resonances kinematically
forbidden in the decay process, but apparently picked up by the OPE. For
singular potentials, we do not obtain a full OPE series, but only a limited
Taylor expansion, since the cofficients become infinite beyond some order. In
this case, we do not find an indication of duality violation: the difference is
smaller than the last term of the limited expansion. This emphasizes that the
case of singular potentials, which may be relevant for QCD, deserves further
study.


  Machine translation (MT) involving Indigenous languages, including those
possibly endangered, is challenging due to lack of sufficient parallel data. We
describe an approach exploiting bilingual and multilingual pretrained MT models
in a transfer learning setting to translate from Spanish to ten South American
Indigenous languages. Our models set new SOTA on five out of the ten language
pairs we consider, even doubling performance on one of these five pairs. Unlike
previous SOTA that perform data augmentation to enlarge the train sets, we
retain the low-resource setting to test the effectiveness of our models under
such a constraint. In spite of the rarity of linguistic information available
about the Indigenous languages, we offer a number of quantitative and
qualitative analyses (e.g., as to morphology, tokenization, and orthography) to
contextualize our results.


  We study the chiral separation and chiral magnetic effects in a slab of Dirac
semimetal of finite thickness, placed in a constant magnetic field
perpendicular to its surfaces. We utilize the Bogolyubov boundary conditions
with a large Dirac mass (band gap) outside the slab. We find that, in a finite
thickness slab, the axial current density is induced by helicity-correlated
standing waves and, as a consequence, is quantized. The quantization is seen in
its stepped-shape dependence on the fermion chemical potential and a
sawtooth-shape dependence on the thickness of the slab. In contrast to a naive
expectation, there is no chiral charge accumulation anywhere in the bulk or at
the boundaries of the semimetal. In the same slab geometry, we also find that a
nonzero chiral chemical potential induces no electric current, as might have
been expected from the chiral magnetic effect. We argue that this outcome is
natural and points to the truly non-static nature of the latter. By taking into
account a nonzero electric field of a double layer near the boundaries of the
slab, we find that the low-energy modes under consideration satisfy the
continuity equation for axial current density without the anomalous term.


  The muon g-2 discrepancy between theory and experiment may be explained by a
light vector boson Z_d that couples to the electromagnetic current via kinetic
mixing with the photon. We illustrate how the existing electron g-2, pion
Dalitz decay, and other direct production data disfavor that explanation if the
Z_d mainly decays into e+e-, mu+mu-. Implications of a dominant invisible Z_d
decay channel, such as light dark matter, along with the resulting strong
bounds from the rare K -> pi + 'missing energy' decay are examined. The K decay
constraints may be relaxed if destructive interference effects due to Z-Z_d
mass mixing are included. In that scenario, we show that accommodating the muon
g-2 data through relaxation of K decay constraints leads to interesting signals
for dark parity violation. As an illustration, we examine the alteration of the
weak mixing angle running at low Q^2, which can be potentially observable in
polarized electron scattering or atomic physics experiments.


  Runaway electrons, which are generated in a plasma where the induced electric
field exceeds a certain critical value, can reach very high energies in the MeV
range. For such energetic electrons, radiative losses will contribute
significantly to the momentum space dynamics. Under certain conditions, due to
radiative momentum losses, a non-monotonic feature - a "bump" - can form in the
runaway electron tail, creating a potential for bump-on-tail-type instabilities
to arise. Here we study the conditions for the existence of the bump. We derive
an analytical threshold condition for bump appearance and give an approximate
expression for the minimum energy at which the bump can appear. Numerical
calculations are performed to support the analytical derivations.


  In this note, we examine the Jacobian ring description of the Hodge structure
of zero loci of vector bundle sections on a class of ambient varieties. We
consider a set of cohomological vanishing conditions that imply such a
description, and we verify these conditions for some new cases. We also observe
that the method can be directly extended to log homogeneous varieties. We apply
the Jacobian ring to study the null varieties of period integrals and their
derivatives, generalizing a result in [9] for projective spaces. As an
additional application, we prove the Hodge conjecture for very generic
hypersurfaces in certain generalized flag varieties.


  Bacteriophages, phages for short, are viruses of bacteria. The majority of
phages contain a double-stranded DNA genome packaged in a capsid at a density
of ~500 mg/ml. This high density requires substantial compression of the normal
B form helix, leading to the conjecture that DNA in mature phage virions is
under significant pressure, and that pressure is used to eject the DNA during
infection. A large number of theoretical, computer simulation and in vitro
experimental studies surrounding this conjecture has revealed many --- though
often isolated and/or contradictory --- aspects of packaged DNA. This prompts
us to present a unified view of the statistical physics and thermodynamics of
DNA packaged in phage capsids. We argue that the DNA in a mature phage is in a
(meta)stable state, wherein electrostatic self-repulsion is balanced by
curvature stress due to confinement in the capsid. We show that in addition to
the osmotic pressure associated with the packaged DNA and its counterions,
there are four different pressures within the capsid: pressure on the DNA,
hydrostatic pressure, the pressure experienced by the capsid, and the pressure
associated with the chemical potential of DNA ejection. Significantly, we
analyze the mechanism of force transmission in the packaged DNA, and
demonstrate that the pressure on DNA is not important for ejection. We derive
equations showing a strong hydrostatic pressure difference across the capsid
shell. We propose that when a phage is triggered to eject by interaction with
its receptor in vitro, the (thermodynamic) incentive of water molecules to
enter the phage capsid flushes the DNA out of the capsid. In vivo, the
difference between the osmotic pressures in the bacterial cell cytoplasm and
the culture medium similarly results in a water flow that drags the DNA out of
the capsid and into the bacterial cell.


  Assume that the eigenvalues of a finite hermitian linear operator have been
deduced accurately but the linear operator itself could not be determined with
precision. Given a set of eigenvalues $\lambda$ and a hermitian matrix $M$,
this paper will explain, with proofs, how to find a hermitian matrix $A$ with
the desired eigenvalues $\lambda$ that is as close as possible to the given
operator $M$ according to the operator 2-norm metric. Furthermore the effects
of this solution are put to a test using random matrices and grayscale images
which evidently show the smoothing property of eigenvalue corrections.


  Parasitic extraction is a powerful tool in the design process of
electromechanical devices, specifically as part of workflows that check
electromagnetic compatibility. A novel scheme to extract impedances from CAD
device models, suitable for a finite element implementation, is derived from
Maxwell's equations in differential form. It provides a foundation for
parasitic extraction across a broad frequency range and is able to handle
inhomogeneous permittivities and permeabilities, making it more flexible than
existing integral equation approaches. The approach allows for the automatic
treatment of multi-port models of arbitrary conductor geometry without
requiring any significant manual user interaction. This is achieved by
computing a connecting source current density that supplies current to the
model's terminals, whatever their location in the model, subsequently using
this current density to compute the electric field, and finally calculating the
impedance via a scalar potential. A mandatory low-frequency stabilization
scheme is outlined, ensuring a stable evaluation of the model at low
frequencies as well. Two quasistatic approximations and the special case of
perfect electric conductors are treated theoretically. The magnetoquasistatic
approximation is validated against an analytical model in a numerical
experiment. Moreover, the intrinsic capability of the method to treat
inhomogeneous permittivities and permeabilities is demonstrated with a simple
capacitor-coil model including dielectric insulation and magnetic core
materials.


  We explain how to encode an algebraic series by a finite amount of data,
namely its minimal polynomial, a total order and its first terms with respect
to this order, and how to do effective arithmetic on the level of these
encodings. The reasoning is based on the Newton-Puiseux algorithm and an
effective equality test for algebraic series. We also explain how to derive
information about the support of an algebraic series, e.g. how to compute the
vertices and bounded faces of the convex hull of its support.


  We use 64 square degrees of deep V and R CCD images to measure the local V
and R band luminosity function of galaxies. The V_0<16.7 and R_0<16.2 redshift
samples contain 1250 galaxies and are 98% complete. We apply k-corrections
before the magnitude selection so that the completeness is to the same depth
for all spectral types. The V and R faint end slopes are surprisingly
identical: alpha = -1.07+-0.09. Representative Schechter function parameters
for H_0=100 are: M^*_R = -20.88+-0.09, phi^*_R = 0.016+-0.003 Mpc^-3 and M^*_V
= -20.23+-0.09, phi^*_V = 0.020+-0.003 Mpc^-3. The V and R local luminosity
densities, j_R = (1.9+-0.6)x10^8 and j_V = (2.2+-0.7)x10^8 L_sun, are in
essential agreement with the recent 2dF and SDSS determinations.
  All low surface brightness (LSB) galaxies fall in the large scale structure
delineated by high surface brightness galaxies. The properties and surface
number density of our LSB galaxies are consistent with the LSB galaxy catalog
of O'Neil, Bothun & Cornell, suggesting that our samples are complete for LSB
galaxies to the magnitude limits. We measure colors, surface brightnesses, and
luminosities for our samples, and find strong correlations among these galaxy
properties.


  We calculate the period of recurrence of dynamical systems comprising two
interacting bosons. A number of theoretical issues related to this problem are
discussed, in particular, the conditions for small periodicity. The knowledge
gathered in this way is then used to propose a notion of dynamical stability
based on the stability of the period. Dynamical simulations show good agreement
with the proposed scheme. We also apply the results to the phenomenon known as
coherent population trapping and find stability conditions in this specific
case.


  We study the efficiency of heat engines that perform mechanical work via the
pdV terms present in the First Law in extended gravitational thermodynamics. We
use charged black holes as the working substance, for a particular choice of
engine cycle. The context is Einstein gravity with negative cosmological
constant and a Born-Infeld non-linear electrodynamics sector. We compare the
results for these `holographic' heat engines to previous results obtained for
Einstein-Maxwell black holes, and for the case where there is a Gauss-Bonnet
sector.


  Multifractal analysis has become a standard signal processing tool,for which
a promising new formulation, the p-leader multifractal formalism, has recently
been proposed. It relies on novel multiscale quantities, the p-leaders, defined
as local l^p norms of sets of wavelet coefficients located at infinitely many
fine scales. Computing such infinite sums from actual finite-resolution data
requires truncations to the finest available scale, which results in biased
p-leaders and thus in inaccurate estimates of multifractal properties. A
systematic study of such finite-resolution effects leads to conjecture an
explicit and universal closed-form correction that permits an accurate
estimation of scaling exponents. This conjecture is formulated from the
theoretical study of a particular class of models for multifractal processes,
the wavelet-based cascades. The relevance and generality of the proposed
conjecture is assessed by numerical simulations conducted over a large variety
of multifractal processes. Finally, the relevance of the proposed corrected
estimators is demonstrated on the analysis of heart rate variability data.


  This paper aims to benchmark recent progress in language understanding models
that output contextualised representations at the character level. Many such
modelling architectures and methods to train those architectures have been
proposed, but it is currently unclear what the relative contributions of the
architecture vs. the pretraining objective are to final model performance. We
explore the design space of such models, comparing architectural innovations
and a variety of different pretraining objectives on a suite of evaluation
tasks with a fixed training procedure in order to find the currently optimal
way to build and train character-level BERT-like models. We find that our best
performing character-level model exceeds the performance of a token-based model
trained with the same settings on the same data, suggesting that
character-level models are ready for more widespread adoption. Unfortunately,
the best method to train character-level models still relies on a subword-level
tokeniser during pretraining, and final model performance is highly dependent
on tokeniser quality. We believe our results demonstrate the readiness of
character-level models for multilingual language representation, and encourage
NLP practitioners to try them as drop-in replacements for token-based models.


  A $d$-dimensional second-order topological insulator (SOTI) can host
topologically protected $(d - 2)$-dimensional gapless boundary modes. Here we
show that a 2D non-Hermitian SOTI can host zero-energy modes at its corners. In
contrast to the Hermitian case, these zero-energy modes can be localized only
at one corner. A 3D non-Hermitian SOTI is shown to support second-order
boundary modes, which are localized not along hinges but anomalously at a
corner. The usual bulk-corner (hinge) correspondence in the second-order 2D
(3D) non-Hermitian system breaks down. The winding number (Chern number) based
on complex wavevectors is used to characterize the second-order topological
phases in 2D (3D). A possible experimental situation with ultracold atoms is
also discussed. Our work lays the cornerstone for exploring higher-order
topological phenomena in non-Hermitian systems.


  We consider the quadratic Zakharov-Kuznetsov equation $$ \partial_t u +
\partial_x \Delta u + \partial_x u^2 =0 $$ on $\mathbb{R}^3$. A solitary wave
solution is given by $Q(x-t,y,z)$, where $Q$ is the ground state solution to
$-Q + \Delta Q + Q^2 =0$. We prove the asymptotic stability of these solitary
wave solutions. Specifically, we show that initial data close to $Q$ in the
energy space, evolves to a solution that, as $t\to\infty$, converges to a
rescaling and shift of $Q(x-t,y,z)$ in $L^2$ in a rightward shifting region $x>
\delta t -\tan \theta \sqrt{y^2+z^2} $ for $0 \leq \theta \leq
\frac{\pi}{3}-\delta$.


  Active drops emit/absorb chemical solutes, whose concentration gradients
cause interfacial flows driving their own transport and the propulsion of the
droplet. Such non-linear coupling enables active drops to achieve directed
self-propulsion despite their isotropy, if the ratio of advective-to-diffusive
solute transport, i.e. the Peclet number Pe, is larger than a finite critical
threshold. In most experimental situations, active drops are non-neutrally
buoyant and thus swim along rigid surfaces; yet theoretical descriptions of
their non-linear motion focus almost exclusively on unbounded domains to
circumvent geometric complexity. To overcome this gap in understanding, we
investigate the spontaneous emergence and nonlinear saturation of propulsion of
an isotropic phoretic colloid along a rigid wall, to which it is confined by a
constant external force (e.g., gravity). This phoretic particle model is
considered here as a limiting case for a viscous active drop. We show that, for
moderate Pe, the particle motion and associated chemical transport reduce the
chemically-induced wall repulsion, thereby causing the particle to swim
progressively closer to the wall as Pe increases. Far from hindering
self-propulsion, this reduction in the particle-wall separation is accompanied
by a wall-induced efficient rearrangement of the solute concentration gradients
driving the particle, thus augmenting its swimming speed.


  We prove the irreducibility of the Hurwitz spaces which parametrize Galois
coverings of P^1 whose Galois group is an arbitrary Weyl group and the local
monodromies are reflections. This generalizes a classical theorem due to
Clebsch and Hurwitz.


  The novel SoLAr concept aims to extend sensitivities of liquid-argon neutrino
detectors down to the MeV scale for next-generation detectors. SoLAr plans to
accomplish this with a liquid-argon time projection chamber that employs an
anode plane with dual charge and light readout, which enables precision
matching of light and charge signals for data acquisition and reconstruction
purposes. We present the results of a first demonstration of the SoLAr detector
concept with a small-scale prototype detector integrating a pixel-based charge
readout and silicon photomultipliers on a shared printed circuit board. We
discuss the design of the prototype, and its operation and performance,
highlighting the capability of such a detector design.


  We construct with a geometric procedure the supersymmetry transformation laws
and Lagrangian for all the ``variant'' D=11 and D=10 Type IIA supergravities.
We identify into our classification the D=11 and D=10 Type IIA ``variant''
theories first introduced by Hull performing T-duality transformation on both
spacelike and timelike circles. We find in addition a set of D=10 Type IIA
``variant'' supergravities that can not be obtained trivially from eleven
dimensions compactifying on a circle.


  Many clustering algorithms are guided by certain cost functions such as the
widely-used $k$-means cost. These algorithms divide data points into clusters
with often complicated boundaries, creating difficulties in explaining the
clustering decision. In a recent work, Dasgupta, Frost, Moshkovitz, and
Rashtchian (ICML 2020) introduced explainable clustering, where the cluster
boundaries are axis-parallel hyperplanes and the clustering is obtained by
applying a decision tree to the data. The central question here is: how much
does the explainability constraint increase the value of the cost function?
  Given $d$-dimensional data points, we show an efficient algorithm that finds
an explainable clustering whose $k$-means cost is at most $k^{1 -
2/d}\,\mathrm{poly}(d\log k)$ times the minimum cost achievable by a clustering
without the explainability constraint, assuming $k,d\ge 2$. Taking the minimum
of this bound and the $k\,\mathrm{polylog} (k)$ bound in independent work by
Makarychev-Shan (ICML 2021), Gamlath-Jia-Polak-Svensson (2021), or
Esfandiari-Mirrokni-Narayanan (2021), we get an improved bound of $k^{1 -
2/d}\,\mathrm{polylog}(k)$, which we show is optimal for every choice of
$k,d\ge 2$ up to a poly-logarithmic factor in $k$. For $d = 2$ in particular,
we show an $O(\log k\log\log k)$ bound, improving near-exponentially over the
previous best bound of $O(k\log k)$ by Laber and Murtinho (ICML 2021).


  In recent years, topology optimization has been developed sufficiently and
many researchers have concentrated on enhancing to computationally numerical
algorithms for computational effectiveness of this method. Along with the
development of topology optimization, High Performance Computing (HPC) was
marked by a strong dynamic mechanism with a continuous appearance and
disappearance of manufacturers, systems, and architectures. Preconditioned
conjugate gradient multigrid method (pCGMG) is the most popular in HPC due to
its advantage in very large-scale problems. The idea which applies high
performance computing to reduce time of running in multi-material topology
optimization (MTO) problems with computational time burdens is newly proposed
in this article. In multi-material topology optimization procedures, pCGMG is
applied for solving linear equation arising from discretization of differential
equations. pCGMG is based on mesh size, and then it is powerful to larger scale
problems. For the large scale linear static system, minimal compliance-based
design is evaluated in this study. This study contributes to a high-performance
computing that pCGMG is integrated to an MTO problem, and numerical examples of
pCGMG are executed to compare with optimization results in terms of iteration
and time-running of different mesh sizes of square wall structure.


  Approximate Message Passing (AMP) algorithmshave recently gathered
significant attention across disciplines such as statistical physics, machine
learning, and communication systems. This study aims to extend AMP algorithms
to non-symmetric (elliptic) matrices, motivated by analyzing equilibrium
properties in ecological systems featuring elliptic interaction matrices.In
this article, we provide the general form of an AMP algorithm associated to a
random elliptic matrix, the main change lying in a modification of the
corrective (Onsager) term. In order to establish the statistical properties of
this algorithm, we use and prove a generalized form of Bolthausen conditioning
argument, pivotal to proceed by a Gaussian-based induction.We finally address
the initial motivating question from theoretical ecology. Large foodwebs are
often described by Lotka-Volterra systems of coupled differential equations,
where the interaction matrix is elliptic random. In this context, we design an
AMP algorithm to analyze the statistical properties of the equilibrium point in
a high-dimensional regime. We rigorously recover the results established by
[Bunin, 2017] and [Galla,2018] who used techniques from theoretical physics,
and extend them with the help of propagation of chaos type arguments.


  We investigate a network model based on an infinite regular square lattice
embedded in the Euclidean plane where the node connection probability is given
by the geometrical distance of nodes. We show that the degree distribution in
the basic model is sharply peaked around its mean value. Since the model was
originally developed to mimic the social network of acquaintances, to broaden
the degree distribution we propose its generalization. We show that when
heterogeneity is introduced to the model, it is possible to obtain fat tails of
the degree distribution. Meanwhile, the small-world phenomenon present in the
basic model is not affected. To support our claims, both analytical and
numerical results are obtained.


  This paper presents a convex, multi-period, AC-feasible Optimal Power Flow
(OPF) framework that robustly dispatches flexible demand-side resources in
unbalanced distribution feeders against uncertainty in very-short timescale
solar Photo-Voltaic (PV) forecasts. This is valuable for power systems with
significant behind-the-meter solar PV generation as their operation is affected
by uncertainty from forecasts of demand and solar PV generation. The aim of
this work is then to ensure the feasibility and reliability of distribution
system operation under high solar PV penetration. We develop and present a
novel, robust OPF formulation that accounts for both the nonlinear power flow
constraints and the uncertainty in forecasts. This is achieved by linearizing
an optimal trajectory and using first-order methods to systematically tighten
voltage bounds. Case studies on a realistic distribution feeder shows the
effectiveness of a receding-horizon implementation.


  Two-dimensional conformal field theory (CFT) has several sources: the search
for simple examples of quantum field theory, the description of surface
critical phenomena, the study of (super)string vacua. In the present overview
of the subject we emphasize the role of CFT in bridging the gap between
mathematics and quantum field theory and discuss some new physical concepts
that emerged in the study of CFT models: anomalous dimensions, rational CFT,
braid group statistics. In an aside, at the end of the paper, we share the
misgivings, recently expressed by Penrose, about some dominant trends in
fundamental theoretical physics.


  Consider the Chern-Simons topological quantum field theory with gauge group
SU(2) and level k. Given a knot in the 3-sphere, this theory associates to the
knot exterior an element in a vector space. We call this vector the knot state
and study its asymptotic properties when the level is large. The latter vector
space being isomorphic to the geometric quantization of the SU(2)-character
variety of the peripheral torus, the knot state may be viewed as a section
defined over this character variety. We first conjecture that the knot state
concentrates in the large level limit to the character variety of the knot.
This statement may be viewed as a real and smooth version of the AJ conjecture.
Our second conjecture says that the knot state in the neighborhood of abelian
representations is a Lagrangian state. Using microlocal techniques, we prove
these conjectures for the figure eight and torus knots. The proof is based on
q-difference relations for the colored Jones polynomial. We also provide a new
proof for the asymptotics of the Witten-Reshetikhin-Turaev invariant of the
lens spaces and a derivation of the Melvin-Morton-Rozansky theorem from the two
conjectures.


  This paper introduces Surgical Data Science as an emerging scientific
discipline. Key perspectives are based on discussions during an intensive
two-day international interactive workshop that brought together leading
researchers working in the related field of computer and robot assisted
interventions. Our consensus opinion is that increasing access to large amounts
of complex data, at scale, throughout the patient care process, complemented by
advances in data science and machine learning techniques, has set the stage for
a new generation of analytics that will support decision-making and quality
improvement in interventional medicine. In this article, we provide a consensus
definition for Surgical Data Science, identify associated challenges and
opportunities and provide a roadmap for advancing the field.


  Future wireless systems are trending towards higher carrier frequencies that
offer larger communication bandwidth but necessitate the use of large antenna
arrays. Existing signal processing techniques for channel estimation do not
scale well to this "high-dimensional" regime in terms of performance and pilot
overhead. Meanwhile, training deep learning based approaches for channel
estimation requires large labeled datasets mapping pilot measurements to clean
channel realizations, which can only be generated offline using simulated
channels. In this paper, we develop a novel unsupervised over-the-air (OTA)
algorithm that utilizes noisy received pilot measurements to train a deep
generative model to output beamspace MIMO channel realizations. Our approach
leverages Generative Adversarial Networks (GAN), while using a conditional
input to distinguish between Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS)
channel realizations. We also present a federated implementation of the OTA
algorithm that distributes the GAN training over multiple users and greatly
reduces the user side computation. We then formulate channel estimation from a
limited number of pilot measurements as an inverse problem and reconstruct the
channel by optimizing the input vector of the trained generative model. Our
proposed approach significantly outperforms Orthogonal Matching Pursuit on both
LOS and NLOS channel models, and EM-GM-AMP -- an Approximate Message Passing
algorithm -- on LOS channel models, while achieving comparable performance on
NLOS channel models in terms of the normalized channel reconstruction error.
More importantly, our proposed framework has the potential to be trained online
using real noisy pilot measurements, is not restricted to a specific channel
model and can even be utilized for a federated OTA design of a dataset
generator from noisy data.


  We investigate the prospect of detecting the Dark Matter (DM) candidate in
the three-loop radiative neutrino mass generation model extended with large
electroweak multiplets of the Standard Model (SM) gauge group, at the future
imaging atmospheric Cherenkov telescope known as the Cherenkov Telescope Array
(CTA). We find that the addition of such large electroweak multiplets leads to
a sizable Sommerfeld enhanced annihilation of the DM with $O(\text{TeV})$ mass,
into the SM gauge bosons which results in continuum and line-like spectra of
very high energy (VHE) gamma-rays, and therefore becomes observable for the
CTA. We determine the viable models by setting the upper limit on the
$SU(2)_{L}$ isospin of the multiplets from the partial-wave unitarity
constraints and the appearance of low-scale Landau pole in the gauge coupling.
Afterwards, by considering the continuum VHE gamma-rays produced from the DM
annihilation at the Galactic center, we probe the parameter space of the model
using the sensitivity reach of the CTA.


  The band structure calculations in the GGA+U approximation show the presence
of additional lattice distortions in the magnetically ordered phase of
AgCrS$_2$. The magnetostriction leads to formation of the long and short Cr-Cr
bonds in the case when respective Cr ions have the same or opposite spin
projections. These changes of the Cr lattice are accompanied by distortions of
the CrS$_6$ octahedra, which in its turn leads to development of the
spontaneous electric polarization.


  We propose an explanation of the peculiar linear temperature dependence of
the uniform spin susceptibility $\chi(T)$ in ferropnictides. We argue that the
linear in $T$ term appears due to non-analytic temperature dependence of
$\chi(T)$ in a two-dimensional Fermi liquid. We show that the prefactor of the
$T$ term is expressed via the square of the spin-density-wave (SDW) amplitude
connecting nested hole and electron pockets. Due to an incipient SDW
instability, this amplitude is large, which, along with a small value of the
Fermi energy, makes the $T$ dependence of $\chi(T)$ strong. We demonstrate that
this mechanism is in quantitative agreement with the experiment.


  We discuss two topics that we have encountered in our lattice-Boltzmann
simulations of complex fluids: the sizes of droplets in particle-stabilised
emulsions and deformable particles in fluid flow. The common factor in these
seemingly disparate subjects is that both represent an opportunity for a novel
application of the Hoshen-Kopelman algorithm. This algorithm is based on
detecting connected clusters on a lattice and labelling the involved lattice
sites such that all sites that are connected share the same label. The
assumption of the presence of a lattice makes it a convenient algorithm to use
in combination with lattice-Boltzmann simulations. In order to apply this
algorithm on the fly during massively parallel simulations, it needs to be
parallelised as well. We present our parallel implementation, which is tailored
to a common parallelisation scheme for the lattice-Boltzmann method, and
compare it to previous work. We then briefly discuss some examples of results
obtained using this procedure.


  In reinforcement learning (RL), function approximation errors are known to
easily lead to the Q-value overestimations, thus greatly reducing policy
performance. This paper presents a distributional soft actor-critic (DSAC)
algorithm, which is an off-policy RL method for continuous control setting, to
improve the policy performance by mitigating Q-value overestimations. We first
discover in theory that learning a distribution function of state-action
returns can effectively mitigate Q-value overestimations because it is capable
of adaptively adjusting the update stepsize of the Q-value function. Then, a
distributional soft policy iteration (DSPI) framework is developed by embedding
the return distribution function into maximum entropy RL. Finally, we present a
deep off-policy actor-critic variant of DSPI, called DSAC, which directly
learns a continuous return distribution by keeping the variance of the
state-action returns within a reasonable range to address exploding and
vanishing gradient problems. We evaluate DSAC on the suite of MuJoCo continuous
control tasks, achieving the state-of-the-art performance.


  For decades, a variety of predictive approaches have been proposed and
evaluated in terms of their prediction capability for Alzheimer's Disease (AD)
and its precursor - mild cognitive impairment (MCI). Most of them focused on
prediction or identification of statistical differences among different
clinical groups or phases (e.g., longitudinal studies). The continuous nature
of AD development and transition states between successive AD related stages
have been overlooked, especially in binary or multi-class classification.
Though a few progression models of AD have been studied recently, they were
mainly designed to determine and compare the order of specific biomarkers. How
to effectively predict the individual patient's status within a wide spectrum
of continuous AD progression has been largely overlooked. In this work, we
developed a novel learning-based embedding framework to encode the intrinsic
relations among AD related clinical stages by a set of meaningful embedding
vectors in the latent space (Disease2Vec). We named this process as disease
embedding. By disease em-bedding, the framework generates a disease embedding
tree (DETree) which effectively represents different clinical stages as a tree
trajectory reflecting AD progression and thus can be used to predict clinical
status by projecting individuals onto this continuous trajectory. Through this
model, DETree can not only perform efficient and accurate prediction for
patients at any stages of AD development (across five clinical groups instead
of typical two groups), but also provide richer status information by examining
the projecting locations within a wide and continuous AD progression process.


  In the evolving landscape of Neural Machine Translation (NMT), the
pretrain-then-finetune paradigm has yielded impressive results. However, the
persistent challenge of Catastrophic Forgetting (CF) remains a hurdle. While
previous work has introduced Continual Learning (CL) methods to address CF,
these approaches grapple with the delicate balance between avoiding forgetting
and maintaining system extensibility. To address this, we propose a CL method,
named $\textbf{F-MALLOC}$ ($\textbf{F}$eed-forward $\textbf{M}$emory
$\textbf{ALLOC}ation)$. F-MALLOC is inspired by recent insights highlighting
that feed-forward layers emulate neural memories and encapsulate crucial
translation knowledge. It decomposes feed-forward layers into discrete memory
cells and allocates these memories to different tasks. By learning to allocate
and safeguard these memories, our method effectively alleviates CF while
ensuring robust extendability. Besides, we propose a comprehensive assessment
protocol for multi-stage CL of NMT systems. Experiments conducted following
this new protocol showcase the superior performance of F-MALLOC, evidenced by
higher BLEU scores and almost zero forgetting.


  We study the photoproduction of the $N(1440)$ resonance in $\gamma^*p\to N^*$
process in quark models, where the $N(1440)$ takes different wave functions:
first radial excitation of the nucleon imported from low-lying baryon mass
spectrum calculations, a general radial excitation of the nucleon, and a $q^3$
state with positive parity. The comparison between the theoretical results and
experimental data on the helicity amplitudes $A_{1/2}$ and $S_{1/2}$ and the
analysis of the spatial wave function of the $N(1440)$ resonance reveal that
the $N(1440)$ resonance is mainly the $q^3$ first radial excitation.


  In this paper, we establish novel deviation bounds for additive functionals
of geometrically ergodic Markov chains similar to Rosenthal and Bernstein
inequalities for sums of independent random variables. We pay special attention
to the dependence of our bounds on the mixing time of the corresponding chain.
More precisely, we establish explicit bounds that are linked to the constants
from the martingale version of the Rosenthal inequality, as well as the
constants that characterize the mixing properties of the underlying Markov
kernel. Finally, our proof technique is, up to our knowledge, new and based on
a recurrent application of the Poisson decomposition.