  We model the essential features of eternal inflation on the landscape of a
dense discretuum of vacua by the potential $V(\phi)=V_{0}+\delta V(\phi)$,
where $|\delta V(\phi)|\ll V_{0}$ is random. We find that the diffusion of the
distribution function $\rho(\phi,t)$ of the inflaton expectation value in
different Hubble patches may be suppressed due to the effect analogous to the
Anderson localization in disordered quantum systems. At $t \to \infty$ only the
localized part of the distribution function $\rho (\phi, t)$ survives which
leads to dynamical selection principle on the landscape. The probability to
measure any but a small value of the cosmological constant in a given Hubble
patch on the landscape is exponentially suppressed at $t\to \infty$.


  When working with algorithms on quantum devices, quantum memory becomes a
crucial bottleneck due to low qubit count in NISQ-era devices. In this context,
the concept of `divide and compute', wherein a quantum circuit is broken into
several subcircuits and executed separately, while stitching the results of the
circuits via classical post-processing, becomes a viable option, especially in
NISQ-era devices. This paper introduces \textbf{Qurzon}, a proposed novel
quantum compiler that incorporates the marriage of techniques of divide and
compute with the state-of-the-art algorithms of optimal qubit placement for
executing on real quantum devices. A scheduling algorithm is also introduced
within the compiler that can explore the power of distributed quantum computing
while paving the way for quantum parallelism for large algorithms. Several
benchmark circuits have been executed using the compiler, thereby demonstrating
the power of the divide and compute when working with real NISQ-era quantum
devices.


  Despite much experimental and theoretical work, the nature of the charge
order in the kagome metals belonging to the family of materials AV$_3$Sb$_5$
(A=Cs,Rb,K) remains controversial. A crucial ingredient for the identification
of the ordering in these materials is their response to external perturbations,
such as strain or magnetic fields. To this end, we provide a comprehensive
symmetry classification of the possible charge orders in kagome materials with
a $2\times2$ increase of the unit cell. Motivated by the experimental reports
of time-reversal-symmetry breaking and rotational anisotropy, we consider the
interdependence of flux and bond orders. Deriving the relevant Landau free
energy for possible orders, we study the effect of symmetry-breaking
perturbations such as strain and magnetic fields. Our results, thus, provide a
roadmap for future tests of these intricate orders.


  We outline how relic neutrino asymmetries may be generated in the early
universe via active-sterile neutrino oscillations. We discuss possible
consequences for big bang nucleosynthesis, within the context of a particular
4-neutrino model.


  The Hitomi X-ray satellite mission carried unique high-resolution
spectrometers that were set to revolutionize the search for sterile neutrino
dark matter (DM) by looking for narrow X-ray lines arising from DM decays.
Unfortunately, the satellite was lost shortly after launch, and to-date the
only analysis using Hitomi for DM decay used data taken towards the Perseus
cluster. In this work we present a significantly more sensitive search from an
analysis of archival Hitomi data towards blank sky locations, searching for DM
decaying in our own Milky Way. The soon-to-be-launched XRISM satellite will
have nearly identical soft-X-ray spectral capabilities to Hitomi; we project
the full-mission sensitivity of XRISM for analyses of their future blank-sky
data, and we find that XRISM will have the leading sensitivity to decaying DM
for masses between roughly 1 to 20 keV, with important implications for sterile
neutrino and heavy axion-like particle DM scenarios.


  Photoproduction of the $\omega$ meson on the proton has been experimentally
studied near the threshold. The total cross sections are determined at incident
energies ranging from 1.09 to 1.15 GeV. The 1/2 and 3/2 spin-averaged
scattering length $a_{\omega p}$ and effective range $r_{\omega p}$ between the
$\omega$ meson and proton are estimated from the shape of the total cross
section as a function of the incident photon energy: $a_{\omega p} =
\left(-0.97^{+0.16_{\rm stat}}_{-0.16_{\rm stat}}{}^{+0.03_{\rm
syst}}_{-0.00_{\rm syst}}\right)+i \left(0.07^{+0.15_{\rm stat}}_{-0.14_{\rm
stat}}{}^{+0.17_{\rm syst}}_{-0.09_{\rm syst}}\right)$ fm and $r_{\omega
p}=\left(+2.78^{+0.68_{\rm stat}}_{-0.54_{\rm stat}}{}^{+0.11_{\rm
syst}}_{-0.13_{\rm syst}}\right)+i\left(-0.01^{+0.46_{\rm stat}}_{-0.50_{\rm
stat}}{}^{+0.07_{\rm syst}}_{-0.00_{\rm syst}}\right)$ fm, resulting in a
repulsive force. The real and imaginary parts for $a_{\omega p}$ and $r_{\omega
p}$ are determined separately for the first time. A small $P$-wave contribution
does not affect the obtained values.


  In this work, we explore wormhole geometries in a recently proposed modified
gravity theory arising from a non-conservative gravitational theory,
tentatively denoted action-dependent Lagrangian theories. The generalized
gravitational field equation essentially depends on a background four-vector
$\lambda^\mu$, that plays the role of a coupling parameter associated with the
dependence of the gravitational Lagrangian upon the action, and may generically
depend on the spacetime coordinates. Considering wormhole configurations, by
using "Buchdahl coordinates", we find that the four-vector is given by
$\lambda_{\mu}=\left(0,0,\lambda_{\theta},0\right)$, and that the spacetime
geometry is severely restricted by the condition $g_{tt}g_{uu}=-1$, where $u$
is the radial coordinate. We find a plethora of specific asymptotically flat,
symmetric and asymmetric, solutions with power law choices for the function
$\lambda$, by generalizing the Ellis-Bronnikov solutions and the recently
proposed black bounce geometries, amongst others. We show that these compact
objects possess a far richer geometrical structure than their general
relativistic counterparts.


  We generalize the control power of a perfect controlled teleportation of an
entangled three-qubit pure state, suggested by Li and Ghose [Phys. Rev. A {\bf
90}, 052305 (2014)], to the control power of a general controlled teleportation
of a multiqubit pure state. Thus, we define the minimal control power, and
calculate the values of the minimal control power for a class of general
three-qubit Greenberger-Horne-Zeilinger (GHZ) states and the three-qubit W
class whose states have zero three-tangles. Moreover, we show that the standard
three-qubit GHZ state and the standard three-qubit W state have the maximal
values of the minimal control power for the two classes, respectively. This
means that the minimal control power can be interpreted as not only an
operational quantity of a three-qubit quantum communication but also a degree
of three-qubit entanglement. In addition, we calculate the values of the
minimal control power for general n-qubit GHZ states and the n-qubit W-type
states.


  In this paper, we present an efficient method for storing fine-tuned models
by leveraging the low-rank properties of weight residuals. Our key observation
is that weight residuals in large overparameterized models exhibit even
stronger low-rank characteristics. Based on this insight, we propose Efficient
Residual Encoding (ERE), a novel approach that achieves efficient storage of
fine-tuned model weights by approximating the low-rank weight residuals.
Furthermore, we analyze the robustness of weight residuals and push the limit
of storage efficiency by utilizing additional quantization and layer-wise rank
allocation. Our experimental results demonstrate that our method significantly
reduces memory footprint while preserving performance in various tasks and
modalities. We release our code.


  H$\alpha$ emission is a clear indicator of circumstellar activity in Be
stars, historically employed to assess the classical Be star (CBe) population
in young open clusters (YOCs). The YOC NGC330 in the Small Magellanic Cloud
exhibits a large known fraction of {CBe} stars and was selected for a pilot
study to establish a comprehensive methodology for identifying H$\alpha$
emitters in the Magellanic Clouds, encompassing the entire B-type spectral
range. Using the SOAR Adaptative Module Imager (SAMI), we investigated the
stellar population of NGC330 using multi-band BVRI+H$\alpha$ imaging. We
identified H$\alpha$ emitters within the entire V-band range covered by
SAMI/SOAR observations ($V\lesssim22$), comprising the complete B-type stellar
population and offering a unique opportunity to explore the Be phenomenon
across all spectral sub-classes. The stellar radial distribution shows a clear
bimodal pattern between the most massive (B5 or earlier) and the lower-mass
main-sequence objects (later than B6) within the cluster. The former is
concentrated towards the cluster center (showing a dispersion of
$\sigma=4.26\pm0.20$ pc), whereas the latter extends across larger radii
($\sigma=10.83\pm0.65$ pc), indicating mass stratification within NGC330. The
total fraction of emitters is $4.4\pm0.5\%$, notably smaller than previous
estimates from flux- or seeing-limited observations. However, a higher fraction
of H$\alpha$ emitters is observed among higher-mass stars ($32.8\pm3.4\%$) than
within lower-mass ($4.4\pm0.9\%$). Consequently, the putative CBe population
exhibits distinct dynamical characteristics compared to the bulk of the stellar
population in NGC330. These findings highlight the significance of the current
observations in providing a complete picture of the CBe population in NGC330.


  We analyze the magnetic excitations and the spin-mediated superconductivity
in iron-based superconductors within a low-energy model that operates in the
band basis but fully incorporates the orbital character of the spin
excitations. We show how the orbital selectivity, encoded in our low-energy
description, simplifies substantially the analysis and allows for analytical
treatments, while retaining all the main features of both spin-excitations and
gap functions computed using multiorbital models. Importantly, our analysis
unveils the orbital matching between the hole and electron pockets as the key
parameter to determine the momentum-dependence and the hierarchy of the
superconducting gaps, instead of the Fermi surface matching as in the common
nesting scenario.


  We study one-flavor QCD at finite temperature and chemical potential using
the functional renormalization group. We discuss the chiral phase transition in
QCD and its order with its underlying mechanism in terms of quarks and gluons
and analyze the dependence of the phase transition temperature on small quark
chemical potentials. Our result for the curvature of the phase boundary at
small quark chemical potential relies on only a single input parameter, the
value of the strong coupling at the Z mass scale.


  In this paper we present a SOA (Service Oriented Architecture)-based
platform, enabling the retrieval and analysis of big datasets stemming from
social networking (SN) sites and Internet of Things (IoT) devices, collected by
smart city applications and socially-aware data aggregation services. A large
set of city applications in the areas of Participating Urbanism, Augmented
Reality and Sound-Mapping throughout participating cities is being applied,
resulting into produced sets of millions of user-generated events and online SN
reports fed into the RADICAL platform. Moreover, we study the application of
data analytics such as sentiment analysis to the combined IoT and SN data saved
into an SQL database, further investigating algorithmic and configurations to
minimize delays in dataset processing and results retrieval.


  We investigate phenomenological implications of a supersymmetric left-right
model based on $SU(2)_L\times SU(2)_R\times U(1)_{B-L}\,$ gauge symmetry
testable in the next generation linear colliders. We concentrate in particular
on the doubly charged $SU(2)_R$ triplet higgsino $\tilde\Delta$, which we find
very suitable for experimental search. We estimate its production rate in
$e^+e^-$, $e^-e^-$, $e^-\gamma$ and $\gamma\gamma$ collisions and consider its
subsequent decays. These processes have a clear discovery signature with a very
low background from other processes.


  We provide necessary and sufficient conditions for operator-valued functions
on arbitrary sets associated with a collection of test functions to have
factorizations in several situations.


  The difference tensor R.C-C.R of a semi-Riemannian manifold (M,g), dim M > 3,
formed by its Riemannian-Christoffel curvature tensor R and the Weyl conformal
curvature tensor C, under some assumptions, can be expressed as a linear
combination of (0,6)-Tachibana tensors Q(A,T), where A is a symmetric
(0,2)-tensor and T a generalized curvature tensor. These conditions form a
family of generalized Einstein metric conditions. In this survey paper we
present recent results on manifolds and submanifolds, and in particular
hypersurfaces, satisfying such conditions.


  The use of empirical characteristic functions for inference problems,
including estimation in some special parametric settings and testing for
goodness of fit, has a long history dating back to the 70s (see for example,
Feuerverger and Mureika (1977), Csorgo (1981a,1981b,1981c), Feuerverger
(1993)). More recently, there has been renewed interest in using empirical
characteristic functions in other inference settings. The distance covariance
and correlation, developed by Szekely and Rizzo (2009) for measuring dependence
and testing independence between two random vectors, are perhaps the best known
illustrations of this. We apply these ideas to stationary univariate and
multivariate time series to measure lagged auto- and cross-dependence in a time
series. Assuming strong mixing, we establish the relevant asymptotic theory for
the sample auto- and cross-distance correlation functions. We also apply the
auto-distance correlation function (ADCF) to the residuals of an autoregressive
processes as a test of goodness of fit. Under the null that an autoregressive
model is true, the limit distribution of the empirical ADCF can differ markedly
from the corresponding one based on an iid sequence. We illustrate the use of
the empirical auto- and cross-distance correlation functions for testing
dependence and cross-dependence of time series in a variety of different
contexts.


  We explore and contrast the single-photon and diphoton signals expected at
LEP 2, that arise from neutralino-gravitino (e^+ e^- -> chi + gravitino ->
gamma + E_miss) and neutralino-neutralino (e^+ e^- -> chi + chi -> gamma +
gamma + E_miss) production in supersymmetric models with a light gravitino. LEP
1 limits imply that one may observe either one, but not both, of these signals
at LEP 2, depending on the values of the neutralino and gravitino masses:
single-photons for m_chi > Mz and m_gravitino < 3 x 10^-5 eV; diphotons for
m_chi < Mz and all allowed values of m_gravitino.


  As the Internet of Things (IoT) becomes a part of our daily life, there is a
rapid growth in connected devices. A well-established approach based on cloud
computing technologies cannot provide the necessary quality of service in such
an environment, particularly in terms of reducing data latency. Today, fog
computing technology is seen as a novel approach for processing large amounts
of critical and time-sensitive data. This article reviews cloud computing
technology and analyzes the prerequisites for the evolution of this approach
and the emergence of the concept of fog computing. As part of an overview of
the critical features of fog computing, we analyze the frequent confusion of
the concepts of fog and edge computing. We provide an overview of fog computing
technologies: virtualization, containerization, orchestration, scalability,
parallel computing environments, as well as a systematic analysis of the most
popular platforms that support fog computing. As a result of the analysis, we
offer two approaches to classification of the fog computing platforms: by the
principle of openness/closure of components and a three-level classification
based on the provided platform functionality (Deploy-, Platform- and Ecosystem
as a Service).


  The mass shift and width broadening of $\rho$-mesons produced in heavy ion
collisions is estimated. It is found that the mass increases by some tens of
MeV but the width becomes large, increasing by 200 MeV at beam energies of a
few GeV$\cdot$A and by twice that amount at beam energies of about a hundred
GeV$\cdot$A.


  Star-join query is the fundamental task in data warehouse and has wide
applications in On-line Analytical Processing (OLAP) scenarios. Due to the
large number of foreign key constraints and the asymmetric effect in the
neighboring instance between the fact and dimension tables, even those latest
DP efforts specifically designed for join, if directly applied to star-join
query, will suffer from extremely large estimation errors and expensive
computational cost. In this paper, we are thus motivated to propose DP-starJ, a
novel Differentially Private framework for star-Join queries. DP-starJ consists
of a series of strategies tailored to specific features of star-join, including
1) we unveil the different effect of fact and dimension tables on the
neighboring database instances, and accordingly revisit the definitions
tailored to different cases of star-join; 2) we propose Predicate Mechanism
(PM), which utilizes predicate perturbation to inject noise into the join
procedure instead of the results; 3) to further boost the robust performance,
we propose a DP-compliant star-join algorithm for various types of star-join
tasks based on PM. We provide both theoretical analysis and empirical study,
which demonstrate the superiority of the proposed methods over the
state-of-the-art solutions in terms of accuracy, efficiency, and scalability.


  We find a formula for the number of solutions of linear congruence systems,
by using elementary methods.


  In practice, deeper networks tend to be more powerful than shallow ones, but
this has not been understood theoretically. In this paper, we find the
analytical solution of a three-layer network with a matrix exponential
activation function, i.e., $$ f(X)=W_3\exp(W_2\exp(W_1X)), X\in
\mathbb{C}^{d\times d} $$ have analytical solutions for the equations $$
  Y_1=f(X_1),Y_2=f(X_2) $$ for $X_1,X_2,Y_1,Y_2$ with only invertible
assumptions. Our proof shows the power of depth and the use of a non-linear
activation function, since one layer network can only solve one
equation,i.e.,$Y=WX$.


  Consider the random graph on $n$ vertices $1, ..., n$. Each vertex $i$ is
assigned a type $X_i$ with $X_1, ..., X_n$ being independent identically
distributed as a nonnegative discrete random variable $X$. We assume that ${\bf
E} X^3<\infty$. Given types of all vertices, an edge exists between vertices
$i$ and $j$ independent of anything else and with probability $\min \{1,
\frac{X_iX_j}{n}(1+\frac{a}{n^{1/3}}) \}$. We study the critical phase, which
is known to take place when ${\bf E} X^2=1$. We prove that normalized by
$n^{-2/3}$ the asymptotic joint distributions of component sizes of the graph
equals the joint distribution of the excursions of a reflecting Brownian motion
$B^a(s)$ with diffusion coefficient $\sqrt{{\bf E}X{\bf E}X^3}$ and drift
$a-\frac{{\bf E}X^3}{{\bf E}X}s$. This shows that finiteness of ${\bf E}X^3$ is
the necessary condition for the diffusion limit. In particular, we conclude
that the size of the largest connected component is of order $n^{2/3}$.


  Physical parameters characterising electrokinetic transport in a confined
electrolyte solution are reconstructed from the generic transport coefficients
obtained within the classical non-equilibrium statistical thermodynamic
framework. The electro-osmotic flow, the diffusio-osmotic flow, the osmotic
current, as well as the pressure-driven Poiseuille-type flow, the electric
conduction, and the ion diffusion, are described by this set of transport
coefficients. The reconstruction is demonstrated for an aqueous NaCl solution
between two parallel charged surfaces with a nanoscale gap, by using the
molecular dynamic (MD) simulations. A Green-Kubo approach is employed to
evaluate the transport coefficients in the linear-response regime, and the
fluxes induced by the pressure, electric, and chemical potential fields are
compared with the results of non-equilibrium MD simulations. Using this
numerical scheme, the influence of the salt concentration on the transport
coefficients is investigated. Anomalous reversal of diffusio-osmotic current,
as well as that of electro-osmotic flow, is observed at high surface charge
densities and high added-salt concentrations.


  I report on recent progress in calculating electroweak processes within the
framework of QCD in the 1/Nc expansion.


  Simpson-Visser (SV) space-times are the simplest globally regular
modifications of the Schwarzschild, Reissner-Nordstrom and other blak-hole
solutions of general relativity. They smoothly interpolate between these black
holes and traversable wormholes. After a brief presentation of the
Schwarzschild-like and Reissner-Nordstrom-like SV geometries, including their
Carter-Penrose diagrams, we show that any static, spherically symmetric SV
metric can be obtained as an exact solution to the Einstein field equations
sourced by a combination of a minimally coupled phantom scalar field with a
nonzero potential $V(\phi)$ and a magnetic field in the framework of nonlinear
electrodynamics with the Lagrangian $\mathcal {L(F)}$, $\mathcal{F} =
F_{\mu\nu} F^{\mu\nu}$ (in standard notations). Explicit forms of $V(\phi)$ and
$\mathcal {L(F)}$ are presented for the cases of Schwarzschild-like and
Reissner-Nordstrom-like SV metrics.


  Recently ANTARES collaboration presented a time dependent analysis to a
selected number of flaring blazars to look for upward going muon events
produced from the charge current interaction of the muon neutrinos. We use the
same list of flaring blazars to look for possible positional correlation with
the IceCube neutrino events. In the context of photohadronic model we propose
that the neutrinos are produced within the nuclear region of the blazar where
Fermi accelerated high energy protons interact with the background
synchrotron/SSC photons. Although we found that some objects from the ANTARES
list are within the error circles of few IceCube events, the statistical
analysis shows that none of these sources have a significant correlation.


  A well-known retinal disease that sends blurry visions to the affected
patients is Macular Degeneration. This research is based on classifying the
healthy and macular degeneration fundus by localizing the affected region of
the fundus. A CNN architecture and CNN with ResNet architecture (ResNet50,
ResNet50v2, ResNet101, ResNet101v2, ResNet152, ResNet152v2) as the backbone are
used to classify the two types of fundus. The data are split into three
categories including (a) Training set is 90% and Testing set is 10% (b)
Training set is 80% and Testing set is 20%, (c) Training set is 50% and Testing
set is 50%. After the training, the best model has been selected from the
evaluation metrics. Among the models, CNN with a backbone of ResNet50 performs
best which gives the training accuracy of 98.7% for 90% train and 10% test data
split. With this model, we have performed the Grad-CAM visualization to get the
region of the affected area of the fundus.


  Bloom Filters are a space-efficient data structure used for the testing of
membership in a set that errs only in the False Positive direction. However,
the standard analysis that measures this False Positive rate provides a form of
worst case bound that is both overly conservative for the majority of network
applications that utilize Bloom Filters, and reduces accuracy by not taking
into account the actual state (number of bits set) of the Bloom Filter after
each arrival. In this paper, we more accurately characterize the False Positive
dynamics of Bloom Filters as they are commonly used in networking applications.
In particular, network applications often utilize a Bloom Filter that
"recycles": it repeatedly fills, and upon reaching a certain level of
saturation, empties and fills again. In this context, it makes more sense to
evaluate performance using the average False Positive rate instead of the worst
case bound. We show how to efficiently compute the average False Positive rate
of recycling Bloom Filter variants via renewal and Markov models. We apply our
models to both the standard Bloom Filter and a "two-phase" variant, verify the
accuracy of our model with simulations, and find that the previous analysis'
worst-case formulation leads to up to a 30\% reduction in the efficiency of
Bloom Filter when applied in network applications, while two-phase overhead
diminishes as the needed False Positive rate is tightened.


  I present results on continuing updates in PDFs within the framework now
called MMHT14 due to both theory improvements and the inclusion of new data
sets, including most of the up-to-date LHC data. A new set of PDFs is
essentially finalised, with no changes expected to the PDFs presented here.


  We propose an algorithm for solving of the graph isomorphism problem. Also,
we introduce the new class of graphs for which the graph isomorphism problem
can be solved polynomially using the algorithm.


  The use of von Neumann -- Morgenstern utility is examined in the context of
multiple choices between lotteries. Different conclusions are reached if the
choices are simultaneous or sequential. It is demonstrated that utility cannot
be additive.


  Recent studies have shown that visually impaired people have desires to take
selfies in the same way as sighted people do to record their photos and share
them with others. Although support applications using sound and vibration have
been developed to help visually impaired people take selfies using smartphone
cameras, it is still difficult to capture everyone in the angle of view, and it
is also difficult to confirm that they all have good expressions in the photo.
To mitigate these issues, we propose a method to take selfies with multiple
people using an omni-directional camera. Specifically, a user takes a few
seconds of video with an omni-directional camera, followed by face detection on
all frames. The proposed method then eliminates false face detections and
complements undetected ones considering the consistency across all frames.
After performing facial expression recognition on all the frames, the proposed
method finally extracts the frame in which the participants are happiest, and
generates a perspective projection image in which all the participants are in
the angle of view from the omni-directional frame. In experiments, we use
several scenes with different number of people taken to demonstrate the
effectiveness of the proposed method.


  We study acoustic oscillations (eigenfrequencies, velocity distributions,
damping times) of normal crusts of strange stars. These oscillations are very
specific because of huge density jump at the interface between the normal crust
and the strange matter core. The oscillation problem is shown to be
self-similar. For a low (but non-zero) multipolarity l the fundamental mode
(without radial nodes) has a frequency ~300 Hz and mostly horizontal
oscillation velocity; other pressure modes have frequencies >=20 kHz and almost
radial oscillation velocities. The latter modes are similar to radial
oscillations (have approximately the same frequencies and radial velocity
profiles). The oscillation spectrum of strange stars with crust differs from
the spectrum of neutron stars. If detected, acoustic oscillations would allow
one to discriminate between strange stars with crust and neutron stars and
constrain the mass and radius of the star.


  We study the doping evolution of the electronic structure in the normal phase
of high-$T_c$ cuprates. Electronic structure and Fermi surface of cuprates with
single CuO$_2$ layer in the unit cell like La$_{2-x}$Sr$_x$CuO$_4$ have been
calculated by the LDA+GTB method in the regime of strong electron correlations
(SEC) and compared to ARPES and quantum oscillations data. We have found two
critical concentrations, $x_{c1}$ and $x_{c2}$, where the Fermi surface
topology changes. Following I.M. Lifshitz ideas of the quantum phase
transitions (QPT) of the 2.5-order we discuss the concentration dependence of
the low temperature thermodynamics. The behavior of the electronic specific
heat $\delta(C/T) \sim (x - x_c)^{1/2}$ is similar to the Loram and Cooper
experimental data in the vicinity of $x_{c1} \approx 0.15$.


  The intrinsic anomalous Hall effect in metallic ferromagnets is shown to be
controlled by Berry phases accumulated by adiabatic motion of quasiparticles on
the Fermi surface, and is purely a Fermi-liquid property, not a ``bulk'' Fermi
sea property like Landau diamagnetism, as has been previously supposed. Berry
phases are a new topological ingredient that must be added to Landau
Fermi-liquid theory in the presence of broken inversion or time-reversal
symmetry.


  The quantum bouncer (QB) concept is a known QM textbook example of confined
particle, namely, a solution to the 1D Schroedinger equation for a linear
potential (the so-called Airy equation). It would be a great methodological
challenge to create such a QM object in laboratory. An attempt of observation
of the QB ``running'' in the horizontal direction was recently made by the
international team at the Laue-Langevin Institute, Grenoble. The experiment was
performed with ultra-cold neutrons. In this paper, the experiment is analyzed
in view of the authors' claim that ``neutron quantum states in Earth
gravitational field'' are observed. The experimental apparatus is designed for
measurements of horizontal flux of neutrons passing through an absorbing wave
guide with a variable height of absorber. From our analysis, it follows,
however, that in such a layout measured data are not sensitive to quantum
probability density in the vertical direction. The overall conclusion is made
that the experimental data do not contain sufficient information to justify the
claim.


  In one-dimensional unbounded domains, we consider the equations of a planar
compressible magnetohydrodynamic (MHD) flow with constant viscosity and heat
conductivity. More precisely, we prove the global existence of strong solutions
to the MHD equations with large initial data satisfying the same conditions as
those of Kazhikhov's theory in bounded domains (Kazhikhov 1987 Boundary Value
Problems for Equations of Mathematical Physics (Krasnoyarsk)). In particular,
our result generalizes the Kazhikhov's theory for the initial boundary value
problem in bounded domains to the unbounded case.


  Recently, Wallentowitz and Toschek [Phys. Rev. A 69, 046101 (2005)]
criticized the assertion made by Hotta and Morikawa [Phys. Rev. A 69, 052114
(2004)] that distant indirect measurements do not cause the quantum Zeno
effect, and claimed that their proof is faulty and that their claim is
unfounded. Here, it is shown that the argument given by Wallentowitz and
Toschek includes a mathematical flaw and that their criticism is unfounded.


  We first review the results of the tidal stirring model for the
transformation of gas-rich dwarf irregulars into dwarf spheroidals, which turns
rotationally supported stellar systems into pressure supported ones. We
emphasize the importance of the combined effect of ram pressure stripping and
heating from the cosmic ultraviolet background in removing the gas and
converting the object into a gas poor system as dSphs. We discuss how the
timing of infall of dwarfs into the primary halo determines the final
mass-to-light ratio and star formation history. Secondly we review the results
of recent cosmological simulations of the formation of gas-rich dwarfs. These
simulations are finally capable to produce a realistic object with no bulge, an
exponential profile and a slowly rising rotation curve. The result owes to the
inclusion of an inhomogeneous ISM and a star formation scheme based on regions
having the typical density of molecular cloud complexes. Supernovae-driven
winds become more effective in such mode, driving low angular momentum baryons
outside the virial radius at high redshift and turning the dark matter cusp
into a core. Finally we show the first tidal stirring experiments adopting
dwarfs formed in cosmological simulations as initial conditions. The latter are
gas dominated and have have turbulent thick gaseous and stellar disks disks
that cannot develop strong bars, yet they are efficiently heated into spheroids
by tidal shocks.


  Evaluating Large Language Models (LLMs) is challenging due to their
generative nature, necessitating precise evaluation methodologies.
Additionally, non-English LLM evaluation lags behind English, resulting in the
absence or weakness of LLMs for many languages. In response to this necessity,
we introduce Khayyam Challenge (also known as PersianMMLU), a meticulously
curated collection comprising 20,192 four-choice questions sourced from 38
diverse tasks extracted from Persian examinations, spanning a wide spectrum of
subjects, complexities, and ages. The primary objective of the Khayyam
Challenge is to facilitate the rigorous evaluation of LLMs that support the
Persian language. Distinctive features of the Khayyam Challenge are (i) its
comprehensive coverage of various topics, including literary comprehension,
mathematics, sciences, logic, intelligence testing, etc., aimed at assessing
different facets of LLMs such as language comprehension, reasoning, and
information retrieval across various educational stages, from lower primary
school to upper secondary school (ii) its inclusion of rich metadata such as
human response rates, difficulty levels, and descriptive answers (iii) its
utilization of new data to avoid data contamination issues prevalent in
existing frameworks (iv) its use of original, non-translated data tailored for
Persian speakers, ensuring the framework is free from translation challenges
and errors while encompassing cultural nuances (v) its inherent scalability for
future data updates and evaluations without requiring special human effort.
Previous works lacked an evaluation framework that combined all of these
features into a single comprehensive benchmark. Furthermore, we evaluate a wide
range of existing LLMs that support the Persian language, with statistical
analyses and interpretations of their outputs.


  We define and fully characterize the witnesses based on second moments
detecting steering in Gaussian states by means of Gaussian measurements. All
such tests, which arise from linear combination of variances or second moments
of canonical operators, are easily implemented in experiments. We propose also
a set of linear constraints fully characterizing steering witnesses when the
steered party has one bosonic mode, while in the general case the constraints
restrict the set of tests detecting steering. Given an unknown quantum state we
implement a semidefinite program providing the appropriate steering test with
respect to the number of random measurements performed. Thus, it is a
"repeat-until-success" method allowing for steering detection with less
measurements than in full tomography. We study the efficiency of steering
detection for two-mode squeezed vacuum states, for two-mode general unknown
states, and for three-mode continuous variable GHZ states. In addition, we
discuss the robustness of this method to statistical errors.


  We have determined the distance to M33 using the tip of the red giant branch
(TRGB) and the red clump (RC), from the VI photometry of stars in ten regions
of M33 based on HST/WFPC2 images. The regions used in this study are located at
R=2.6 - 17.8 arcmin from the center of M33. The distance modulus to M33
obtained in this study, for an adopted foreground reddening of E(B-V)=0.04, is
(m-M)_{0,TRGB}=24.81+/-0.04(random)+0.15/-0.11(systematic) from the TRGB, and
(m-M)_{0,RC}=24.80+/-0.04(random)+/-0.05(systematic) from the RC, showing an
excellent agreement between the two (corresponding to a distance of
916+/-17(random) kpc and 912+/-17(random) kpc, respectively). These results are
\~0.3 mag larger than the Cepheid distances based on the same HST/WFPC2 data
and ground-based data. This difference is considered partially due to the
uncertainty in the estimates of the total reddening for Cepheids in M33.


  The versatility of Large Language Models (LLMs) on natural language
understanding tasks has made them popular for research in social sciences. To
properly understand the properties and innate personas of LLMs, researchers
have performed studies that involve using prompts in the form of questions that
ask LLMs about particular opinions. In this study, we take a cautionary step
back and examine whether the current format of prompting LLMs elicits responses
in a consistent and robust manner. We first construct a dataset that contains
693 questions encompassing 39 different instruments of persona measurement on
115 persona axes. Additionally, we design a set of prompts containing minor
variations and examine LLMs' capabilities to generate answers, as well as
prompt variations to examine their consistency with respect to content-level
variations such as switching the order of response options or negating the
statement. Our experiments on 17 different LLMs reveal that even simple
perturbations significantly downgrade a model's question-answering ability, and
that most LLMs have low negation consistency. Our results suggest that the
currently widespread practice of prompting is insufficient to accurately and
reliably capture model perceptions, and we therefore discuss potential
alternatives to improve these issues.


  We performed pairwise comparisons by human raters of JPEG images from
MozJPEG, libjpeg-turbo and our new Jpegli encoder. When compressing images at a
quality similar to libjpeg-turbo quality 95, the Jpegli images were 54% likely
to be preferred over both libjpeg-turbo and MozJPEG images, but used only 2.8
bits per pixel compared to libjpeg-turbo and MozJPEG that used 3.8 and 3.5 bits
per pixel respectively. The raw ratings and source images are publicly
available for further analysis and study.


  The quark diffusion coefficient in the critical window near $T_c$ and at
moderate values of the chemical potential is evaluated.


  The axion solution to the strong CP problem makes use of a global
Peccei-Quinn (PQ) U(1) symmetry which is susceptible to violations from quantum
gravitational effects. We show explicitly how discrete gauge symmetries can
protect the axion from such violations. PQ symmetry emerges as an accidental
global symmetry from discrete gauge symmetries which are subgroups of the
anomalous U(1) of string origin. We also show how the
Dine-Fischler-Srednicki-Zhitnitsky (DFSZ) axion model provides a natural
solution to mu problem of supersymmetry as mu ~ M_{SUSY} ~ M^2_{PQ}/M_{Pl}.


  We obtain the inequality $$\int_{\Omega}|\nabla u(x)|^ph(u(x))dx\leq
C(n,p)\int_{\Omega} \left( \sqrt{ |\nabla^{(2)} u(x)||{\cal
T}_{h,C}(u(x))|}\right)^{p}h(u(x))dx,$$ where $\Omega\subseteq {\bf R}^n$ and
$n\ge 2$, $u:\Omega\rightarrow {\bf R}$ is in certain subset in second order
Sobolev space $W^{2,1}_{loc}(\Omega)$, $\nabla^{(2)} u$ is the Hessian matrix
of $u$, ${\cal T}_{h,C}(u)$ is certain transformation of the continuous
function $h(\cdot)$. Such inequality is the generalization of similar
inequality holding in one dimension, obtained earlier by second author and
Peszek.


  Assuming the availability of a reliable aircraft trajectory planner, this
paper presents a probabilistic methodology to detect conflicts between
aircraft, in the cruise phase of the flight, in the presence of wind prediction
uncertainties quantified by ensemble weather forecasts, which are regarded as
realizations of correlated random processes and employed to derive the eastward
and northward components of the wind velocity. First, the Karhunen-Lo`eve
expansion is used to obtain a series expansion of the wind components in terms
of a set of uncorrelated random variables and deterministic coefficients. Then,
the uncertainty induced by these uncorrelated random variables in the outputs
of the aircraft trajectory planner is quantified by means of the arbitrary
polynomial chaos technique. Finally, the probability density function of the
great circle distance between each pair of aircraft is derived from the
polynomial expansions using a Gaussian kernel density estimator and employed to
estimate the probability of conflict. The arbitrary polynomial chaos technique
allows the effects of uncertainties in complex nonlinear dynamical system, such
as those underlying aircraft trajectory planners, to be quantified with high
computational efficiency, only requiring the existence of a finite number of
statistical moments of the random variables of the Karhunen-Lo`eve expansion,
while avoiding any assumption on their probability distributions. In order to
demonstrate the effectiveness of the proposed conflict detection method,
numerical experiments are conducted through an optimal control based aircraft
trajectory planner for a given wind forecast represented by an ensemble
prediction system.


  We use simplicial complexes to model weighted voting games where certain
coalitions are considered unlikely or impossible. Expressions for Banzhaf and
Shapley-Shubik power indices for such games in terms of the topology of
simplicial complexes are provided. We calculate the indices in several examples
of weighted voting games with unfeasible coalitions, including the U.S.
Electoral College and the Parliament of Bosnia-Herzegovina.


  A recent Letter proposed changing the dimensionless status of the radian and
steradian within the SI, while allowing the continued use of the convention to
set the angle 1 radian equal to the number 1 within equations, providing this
is done explicitly. This would bring the advantages of a physics-based,
consistent, and logically-robust unit system, with unambiguous units for all
physical quantities, for the first time, while any upheaval to familiar
equations and routine practice would be minimised. More details of this
proposal are given here. The only notable changes for typical end-users would
be: improved units for the quantities torque, angular momentum and moment of
inertia; a statement of the convention accompanying some familiar equations;
and the use of different symbols for h-bar the action and h-bar the angular
momentum, a small step forward for quantum physics. Some features of the
proposal are already established practice for quantities involving the
steradian such as radiant intensity and radiance.


  The photometric and spectroscopic signatures of habitable planets orbiting
FGK stars may be modulated by surface ice coverage. To estimate its frequency
and locations, we simulated the climates of hypothetical planets with a 1D
energy balance model and assumed that the planets possess properties similar to
modern Earth (mass, geography, atmosphere). We first simulated planets with
fixed rotational axes and circular orbits, finding that the vast majority
(>90%) of planets with habitable surfaces are free of ice. For planets with
partial ice coverage, the parameter space for ice caps (interannual ice located
at the poles) is about as large as that for "ice belts" (interannual ice
located at the equator), but belts only persist on land. We then performed
simulations that mimicked perturbations from other planets by forcing
sinusoidal orbital and rotational oscillations over a range of frequencies and
amplitudes. We assume initially ice-free surfaces and set the initial
eccentricity distribution to mirror known exoplanets, while the initial
obliquity distribution matches planet formation predictions, ie favoring 90
degrees. For these dynamic cases, we find again that ~90% of habitable planets
are free of surface ice for a range of assumptions for ice's albedo. Planets
orbiting F dwarfs are three times as likely to have ice caps than belts, but
for planets orbiting K and G dwarfs ice belts are twice as likely as caps. In
some cases, a planet's surface ice can cycle between the equatorial and polar
regions. Future direct imaging surveys of habitable planets may be able to test
these predictions.


  Extracting roads from high-resolution remote sensing images (HRSIs) is vital
in a wide variety of applications, such as autonomous driving, path planning,
and road navigation. Due to the long and thin shape as well as the shades
induced by vegetation and buildings, small-sized roads are more difficult to
discern. In order to improve the reliability and accuracy of small-sized road
extraction when roads of multiple sizes coexist in an HRSI, an enhanced deep
neural network model termed Dual-Decoder-U-Net (DDU-Net) is proposed in this
paper. Motivated by the U-Net model, a small decoder is added to form a
dual-decoder structure for more detailed features. In addition, we introduce
the dilated convolution attention module (DCAM) between the encoder and
decoders to increase the receptive field as well as to distill multi-scale
features through cascading dilated convolution and global average pooling. The
convolutional block attention module (CBAM) is also embedded in the parallel
dilated convolution and pooling branches to capture more attention-aware
features. Extensive experiments are conducted on the Massachusetts Roads
dataset with experimental results showing that the proposed model outperforms
the state-of-the-art DenseUNet, DeepLabv3+ and D-LinkNet by 6.5%, 3.3%, and
2.1% in the mean Intersection over Union (mIoU), and by 4%, 4.8%, and 3.1% in
the F1 score, respectively. Both ablation and heatmap analyses are presented to
validate the effectiveness of the proposed model.


  We solve the Chapman-Kolmogorov equation and study the exact splitting
probabilities of the general stochastic process which describes polymer
translocation through membrane pores within the broad class of Markov chains.
Transition probabilities which satisfy a specific balance constraint provide a
refinement of the Chuang-Kantor-Kardar relaxation picture of translocation,
allowing us to investigate finite size effects in the evaluation of dynamical
scaling exponents. We find that (i) previous Langevin simulation results can be
recovered only if corrections to the polymer mobility exponent are taken into
account and that (ii) the dynamical scaling exponents have a slow approach to
their predicted asymptotic values as the polymer's length increases. We also
address, along with strong support from additional numerical simulations, a
critical discussion which points in a clear way the viability of the Markov
chain approach put forward in this work.


  An ordered $d$-density wave (DDW) state has been proposed as an explanation
of the pseudogap phase in underdoped high-temperature superconductors. The
staggered currents associated with this order have signatures which are
qualitatively different from those of ordered spins. We apply the order
parameter theory to an orthorhombic bilayer system and show that the expected
magnitude as well as the momentum, energy, and polarization dependence of the
consequent neutron scattering is consistent with the findings of a recent
experiment.


  This paper deals with the relation of the dynamic elastic Cosserat rod model
and the Kirchhoff beam equations. We show that the Kirchhoff beam without
angular inertia is the asymptotic limit of the Cosserat rod, as the slenderness
parameter (ratio between rod diameter and length) and the Mach number (ratio
between rod velocity and typical speed of sound) approach zero, i.e.
low-Mach-number--slenderness limit. The asymptotic framework is exact up to
fourth order in the small parameter and reveals a mathematical structure that
allows a uniform handling of the transition regime between the models. To
investigate this regime numerically, we apply a scheme that is based on a
spatial Gauss-Legendre collocation and an $\alpha$-method in time.


  Using measured spin-transfer rates from alkali atoms to He-3, combined with
spin-relaxation rates of the alkali atoms due to He-3 and He-4, it should be
possible to differentiate between isotropic and anisotropic spin-exchange. This
would give a fundamental limit on the He-3 polarization attainable in
spin-exchange optical pumping. For K-He, we find the limit to be 0.90+-0.11.


  The performance of key tasks in quantum technology, such as accurate state
preparation, can be maximized by utilizing external controls and deriving their
shape with optimal control theory. For non-pure target states, the performance
measure needs to match both angle and length of the generalized Bloch vector.
We introduce a measure based on this simple geometric picture that separates
angle and length mismatch into individual terms and apply the ensuing
optimization framework to maximize squeezing of an optomechanical oscillator at
finite temperature. Our results show that shaping the cavity drives can speed
up squeezed state preparation by more than two orders of magnitude.
Cooperativities and pulse shapes required to this end are fully compatible with
current experimental technology.


  The semantics of probabilistic languages has been extensively studied, but
specification languages for their properties have received little attention.
This paper introduces the probabilistic dynamic logic pDL, a specification
logic for programs in the probabilistic guarded command language (pGCL) of
McIver and Morgan. The proposed logic pDL can express both first-order state
properties and probabilistic reachability properties, addressing both the
non-deterministic and probabilistic choice operators of pGCL. In order to
precisely explain the meaning of specifications, we formally define the
satisfaction relation for pDL. Since pDL embeds pGCL programs in its
box-modality operator, pDL satisfiability builds on a formal MDP semantics for
pGCL programs. The satisfaction relation is modeled after PCTL, but extended
from propositional to first-order setting of dynamic logic, and also embedding
program fragments. We study basic properties of pDL, such as weakening and
distribution, that can support reasoning systems. Finally, we demonstrate the
use of pDL to reason about program behavior.


  We prove discrete-to-continuum convergence for dynamical optimal transport on
$\mathbb{Z}^d$-periodic graphs with energy density having linear growth at
infinity. This result provides an answer to a problem left open by Gladbach,
Kopfer, Maas, and Portinale (Calc Var Partial Differential Equations 62(5),
2023), where the convergence behaviour of discrete boundary-value dynamical
transport problems is proved under the stronger assumption of superlinear
growth. Our result extends the known literature to some important classes of
examples, such as scaling limits of 1-Wasserstein transport problems. Similarly
to what happens in the quadratic case, the geometry of the graph plays a
crucial role in the structure of the limit cost function, as we discuss in the
final part of this work, which includes some visual representations.


  Following the reported detection of an absorption profile associated with the
21~cm sky-averaged signal from the Cosmic Dawn by the EDGES experiment in 2018,
a number of experiments have been set up to verify this result. This paper
discusses the design process used for global 21~cm experiments, focusing
specifically on the Radio Experiment for the Analysis of Cosmic Hydrogen
(REACH). This experiment will seek to understand and compensate for systematic
errors present using detailed modelling and characterization of the
instrumentation. There is detailed the quantitative figures of merit and
numerical modelling used to assist the design process of the REACH dipole
antenna (one of the 2 antenna designs for REACH Phase I). This design process
produced a 2.5:1 frequency bandwidth dipole. The aim of this design was to
balance spectral smoothness and low impedance reflections with the ability to
describe and understand the antenna response to the sky signal to inform the
critically important calibration during observation and data analysis.


  Serial and parallel algorithms for simulation of tandem queueing systems with
infinite buffers are presented, and their performance is examined. It is shown
that the algorithms which are based on a simple computational procedure involve
low time and memory requirements.


  A non-destructive optical technique described in this paper is an effective
new tool for the investigation of defects in semiconductors. The basic
instrument for this technique---a mid-IR-laser microscope---being sensitive to
accumulations of free carriers enables the study of both accumulations of
electrically-active defects or impurities in bulk semiconductors and doped
domains in semiconductor structures. The optical beam induced scattering mode
of this microscope is designed for the investigation of recombination-active
defects but unlike EBIC it requires neither Schottky barrier or p--n junction
nor special preparation of samples


  The classical invariants of a Hamiltonian system are expected to be derivable
from the respective quantum spectrum. In fact, semiclassical expressions relate
periodic orbits with eigenfunctions and eigenenergies of classical chaotic
systems. Based on trace formulae, we construct smooth functions highly
localized in the neighborhood of periodic orbits using only quantum
information. Those functions show how classical hyperbolic structures emerge
from quantum mechanics in chaotic systems. Finally, we discuss the proper
quantum-classical link.


  When using R package tmbstan for Bayesian inference, the built-in feature
Laplace approximation to the marginal likelihood with random effects integrated
out can be switched on and off. There exists no guideline on whether Laplace
approximation should be used to achieve better efficiency especially when the
statistical model for estimating selection is complicated. To answer this
question, we conducted simulation studies under different scenarios with a
state-space model employing a VAR(1) state equation. We found that turning on
Laplace approximation in tmbstan would probably lower the computational
efficiency, and only when there is a good amount of data, both tmbstan with and
without Laplace approximation are worth trying since in this case, Laplace
approximation is more likely to be accurate and may also lead to slightly
higher computational efficiency. The transition parameters and scale parameters
in a VAR(1) process are hard to be estimated accurately and increasing the
sample size at each time point do not help in the estimation, only more time
points in the data contain more information on these parameters and make the
likelihood dominate the posterior likelihood, thus lead to accurate estimates
for them.


  Detectingandsegmentingobjectswithinwholeslideimagesis essential in
computational pathology workflow. Self-supervised learning (SSL) is appealing
to such annotation-heavy tasks. Despite the extensive benchmarks in natural
images for dense tasks, such studies are, unfortunately, absent in current
works for pathology. Our paper intends to narrow this gap. We first benchmark
representative SSL methods for dense prediction tasks in pathology images.
Then, we propose concept contrastive learning (ConCL), an SSL framework for
dense pre-training. We explore how ConCL performs with concepts provided by
different sources and end up with proposing a simple dependency-free concept
generating method that does not rely on external segmentation algorithms or
saliency detection models. Extensive experiments demonstrate the superiority of
ConCL over previous state-of-the-art SSL methods across different settings.
Along our exploration, we distll several important and intriguing components
contributing to the success of dense pre-training for pathology images. We hope
this work could provide useful data points and encourage the community to
conduct ConCL pre-training for problems of interest. Code is available.


  Embedding tables dominate industrial-scale recommendation model sizes, using
up to terabytes of memory. A popular and the largest publicly available machine
learning MLPerf benchmark on recommendation data is a Deep Learning
Recommendation Model (DLRM) trained on a terabyte of click-through data. It
contains 100GB of embedding memory (25+Billion parameters). DLRMs, due to their
sheer size and the associated volume of data, face difficulty in training,
deploying for inference, and memory bottlenecks due to large embedding tables.
This paper analyzes and extensively evaluates a generic parameter sharing setup
(PSS) for compressing DLRM models. We show theoretical upper bounds on the
learnable memory requirements for achieving $(1 \pm \epsilon)$ approximations
to the embedding table. Our bounds indicate exponentially fewer parameters
suffice for good accuracy. To this end, we demonstrate a PSS DLRM reaching
10000$\times$ compression on criteo-tb without losing quality. Such a
compression, however, comes with a caveat. It requires 4.5 $\times$ more
iterations to reach the same saturation quality. The paper argues that this
tradeoff needs more investigations as it might be significantly favorable.
Leveraging the small size of the compressed model, we show a 4.3$\times$
improvement in training latency leading to similar overall training times.
Thus, in the tradeoff between system advantage of a small DLRM model vs. slower
convergence, we show that scales are tipped towards having a smaller DLRM
model, leading to faster inference, easier deployment, and similar training
times.


  In this paper, we present a family of regular black hole solutions in the
presence of charge and angular momentum. We also discuss the related
thermodynamics and we comment about the black hole life cycle during the
balding and spin down phases. Interestingly the static solution resembles the
Ay\'on-Beato--Garc\'ia spacetime, provided the T-duality scale is redefined in
terms of the electric charge, $l_0\to Q$. The key factor at the basis of our
derivation is the employment of Padmanabhan's propagator to calculate static
potentials. Such a propagator encodes string T-duality effects. This means that
the regularity of the spacetimes here presented can open a new window on string
theory phenomenology.


  We study the growth of a population of bacteria in a dynamical hostile
environment corresponding to the immune system of the colonised organism. The
immune cells evolve as subcritical open clusters of oriented percolation and
are perpetually reinforced by an immigration process, while the bacteria try to
grow as a supercritical oriented percolation in the remaining empty space. For
appropriate values of the parameters, we prove that the population of bacteria
grows linearly. In this perspective, we build general tools to study dependent
percolation models issued from renormalization processes.


  We propose a novel hierarchical approach for multiple rotation averaging,
dubbed HARA. Our method incrementally initializes the rotation graph based on a
hierarchy of triplet support. The key idea is to build a spanning tree by
prioritizing the edges with many strong triplet supports and gradually adding
those with weaker and fewer supports. This reduces the risk of adding outliers
in the spanning tree. As a result, we obtain a robust initial solution that
enables us to filter outliers prior to nonlinear optimization. With minimal
modification, our approach can also integrate the knowledge of the number of
valid 2D-2D correspondences. We perform extensive evaluations on both synthetic
and real datasets, demonstrating state-of-the-art results.


  Forest bathing is a nature immersion practice that reduces stress, restores
mental resources, and has a wide variety of use cases in the treatment of
mental illnesses. Since many people who need the benefits of forest bathing
have little access to nature, virtual reality (VR) is being explored as a tool
for delivering accessible immersive nature experiences via virtual nature
environments (VNE's). Research on VNE's mainly utilizes the audiovisual
capabilities of VR, but since forest bathing is a fully multisensory
experience, further investigations into the integration of other sensory
technologies, namely smell and temperature, are essential for the future of VNE
research.


  Atomic ionization by intense mid-infrared (mid-IR) pulses produces low
electron energy features that the strong-field approximation, which is expected
to be valid in the tunneling ionization regime characterized by small Keldysh
parameters ($\gamma \ll 1$), cannot describe. These features include the
low-energy structure (LES), the very-low-energy structure (VLES), and the more
recently found zero-energy structure (ZES). They result from the interplay
between the laser electric field and the atomic Coulomb field which controls
the low-energy spectrum also for small $\gamma$. In the present joint
experimental and theoretical study we investigate the vectorial momentum
spectrum at very low energies. Using a reaction microscope optimized for the
detection of very low energy electrons, we have performed a thorough study of
the three-dimensional momentum spectrum well below 1 eV. Our measurements are
complemented by quantum and classical simulations, which allow for an
interpretation of the LES, VLES and of the newly identified ZES in terms of
two-dimensional Coulomb focusing and recapture into Rydberg states,
respectively.


  A $d^{\{n\}}$-cage $\mathsf K$ is the union of $n$ groups of hyperplanes in
$\Bbb P^n$, each group containing $d$ members. The hyperplanes from the
distinct groups are in general position, thus producing $d^n$ points, where
hyperplanes from all groups intersect. These points are called the nodes of
$\mathsf K$. We study the combinatorics of nodes that impose independent
conditions on the varieties $X \subset \Bbb P^n$ containing them. We prove that
if $X$, given by homogeneous polynomials of degrees $\leq d$, contains the
points from such a special set $\mathsf A$ of nodes, then it contains all the
nodes of $\mathsf K$. Such a variety $X$ is very special: in particular, $X$ is
a complete intersection.


  Evidence-based targeting has been a topic of growing interest among the
practitioners of policy and business. Formulating decision-maker's policy
learning as a fixed-budget best arm identification (BAI) problem with
contextual information, we study an optimal adaptive experimental design for
policy learning with multiple treatment arms. In the sampling stage, the
planner assigns treatment arms adaptively over sequentially arriving
experimental units upon observing their contextual information (covariates).
After the experiment, the planner recommends an individualized assignment rule
to the population. Setting the worst-case expected regret as the performance
criterion of adaptive sampling and recommended policies, we derive its
asymptotic lower bounds, and propose a strategy, Adaptive Sampling-Policy
Learning strategy (PLAS), whose leading factor of the regret upper bound aligns
with the lower bound as the size of experimental units increases.


  We evaluate the matrix elements $<r^{p}>$ for the $n$ -dimensional harmonic
oscillator in terms of the dual Hahn polynomials and derive a corresponding
three-term recurrence relation and a Pasternack-type reflection relation. A
short review of similar results for nonrelativistic hydrogen atom is also
given.


  In this paper, using variational methods, we look for non-trivial solutions
for the following problem $$ \begin{cases} -{\rm div}\left(a(|\nabla
u|^2)\nabla u\right)=g(u), & \hbox{in }\mathbb{R}^N,\; N\geq 3, \\[1mm] u(x)\to
0, &\hbox{as }|x|\to +\infty, \end{cases} $$ under general assumptions on the
continuous nonlinearity $g$. We assume only growth conditions of $g$ at $0$,
however no growth conditions at infinity are imposed. If $a(s)=(1-s)^{-1/2}$,
we obtain the well-known Born-Infeld operator, but we are able to study also a
general class of $a$ such that $a(s)\to+\infty$ as $s\to 1^{-}$. We find a
radial solution to the problem with finite energy.


  This work reports that the Systematic Literature Review process is
responsible for providing theoretical support to research in the Threat Model
and Multi-Factor Authentication. However, different from the related works,
this study aims to evaluate the main characteristics of authentication
solutions and their threat model. Also, it intends to list characteristics,
threats, and related content to a state-of-art. As a result, we brought a
portfolio analysis through charts, figures, and tables presented in the
discussion section.


  Self-supervised depth learning from monocular images normally relies on the
2D pixel-wise photometric relation between temporally adjacent image frames.
However, they neither fully exploit the 3D point-wise geometric
correspondences, nor effectively tackle the ambiguities in the photometric
warping caused by occlusions or illumination inconsistency. To address these
problems, this work proposes Density Volume Construction Network (DevNet), a
novel self-supervised monocular depth learning framework, that can consider 3D
spatial information, and exploit stronger geometric constraints among adjacent
camera frustums. Instead of directly regressing the pixel value from a single
image, our DevNet divides the camera frustum into multiple parallel planes and
predicts the pointwise occlusion probability density on each plane. The final
depth map is generated by integrating the density along corresponding rays.
During the training process, novel regularization strategies and loss functions
are introduced to mitigate photometric ambiguities and overfitting. Without
obviously enlarging model parameters size or running time, DevNet outperforms
several representative baselines on both the KITTI-2015 outdoor dataset and
NYU-V2 indoor dataset. In particular, the root-mean-square-deviation is reduced
by around 4% with DevNet on both KITTI-2015 and NYU-V2 in the task of depth
estimation. Code is available at https://github.com/gitkaichenzhou/DevNet.


  For the first time, we approach in this work the problem of the
renormalization of the Gamow-Teller decay operator for nuclear shell-model
calculations by way of many-body perturbation theory, starting from a nuclear
Hamiltonian and electroweak currents derived consistently by way of the chiral
perturbation theory. These are the inputs we need to construct microscopically
the effective shell-model Hamiltonians and decay operators. The goal is to
assess the role of both electroweak currents and many-body correlations as the
origins of the well-known problem of the quenching of the axial coupling
constant gA. To this end, the calculation of observables related to the
Gamow-Teller transitions has been performed for several nuclear systems outside
the 40Ca and 56Ni closed cores and compared with the available data.


  The unique real root of cos(x) = x, recently referred to as the Dottie
number, is expressed as an iteral of cosine. Using the derivatives of iterals,
it is shown why this number is achieved starting from any real number, when the
iterates of cosine successfully approach infinity, and how this affects the
Maclaurin series of the iterals. Properties of the iterals of cosine and sine
and their derivatives are considered. A C++ template for iteral is applied for
computation of Julia sets.


  The fact that the LambdaCDM model fits the observations does not necessarily
imply the physical existence of `dark energy'. Dropping the assumption that
cold dark matter (CDM) is a perfect fluid opens the possibility to fit the data
without dark energy. For imperfect CDM, negative bulk pressure is favoured by
thermodynamical arguments and might drive the cosmic acceleration. The
coincidence between the onset of accelerated expansion and the epoch of
structure formation at large scales might suggest that the two phenomena are
linked. A specific example is considered in which effective (anti-frictional)
forces, which may be due to dissipative processes during the formation of
inhomogeneities, give rise to accelerated expansion of a CDM universe.


  The emergence of deep learning has significantly enhanced the analysis of
electrocardiograms (ECGs), a non-invasive method that is essential for
assessing heart health. Despite the complexity of ECG interpretation, advanced
deep learning models outperform traditional methods. However, the increasing
complexity of ECG data and the need for real-time and accurate diagnosis
necessitate exploring more robust architectures, such as transformers. Here, we
present an in-depth review of transformer architectures that are applied to ECG
classification. Originally developed for natural language processing, these
models capture complex temporal relationships in ECG signals that other models
might overlook. We conducted an extensive search of the latest
transformer-based models and summarize them to discuss the advances and
challenges in their application and suggest potential future improvements. This
review serves as a valuable resource for researchers and practitioners and aims
to shed light on this innovative application in ECG interpretation.


  To have a better understanding and usage of Convolution Neural Networks
(CNNs), the visualization and interpretation of CNNs has attracted increasing
attention in recent years. In particular, several Class Activation Mapping
(CAM) methods have been proposed to discover the connection between CNN's
decision and image regions. In spite of the reasonable visualization, lack of
clear and sufficient theoretical support is the main limitation of these
methods. In this paper, we introduce two axioms -- Conservation and Sensitivity
-- to the visualization paradigm of the CAM methods. Meanwhile, a dedicated
Axiom-based Grad-CAM (XGrad-CAM) is proposed to satisfy these axioms as much as
possible. Experiments demonstrate that XGrad-CAM is an enhanced version of
Grad-CAM in terms of conservation and sensitivity. It is able to achieve better
visualization performance than Grad-CAM, while also be class-discriminative and
easy-to-implement compared with Grad-CAM++ and Ablation-CAM. The code is
available at https://github.com/Fu0511/XGrad-CAM.


  A conventional explanation of the dipole anisotropy of the cosmic microwave
background (CMB) radiation is in terms of the Doppler effect: our galaxy is
moving with respect to CMB frame with $ \sim 600 ~ km ~ s^{-1} $. However, as
the deep redshift surveys fail to reveal a convergence of the large scale flow
to zero at distances as large as $ d \sim H^{-1} 15,000 ~ km ~ s^{-1} $ (Lauer
& Postman, 1994), the uniqueness of the conventional interpretation has to be
investigated. A possible alternative might be a cosmological entropy gradient,
as suggested by Paczy\'nski & Piran (1990). We find that contrary to that
suggestion a quadrupole anisotropy is generically of the same order of
magnitude as the dipole anisotropy (or larger) not only for adiabatic but also
for iso-curvature initial perturbations. Hence, the observed dipole cannot be
explained with a very large scale perturbation which was initially
iso-curvature.


  We have performed an experimental characterization of the dynamics of
oscillating quartz tuning forks which are being increasingly used in scanning
probe microscopy as force sensors. We show that tuning forks can be described
as a system of coupled oscillators. Nevertheless, this description requires the
knowledge of the elastic coupling constant between the prongs of the tuning
fork, which has not yet been measured. Therefore tuning forks have been usually
described within the single oscillator or the weakly coupled oscillators
approximation that neglects the coupling between the prongs. We propose three
different procedures to measure the elastic coupling constant: an
opto-mechanical method, a variation of the Cleveland method and a thermal noise
based method. We find that the coupling between the quartz tuning fork prongs
has a strong influence on the dynamics and the measured motion is in remarkable
agreement with a simple model of coupled harmonic oscillators. The precise
determination of the elastic coupling between the prongs of a tuning fork
allows to obtain a quantitative relation between the resonance frequency shift
and the force gradient acting at the free end of a tuning fork prong.


  Shifted and modulated Gaussian functions play a vital role in the
representation of signals. We extend the theory into a quaternionic setting,
using two exponential kernels with two complex numbers. As a final result, we
show that every continuous and quaternion-valued signal $f$ in the Wiener space
can be expanded into a unique $\ell^2$ series on a lattice at critical density
$1$, provided one more point is added in the middle of a cell. We call that a
relaxed Gabor expansion.


  A particular, yet relevant, particular case of the Penrose inequality
involves null shells propagating in the Minkowski spacetime. Despite previous
claims in the literature, the validity of this inequality remains open. In this
paper we rewrite this inequality in terms of the geometry of the surface
obtained by intersecting the past null cone of the original surface S with a
constant time hyperplane and the "time height" function of S over this
hyperplane. We also specialize to the case when S lies in the past null cone of
a point and show the validity of the corresponding inequality in any dimension
(in four dimensions this inequality was proved by Tod). Exploiting properties
of convex hypersurfaces in Euclidean space we write down the Penrose inequality
in the Minkowski spacetime of arbitrary dimension n+2 as an inequality for two
smooth functions on the sphere. We finally obtain a sufficient condition for
the validity of the Penrose inequality in the four dimensional Minkowski
spacetime and show that this condition is satisfied by a large class of
surfaces.


  In biology, a phylogenetic tree is a tool to represent the evolutionary
relationship between species. Unfortunately, the classical Schr\"oder tree
model is not adapted to take into account the chronology between the branching
nodes. In particular, it does not answer the question: how many different
phylogenetic stories lead to the creation of n species and what is the average
time to get there? In this paper, we enrich this model in two distinct ways in
order to obtain two ranked tree models for phylogenetics, i.e. models coding
chronology. For that purpose, we first develop a model of (strongly) increasing
Schr\"oder trees, symbolically described in the classical context of increasing
labeling. Then we introduce a generalization for the labeling with some unusual
order constraint in Analytic Combinatorics (namely the weakly increasing
trees). Although these models are direct extensions of the Schr\"oder tree
model, it appears that they are also in one-to-one correspondence with several
classical combinatorial objects. Through the paper, we present these links,
exhibit some parameters in typical large trees and conclude the studies with
efficient uniform samplers.


  A new order parameter approximation to Random Boolean Networks (RBN) is
introduced, based on the concept of Boolean derivative. A statistical argument
involving an annealed approximation is used, allowing to measure the order
parameter in terms of the statistical properties of a random matrix. Using the
same formalism, a Lyapunov exponent is calculated, allowing to provide the
onset of damage spreading through the network and how sensitive it is to
minimal perturbations. Finally, the Lyapunov exponents are obtained by means of
different approximations: through distance method and a discrete variant of the
Wolf's method for continuous systems.


  The generalized Bloch theorem was applied to calculate the spin stiffness and
to consider its tendencies when introducing the doping in zigzag graphene
nanoribbons. To reach the intentions, two different flat spin spiral formations
were constructed by fixing the ferromagnetic and antiferromagnetic spin
arrangements at the two different edges by applying a constraint scheme method.
A spin stiffness was then calculated by means of a quadratic order function,
which maps the total energy difference in the self-consistent calculations onto
the Heisenberg Hamiltonian. We found a very high spin stiffness, as predicted
previously by the supercell calculation. We also showed that the
antisymmetric-symmetric tendencies of spin stiffness are induced by the
hole-electron doping. The dependence of ribbon widths of zigzag graphene
nanoribbon on the spin stiffness was also provided with similar tendencies when
the doping is taken into account.


  When creating asteroid regolith simulant, it is necessary to have a model of
asteroid regolith to guide and to evaluate the simulant. We created a model
through evaluation and synthesis of the available data sets including (1) the
returned sample from Itokawa by the Hayabusa spacecraft, (2) imagery from the
Hayabusa and NEAR spacecraft visiting Itokawa and Eros, respectively, (3)
thermal infrared observations from asteroids, (4) the texture of meteorite
regolith breccias, and (5) observations and modeling of the ejecta clouds from
disrupted asteroids. Comparison of the Hayabusa returned sample with other data
sets suggest the surficial material in the smooth regions of asteroids is
dissimilar to the bulk regolith, probably due to removal of fines by
photoionization and solar wind interaction or by preferential migration of
mid-sized particles into the smooth terrain. We found deep challenges
interpreting and applying the thermal infrared data so we were unable to use
those observations in the model. Texture of regolith breccias do not agree with
other data sets, suggesting the source regolith on Vesta was coarser than
typical asteroid regolith. The observations of disrupted asteroids present a
coherent picture of asteroid bulk regolith in collisional equilibrium, unlike
lunar regolith, HED textures, and the Itokawa returned sample. The model we
adopt consists of power laws for the bulk regolith in unspecified terrain
(differential power index -3.5, representing equilibrium), and the surficial
regolith in smooth terrain (differential power index -2.5, representing
disequilibrium). Available data do not provide adequate constraints on maximum
and minimum particle sizes for these power laws, so the model treats them as
user-selectable parameters for the simulant.


  We present Keck LRIS spectroscopy of the black hole-hosting globular cluster
RZ2109 in the Virgo elliptical galaxy NGC 4472. We find that this object has
extraordinarily broad [OIII]5007 and [OIII]4959 emission lines, with velocity
widths of approximately 2,000 k/ms. This result has significant implications
for the nature of this accreting black-hole system and the mass of the globular
cluster black hole. We show that the broad [OIII]5007 emission must arise from
material driven at high velocity from the black hole system. This is because
the volume available near the black hole is too small by many orders of
magnitude to have enough [OIII] emitting atoms to account for the observed
L([OIII]5007) at high velocities, even if this volume is filled with Oxygen at
the critical density for [OIII]5007. The Balmer emission is also weak,
indicating the observed [OIII] is not due to shocks. We therefore conclude that
the [OIII]4959,5007 is produced by photoionization of material driven across
the cluster. The only known way to drive significant material at high velocity
is for a system accreting mass near or above its Eddington limit, which
indicates a stellar mass black hole. Since it is dynamically implausible to
form an accreting stellar mass black hole system in a globular cluster with an
intermediate mass black hole (IMBH), it appears this massive globular cluster
does not have an IMBH. We discuss further tests of this conclusion, and its
implications for the M_BH - M_stellar and M_BH - sigma relations.


  In this work, we discuss a theoretically motivated family-centered design
approach for child-robot interactions, adapted by Family Systems Theory (FST)
and Family Ecological Model (FEM). Long-term engagement and acceptance of
robots in the home is influenced by factors that surround the child and the
family, such as child-sibling-parent relationships and family routines,
rituals, and values. A family-centered approach to interaction design is
essential when developing in-home technology for children, especially for
social agents like robots with which they can form connections and
relationships. We review related literature in family theories and connect it
with child-robot interaction and child-computer interaction research. We
present two case studies that exemplify how family theories, FST and FEM, can
inform the integration of robots into homes, particularly research into
child-robot and family-robot interaction. Finally, we pose five overarching
recommendations for a family-centered design approach in child-robot
interactions.


  The cosmic rays non-resonant streaming instability is believed to be the
source of substantial magnetic field amplification. In this work we investigate
the effects of the ambient plasma temperature on the instability and derive
analytical expressions of its growth rate in the hot, demagnetized regime of
interaction. To study its non-linear evolution we perform hybrid-PIC
simulations for a wide range of temperatures. We find that in the cold limit
about two-thirds of the cosmic rays drift kinetic energy is converted into
magnetic energy. Increasing the temperature of the ambient plasma can
substantially reduce the growth rate and the magnitude of the saturated
magnetic field.


  We introduce a new combinatorial condition that characterises the amenability
for locally compact groups. Our condition is weaker than the well-known
F{\o}lner's conditions, and so is potentially useful as a criteria to show the
amenability of specific locally compact groups. Our proof requires us to give a
quantitative characterisation of (relatively) weakly compact subsets of
${\mathfrak L}^1$-spaces, and we do this through the introduction of a new
notion of almost $(p,q)$-multi-boundedness for a subset of a Banach space that
is intimately related to the well-known notion of the $(q,p)$-summing constants
of an operator. As a side product, we also obtain a characterisation of weakly
compact operators from ${\mathfrak L}^\infty$-spaces in terms of their
sequences of $(q,p)$-summing constants.


  Scalability and modularity are key features for future power converters, such
that these systems can be easily employed in many applications with different
electrical specifications. In this thesis, the potential of a new bidirectional
phase-modular three-phase AC/DC converter with buck-boost capability is
evaluated by means of studying two potential application cases and developing a
hardware prototype for one of them. The DC-DC inverting buck-boost converter is
a well-known and established topology. By connecting three such systems in
parallel, a phase-modular bidirectional buck-boost DC-AC converter employing a
minimum number of active components results, where for given AC voltage
amplitudes, an arbitrary DC voltage can be generated and vice versa. Such a
three-phase converter was not yet described in literature and this project aims
at investigating the fundamental topology properties, as well as its
performance limits. A hardware demonstrator is designed for one potential
application in order to verify the basic operation and the expected high
performance in terms of efficiency and power density.


  We propose a nonlinear self-consistent model of the turbulent non-resonant
particle acceleration in solar flares. We simulate temporal evolution of the
spectra of charged particles accelerated by strong long-wavelength MHD
turbulence taking into account back reaction of the accelerated particles on
the turbulence. The main finding is that the nonlinear coupling of accelerated
particles and MHD turbulence result in prominent evolution of the spectra of
accelerated particles, which can be either soft-hard-soft or soft-hard-harder
depending on the particle injection efficiency. Such evolution patterns are
widely observed in hard X-ray and gamma-ray emission from solar flares.


  The literature on Gaussian graphical models (GGMs) contains two equally rich
and equally significant domains of research efforts and interests. The first
research domain relates to the problem of graph determination. That is, the
underlying graph is unknown and needs to be inferred from the data. The second
research domain dominates the applications in spatial epidemiology. In this
context GGMs are typically referred to as Gaussian Markov random fields
(GMRFs). Here the underlying graph is assumed to be known: the vertices
correspond to geographical areas, while the edges are associated with areas
that are considered to be neighbors of each other (e.g., if they share a
border). We introduce multi-way Gaussian graphical models that unify the
statistical approaches to inference for spatiotemporal epidemiology with the
literature on general GGMs. The novelty of the proposed work consists of the
addition of the G-Wishart distribution to the substantial collection of
statistical tools used to model multivariate areal data. As opposed to fixed
graphs that describe geography, there is an inherent uncertainty related to
graph determination across the other dimensions of the data. Our new class of
methods for spatial epidemiology allow the simultaneous use of GGMs to
represent known spatial dependencies and to determine unknown dependencies in
the other dimensions of the data. KEYWORDS: Gaussian graphical models, Gaussian
Markov random fields, spatiotemporal multivariate models


  Recent estimates of the scale of structures at the heart of quasars suggest
that the region responsible for the broad line emission are smaller than
previously thought. With this revision of scale, the broad line region is
amenable to the influence of gravitational microlensing. This study
investigates the influence on microlensing at high optical depth on a number of
current models of the Broad Line Region (BLR). It is found that the BLR can be
significantly magnified by the action of microlensing, although the degree of
magnification is dependent upon spatial and kinematic structure of the BLR.
Furthermore, while there is a correlation between the microlensing fluctuations
of the continuum source and the BLR, there is substantial scatter about this
relation, revealing that broadband photometric monitoring is not necessarily a
guide to microlensing of the BLR. The results of this study demonstrate that
the spatial and kinematic structure within the BLR may be determined via
spectroscopic monitoring of microlensed quasars.


  Using Wegner-Houghton equation, within the Local Potential Approximation, we
study critical properties of O(N) vector models. Fixed Points, together with
their critical exponents and eigenoperators, are obtained for a large set of
values of N, including N=0 and N\to\infty. Polchinski equation is also treated.
The peculiarities of the large N limit, where a line of Fixed Points at d=2+2/n
is present, are studied in detail. A derivation of the equation is presented
together with its projection to zero modes.


  The nitrogen-vacancy (NV) center in diamond is a promising quantum system for
magnetometry applications exhibiting optical readout of minute energy shifts in
its spin sub-levels. Key material requirements for NV ensembles are a high
NV$^-$ concentration, a long spin coherence time and a stable charge state.
However, these are interdependent and can be difficult to optimize during
diamond growth and subsequent NV creation. In this work, we systematically
investigate the NV center formation and properties in chemical vapor deposition
(CVD) diamond. The nitrogen flow during growth is varied by over 4 orders of
magnitude, resulting in a broad range of single substitutional nitrogen
concentrations of 0.2-20 parts per million. For a fixed nitrogen concentration,
we optimize electron-irradiation fluences with two different accelerated
electron energies, and we study defect formation via optical characterizations.
We discuss a general approach to determine the optimal irradiation conditions,
for which an enhanced NV concentration and an optimum of NV charge states can
both be satisfied. We achieve spin-spin coherence times T$_2$ ranging from 45.5
to 549 $\mu$s for CVD diamonds containing 168 to 1 parts per billion NV$^-$
centers, respectively. This study shows a pathway to engineer properties of
NV-doped CVD diamonds for improved sensitivity.


  The well-known superradiant amplification mechanism allows a charged scalar
field of proper mass $\mu$ and electric charge $q$ to extract the Coulomb
energy of a charged Reissner-Nordstr\"om black hole. The rate of energy
extraction can grow exponentially in time if the system is placed inside a
reflecting cavity which prevents the charged scalar field from escaping to
infinity. This composed black-hole-charged-scalar-field-mirror system is known
as the {\it charged black-hole bomb}. Previous numerical studies of this
composed physical system have shown that, in the linearized regime, the
inequality $q/\mu>1$ provides a necessary condition for the development of the
superradiant instability. In the present paper we use analytical techniques to
study the instability properties of the charged black-hole bomb in the regime
of linearized scalar fields. In particular, we prove that the lower bound
${{q}\over{\mu}}>\sqrt{{{r_{\text{m}}/r_--1}\over{r_{\text{m}}/r_+-1}}}$
provides a necessary condition for the development of the superradiant
instability in this composed physical system (here $r_{\pm}$ are the horizon
radii of the charged Reissner-Nordstr\"om black hole and $r_{\text{m}}$ is the
radius of the confining mirror). This {\it analytically} derived lower bound on
the superradiant instability regime of the composed
black-hole-charged-scalar-field-mirror system is shown to agree with direct
{\it numerical} computations of the instability spectrum.


  To probe the nature of stellar evolution in dense environments, we study the
dense core of the globular cluster Messier 13 using pre-refurbishment Planetary
Camera-I images obtained with the Hubble Space Telescope. We find 15 blue
straggler star candidates and 10 other possible blue stragglers in this region
of M13. Their specific frequency is in the range 0.04-0.07, comparable to what
is observed near the centers of other dense clusters. A comparison between
M13's observed V band stellar luminosity function and a theoretical model
(Bergbusch & Vandenberg 1992) for the luminosity function of an old, metal-poor
cluster shows that the model predicts too few of the brightest red giants
(V~12.5-15) by a factor of two relative to subgiants/turnoff stars (> 6 sigma
effect). The radial distributions of the red giants, blue stragglers, and
subgiants are consistent with one another. Stars in the blue horizontal branch
of M13, however, appear to be centrally depleted relative to other stellar
types.
  We combine data from three dense `King model clusters', M13, M3, and 47 Tuc,
and two post core collapse clusters, M30 and M15, and compare the distributions
of various stellar types as a function of (r/r_half light) and (r/r_core). The
horizontal branch stars in the combined sample appear to be centrally depleted
relative to the giants (97% significance) - this depletion is only marginal (<
about 1.5 sigma) in each of the clusters taken individually. The blue
stragglers in the combined sample are centrally concentrated relative to the
giants.


  The usual dispersionless limit of the KP hierarchy does not work in the case
where the dependent variable has values in a noncommutative (e.g. matrix)
algebra. Passing over to the potential KP hierarchy, there is a corresponding
scaling limit in the noncommutative case, which turns out to be the hierarchy
of a `pseudodual chiral model' in 2+1 dimensions (`pseudodual' to a hierarchy
extending Ward's (modified) integrable chiral model). Applying the scaling
procedure to a method generating exact solutions of a matrix (potential) KP
hierarchy from solutions of a matrix linear heat hierarchy, leads to a
corresponding method that generates exact solutions of the matrix
dispersionless potential KP hierarchy, i.e. the pseudodual chiral model
hierarchy. We use this result to construct classes of exact solutions of the
su(m) pseudodual chiral model in 2+1 dimensions, including various multiple
lump configurations.


  Purpose: There is increasing interest in computed tomography (CT) image
estimations from magnetic resonance (MR) images. The estimated CT images can be
utilised for attenuation correction, patient positioning, and dose planning in
diagnostic and radiotherapy workflows. This study aims to introduce a novel
statistical learning approach for improving CT estimation from MR images and to
compare the performance of our method with the existing model based CT image
estimation methods.
  Methods: The statistical learning approach proposed here consists of two
stages. At the training stage, prior knowledges about tissue-types from CT
images were used together with a Gaussian mixture model (GMM) to explore CT
image estimations from MR images. Since the prior knowledges are not available
at the prediction stage, a classifier based on RUSBoost algorithm was trained
to estimate the tissue-types from MR images. For a new patient, the trained
classifier and GMMs were used to predict CT image from MR images. The
classifier and GMMs were validated by using voxel level 10-fold
cross-validation and patient-level leave-one-out cross-validation,
respectively.
  Results: The proposed approach has outperformance in CT estimation quality in
comparison with the existing model based methods, especially on bone tissues.
Our method improved CT image estimation by 5% and 23% on the whole brain and
bone tissues, respectively.
  Conclusions: Evaluation of our method shows that it is a promising method to
generate CT image substitutes for the implementation of fully MR-based
radiotherapy and PET/MRI applications.


  Context. The accretion process in Classical T Tauri Stars (CTTSs) can be
studied through the analysis of some UV and X-ray emission lines which trace
hot gas flows and act as diagnostics of the post-shock downfalling plasma. In
the UV band, where higher spectral resolution is available, these lines are
characterized by rather complex profiles whose origin is still not clear.
  Aims. We investigate the origin of UV and X-ray emission at impact regions of
density structured (fragmented) accretion streams.We study if and how the
stream fragmentation and the resulting structure of the post-shock region
determine the observed profiles of UV and X-ray emission lines.
  Methods. We model the impact of an accretion stream consisting of a series of
dense blobs onto the chromosphere of a CTTS through 2D MHD simulations. We
explore different levels of stream fragmentation and accretion rates. From the
model results, we synthesize C IV (1550 {\AA}) and OVIII (18.97 {\AA}) line
profiles.
  Results. The impacts of accreting blobs onto the stellar chromosphere produce
reverse shocks propagating through the blobs and shocked upflows. These
upflows, in turn, hit and shock the subsequent downfalling fragments. As a
result, several plasma components differing for the downfalling velocity,
density, and temperature are present altoghether. The profiles of C IV doublet
are characterized by two main components: one narrow and redshifted to speed
$\approx$ 50 km s$^{-1}$ and the other broader and consisting of subcomponents
with redshift to speed in the range 200 $\approx$ 400 km s$^{-1}$. The profiles
of OVIII lines appear more symmetric than C IV and are redshifted to speed
$\approx$ 150 km s$^{-1}$.
  Conclusions. Our model predicts profiles of C IV line remarkably similar to
those observed and explains their origin in a natural way as due to stream
fragmentation.


  This article gives an introduction to arithmetic motivic integration in the
context of p-adic integrals that arise in representation theory. A special case
of the fundamental lemma is interpreted as an identity of Chow motives.


  Computer aided diagnostics often requires analysis of a region of interest
(ROI) within a radiology scan, and the ROI may be an organ or a suborgan.
Although deep learning algorithms have the ability to outperform other methods,
they rely on the availability of a large amount of annotated data. Motivated by
the need to address this limitation, an approach to localisation and detection
of multiple organs based on supervised and semi-supervised learning is
presented here. It draws upon previous work by the authors on localising the
thoracic and lumbar spine region in CT images. The method generates six
bounding boxes of organs of interest, which are then fused to a single bounding
box. The results of experiments on localisation of the Spleen, Left and Right
Kidneys in CT Images using supervised and semi supervised learning (SSL)
demonstrate the ability to address data limitations with a much smaller data
set and fewer annotations, compared to other state-of-the-art methods. The SSL
performance was evaluated using three different mixes of labelled and
unlabelled data (i.e.30:70,35:65,40:60) for each of lumbar spine, spleen left
and right kidneys respectively. The results indicate that SSL provides a
workable alternative especially in medical imaging where it is difficult to
obtain annotated data.


  Indoor rooms are among the most common use cases in 3D scene understanding.
Current state-of-the-art methods for this task are driven by large annotated
datasets. Room layouts are especially important, consisting of structural
elements in 3D, such as wall, floor, and ceiling. However, they are difficult
to annotate, especially on pure RGB video. We propose a novel method to produce
generic 3D room layouts just from 2D segmentation masks, which are easy to
annotate for humans. Based on these 2D annotations, we automatically
reconstruct 3D plane equations for the structural elements and their spatial
extent in the scene, and connect adjacent elements at the appropriate contact
edges. We annotate and publicly release 2246 3D room layouts on the
RealEstate10k dataset, containing YouTube videos. We demonstrate the high
quality of these 3D layouts annotations with extensive experiments.