  This set of theories presents an Isabelle/HOL+Isar formalisation of stream
processing components introduces in Focus, a framework for formal specification
and development of interactive systems. This is an extended and updated version
of the formalisation, which was elaborated within the methodology 'Focus on
Isabelle'. In addition, we also applied the formalisation on three case studies
that cover different application areas: process control (Steam Boiler System),
data transmission (FlexRay communication protocol), memory and processing
components (Automotive-Gateway System).


  We construct irreducible complex projective varieties such that the Lyubeznik
numbers of their affine cones depend on the choices of projective embeddings.
The main ingredient is the recent work of Reichelt-Saito-Walther, where the
Lyubeznik numbers are reinterpreted using perverse sheaves and reducible
projective varieties with dependent Lyubeznik numbers are constructed.


  The 3D organisation of the genome in interphase cells is not a randomly
folded polymer. Rather, experiments show that chromosomes arrange into a
network of 3D compartments that correlate with biological processes, such as
transcription, chromatin modifications, and protein binding. However, these
compartments do not exist during cell division when the DNA is condensed, and
it is unclear how and when they emerge. In this paper, we focus on the early
stages after cell-division as the chromosomes start to decondense. We use a
simple polymer model to understand the types of 3D structures that emerge from
local unfolding of a compact initial state. From simulations, we recover 3D
compartments, such as TADs and A/B compartments, that are consistently detected
in Chromosome Capture Experiments across cell types and organisms. This
suggests that the large-scale 3D organisation is a result of an inflation
process.


  We generalize the combinatorial description of the orbifold (Chen--Ruan)
cohomology and of the Grothendieck ring of a Deligne--Mumford toric stack and
its associated stacky fan in a lattice $N$ in the presence of a deformation
parameter $\beta \in N \otimes {\mathbb C}.$ As an application, we construct a
topological mirror symmetry map that produces a complete system of
$\Gamma$--series solutions to the better behaved version of the GKZ
hypergeometric system for $\beta \in N \otimes {\mathbb C}.$


  We describe a new method for imaging ultrafast dynamics in condensed matter
using inelastic x-ray scattering (IXS). We use the concepts of causality and
irreversibility to construct a general solution to the inverse scattering
problem (or "phase problem") for inelastic x-ray scattering, which enables
direct imaging of dynamics of the electron density with resolutions of ~1
attosecond (10-18 sec) in time and < 1 A in space. This method is not a Fourier
transform of IXS data, but a means to impose causality on the data and
reconstruct the charge propagator. The method can also be applied to inelastic
electron or neutron scattering. We give a general outline of phenomena that can
and cannot be studied with this technique, and provide an outlook for the
future.


  Prototype pollution is a recent vulnerability that affects JavaScript code,
leading to high impact attacks such as arbitrary code execution. The
vulnerability is rooted in JavaScript's prototype-based inheritance, enabling
attackers to inject arbitrary properties into an object's prototype at runtime.
The impact of prototype pollution depends on the existence of otherwise benign
pieces of code (gadgets), which inadvertently read from attacker-controlled
properties to execute security-sensitive operations. While prior works
primarily study gadgets in third-party libraries and client-side applications,
gadgets in JavaScript runtime environments are arguably more impactful as they
affect any application that executes on these runtimes.
  In this paper we design, implement, and evaluate a pipeline, GHunter, to
systematically detect gadgets in V8-based JavaScript runtimes with prime focus
on Node.js and Deno. GHunter supports a lightweight dynamic taint analysis to
automatically identify gadget candidates which we validate manually to derive
proof-of-concept exploits. We implement GHunter by modifying the V8 engine and
the targeted runtimes along with features for facilitating manual validation.
Driven by the test suites of Node.js and Deno, we use GHunter in a study of
gadgets in these runtimes. We identified a total of 56 new gadgets in Node.js
and 67 gadgets in Deno, pertaining to vulnerabilities such as arbitrary code
execution (19), privilege escalation (31), path traversal (13), and more.
Moreover, we systematize, for the first time, existing mitigations for
prototype pollution and gadgets in terms of development guidelines. We collect
a list of vulnerable applications and revisit the fixes through the lens of our
guidelines. Through this exercise, we identified one high-severity CVE leading
to remote code execution, which was due to incorrectly fixing a gadget.


  B20-type compounds, such as MnSi and FeGe, host helimagnetic and skyrmion
phases at the mesoscale, which are canonically explained by the combination of
ferromagnetic isotropic interactions with weaker chiral Dzyaloshinskii-Moriya
ones. Mysteriously, MnGe evades this paradigm as it displays a noncollinear
magnetic state at a much shorter nanometer scale. Here we show that the length
scale and volume-dependent magnetic properties of MnGe stem from purely
isotropic exchange interactions, generally obtained in the paramagnetic state.
Our approach is validated by comparing MnGe with the canonical B20-helimagnet
FeGe. The free energy of MnGe is calculated, from which we show how triple-q
magnetic states can stabilize by adding higher-order interactions.


  In the usual d dimensional SO(d) gauged Higgs models with $d$-component Higgs
fields, the 'energies' of the topologically stable solitons are bounded from
below by the Chern-Pontryagin charges. A new class of Higgs models is proposed
here, whose 'energies' are stabilised instead by the winding number of the
Higgs field itself, with no reference to the gauge group. Consequently, such
Higgs models can be gauged by SO(N), with 2 \le N \le d.


  Diffusion-weighted MR imaging (DWI) is the only method we currently have to
measure connections between different parts of the human brain in vivo. To
elucidate the structure of these connections, algorithms for tracking bundles
of axonal fibers through the subcortical white matter rely on local estimates
of the fiber orientation distribution function (fODF) in different parts of the
brain. These functions describe the relative abundance of populations of axonal
fibers crossing each other in each location. Multiple models exist for
estimating fODFs. The quality of the resulting estimates can be quantified by
means of a suitable measure of distance on the space of fODFs. However, there
are multiple distance metrics that can be applied for this purpose, including
smoothed $L_p$ distances and the Wasserstein metrics. Here, we give four
reasons for the use of the Earth Mover's Distance (EMD) equipped with the
arc-length, as a distance metric. (continued)


  We propose a new geometric regularization principle for reconstructing vector
fields based on prior knowledge about their divergence. As one important
example of this general idea, we focus on vector fields modelling blood flow
pattern that should be divergent in arteries and convergent in veins. We show
that this previously ignored regularization constraint can significantly
improve the quality of vessel tree reconstruction particularly around
bifurcations where non-zero divergence is concentrated. Our divergence prior is
critical for resolving (binary) sign ambiguity in flow orientations produced by
standard vessel filters, e.g. Frangi. Our vessel tree centerline reconstruction
combines divergence constraints with robust curvature regularization. Our
unsupervised method can reconstruct complete vessel trees with near-capillary
details on synthetic and real 3D volumes.


  We study transition to phase synchronization in an ensemble of Stuart-Landau
oscillators interacting on a star network. We observe that by introducing
frequency weighted coupling and time scale variations in the dynamics of nodes,
system exhibits a first order explosive transition to phase synchrony. Further,
we extend this study to understand the nature of synchronization in case of two
coupled star networks. In presence of symmetry preserving (direct) coupling
between the hubs of the two stars, we observe that hysteresis width first
increases and then saturates for increasing inter-star coupling strength. For
symmetry breaking (conjugate) coupling, the hysteresis width first increases
and then decreases with increasing inter-star coupling. As we increase the
inter-star coupling further, the transition gradually becomes a second order.


  Barnard 59 and Lupus 1 are two nearby star-forming regions visible from the
southern hemisphere. In this manuscript, we present deep ($\sigma$ $\lesssim$
15 $ \mu$Jy) radio observations ($\nu$ = 6 GHz; $\lambda$ = 5 cm) of these
regions, and report the detection of a total of 114 sources. Thirteen of these
sources are associated with known young stellar objects, nine in Barnard 59 and
four in Lupus 1. The properties of the radio emission (spectral index and, in
some cases, polarization) suggest a thermal origin for most young stellar
objects. Only for two sources (Sz~65 and Sz~67) are there indications for a
possible non-thermal origin; more observations will be needed to ascertain the
exact nature of the radio emission in these sources. The remaining radio
detections do not have counterparts at other wavelengths, and the number of
sources detected per unit solid angle is in agreement with extragalactic number
counts. This suggests that all radio sources not associated with known young
stellar objects are background extragalactic sources.


  We report the Compton scattering emission from the Poynting flux acceleration
of electron- positron plasma simulated by the 2-1/2 dimensional
particle-in-cell(PIC) code. We show these and other remarkable properties of
Poynting flux acceleration and Compton spectral output, and discuss the
agreement with the observed spectra of GRBs and XRFs.


  It is shown that the various claims made in the comment by M. Ya. Azbel
(physics/0403106) on the two publications Phys. Rev. Lett. 91, 055502 (2003)
and Phys. Rev. Lett. 85, 4988 (2000) are invalid. They are a result of a
misinterpretation of the main points of both papers.


  In the present work, the effects of diffuse and collimated radiation on the
symmetrical cooling case of natural convection in a two-dimensional cavity
heated from the bottom have been investigated, numerically. The cavity is
convectively heated from the bottom with heat transfer coefficient of 50 W/m2K
and free stream temperature 305 K, while both vertical walls of cavity are
isothermal at temperature of 296 K. The top wall is adiabatic and all walls are
opaque for radiation heat transfer. For collimated case, a small
semitransparent window of non-dimensional width of 0.05 at height of 0.7 has
been created on the left wall and a collimated irradiation of value 1000 W/m2
at an angle 45 is applied on this semitransparent window. The results reveal
that the diffuse radiation has little effect on the dynamics of two rolls
inside the cavity, however, collimated beam irradiation changes the dynamics of
two rolls significantly and also the heat transfer characteristics. This
further changes with the optical thickness of the fluid. The left vortex is
bigger in size than the right vortex for collimated beam in transparent fluid,
whereas, reverse trend is seen for collimated beam in non-zero optical
thickness of the fluid.


  In this paper we describe an algorithm based on the Picard-Vessiot theory
that constructs, given any curve invariant under a finite linear algebraic
group over the complex numbers, an ordinary linear differential equation whose
Schwarz map parametrizes it.


  Cosmic rays are the only agent capable of ionizing the interior of dense
molecular clouds and, thus, they are believed to play an essential role in
determining the physical and chemical evolution of star-forming regions. In
this work, we aim to study cosmic-ray induced ionization rates in starburst
environments using non-thermal emissions of cosmic rays from starburst nuclei.
To this end, we first revisit cosmic-ray models which could explain data of
non-thermal emissions from radio to X-ray and gamma-ray from nuclei of three
prototypical starburst galaxies NGC 253, M82, and Arp 220. These models are
then applied to predict ionization rates in starburst environments which gives
values around $10^{-14}$ s$^{-1}$. Such a high value of the ionization rate,
which is 2 to 3 orders of magnitude higher than the typical values found in the
Milky Way, is probably due to relatively high rates of supernova explosions
occurring within the nuclei of these starburst galaxies. We also discuss in
more details the case of NGC 253 where our predicted ionization rate is found
to be, in most cases, a few times smaller than the values inferred from
molecular line observations of clouds in the starburst nucleus. The general
framework provided in this work illustrates how the use of non-thermal emission
data could help to provide more insights into ionization rates or, more
generally, cosmic-ray impact in starburst environments.


  We performed $^{59}$Co nuclear magnetic resonance (NMR) measurements of
single-crystalline U$_6$Co. There is a small decrease in the Knight shift in
the superconducting (SC) state, but this change mainly arises from the SC
diamagnetic effect. The negligible change of the spin part of the Knight shift,
together with the absence of the Pauli-paramagnetic effect in the SC U$_6$Co,
is understood as a consequence of the small spin susceptibility. The nuclear
spin-lattice relaxation rate $1/T_1$ is also measured in the SC state under the
magnetic field, and exhibits a tiny Hebel-Slichter peak just below the SC
transition temperature and exponential behavior at lower temperatures. These
behaviors are in agreement with the full-gap s-wave pairing in U$_6$Co.


  Ion cyclotron emission (ICE) was the first collective radiative instability,
driven by confined fusion-born ions, observed from deuterium-tritium plasmas in
JET and TFTR. ICE comprises strongly suprathermal emission, which has spectral
peaks at multiple ion cyclotron harmonic frequencies as evaluated at the outer
mid-plane edge of tokamak plasmas. The measured intensity of ICE spectral peaks
scaled linearly with measured fusion reactivity in JET. In other large tokamak
plasmas, ICE is currently used as an indicator of fast ions physics. The
excitation mechanism for ICE is the magnetoacoustic cyclotron instability
(MCI); in the case of JET and TFTR, the MCI is driven by a set of centrally
born fusion products, lying just inside the trapped-passing boundary in
velocity space, whose drift orbits make large radial excursions to the outer
mid-plane edge. Diagnostic exploitation of ICE in future experiments therefore
rests in part on deep understanding of the MCI, and recent advances in
computational plasma physics have led to substantial recent progress, reviewed
here.


  The kinetic energy term of Hamiltonian systems with balanced loss and gain is
not semi-positive-definite, leading to instabilities at the classical as well
quantum level. It is shown that an additional Lorentz interaction in the
Hamiltonian allows the kinetic energy term to be semi-positive-definite and
thereby, improving the stability properties of the system. Further, a
consistent quantum theory admitting bound states may be obtained on the real
line instead of Stoke wedges on the complex plane. The Landau Hamiltonian in
presence of balanced loss and gain is considered for elucidating the general
result. The kinetic energy term is semi-positive-definite provided the
magnitude of the applied external magnetic field is greater than the magnitude
of the `analogous magnetic field' due to the loss gain terms. It is shown that
the classical particle moves on an elliptical orbit with a cyclotron frequency
that is less than its value in absence of the loss-gain terms. The quantum
system share the properties of the standard Landau Hamiltonian, but, with the
modified cyclotron frequency. It is shown that the Hall current has
non-vanishing components along the direction of the external uniform electric
field and to its transverse direction. The Pauli equation in presence of
balanced loss and gain is shown to be supersymmetric.


  We review the spectrum of lightest scalar resonances recently determined
using dispersion techniques. The conceptual difference between the pole mass
and the bare mass (or the line--shape mass) is stressed. The nature of the
lightest scalars are discussed and we argue, without relying on any model
details, that the $\sigma(500)$, $\kappa(700)$, $a_0(980)$ and $f_0(980)$ may
be understood as chiral partners of the Nambu--Goldstone bosons in the linear
realization of chiral symmetry. But there remains some difficulties in
understanding the role of $f_0(980)$ in this picture.


  The flow of an ideal fluid possesses a remarkable property: despite limited
regularity of the velocity field, its particle trajectories are analytic
curves. In our previous work, this fact was used to introduce the structure of
an analytic Banach manifold in the set of 2D stationary flows having no
stagnation points. The main feature of our description was to regard the
stationary flow as a collection of its analytic flow lines, parameterized
non-analytically by values of the stream function $\psi$.
  In this work, we adapt this description to the case of 2D stationary flows
which have a single elliptic stagnation point. Namely, we consider flows in a
domain bounded by the graph of analytic function $\rho = b(\varphi)$, where
$(\rho,\varphi)$ are polar coordinates centred at the origin. The position $p$
of the stagnation point is an unknown and must be included in the solution. In
polar coordinates $(r,\theta)$ centred at $p$, the flow lines are described by
graphs of $r=a(\psi,\theta)$, where $a$ is a `partially-analytic' function
(analytic in $\theta$, of finite regularity in $\psi$). The equation of
stationary flow $\Delta \psi = F(\psi)$ is transformed to the quasilinear
elliptic equation $\Xi(a) = F(\psi)$ for the flow lines. The analysis is
complicated by the fact that the ellipticity of $\Xi$ degenerates at the
stagnation point.
  We introduce function spaces for the partially-analytic family of flow lines,
modelled on the weighted Kondratev spaces, appropriate for the degenerate
setting. The equation of stationary flow is thus regarded as an analytic
operator equation in complex Banach spaces, with local solution given by the
implicit function theorem. In particular, we show that near the circular flow
of constant vorticity, the equation has unique solution $p, a(\psi,\theta)$
depending analytically on parameters $b(\varphi)$ and $F(\psi)$.


  Massive binaries play significant roles in many fields. Identification of
massive stars, particularly massive binaries, is of great importance. In this
paper, by adopting the technique of measuring the equivalent widths of several
spectral lines, we identified 9,382 early-type stars from LAMOST
medium-resolution survey and divided the sample into four groups, T1
($\sim$O-B4), T2 ($\sim$B5), T3 ($\sim$B7), and T4 ($\sim$B8-A). The relative
radial velocities $RV_{\rm rel}$ were calculated using the Maximum Likelihood
Estimation. The stars with significant changes of $RV_{\rm rel}$ and at least
larger than 15.57km s$^{-1}$ were identified as spectroscopic binaries. We
found that the observed spectroscopic binary fractions for the four groups are
$24.6\%\pm0.5\%$, $20.8\%\pm0.6\%$, $13.7\%\pm0.3\%$, and $7.4\%\pm0.3\%$,
respectively. Assuming that orbital period ($P$) and mass ratio ($q$) have
intrinsic distributions as $f(P) \propto P^\pi$ (1\textless$P$\textless1000
days) and $f(q) \propto q^\kappa$ (0.1\textless$q$\textless1), respectively, we
conducted a series of Monte-Carlo simulations to correct observational biases
for estimating the intrinsic multiplicity properties. The results show that the
intrinsic binary fractions for the four groups are 68$\%\pm8\%$, 52$\%\pm3\%$,
44$\%\pm6\%$, and 44$\%\pm6\%$, respectively. The best estimated values for
$\pi$ are -1$\pm0.1$, -1.1$\pm0.05$, -1.1$\pm0.1$, and -0.6$\pm0.05$,
respectively. The $\kappa$ cannot be constrained for groups T1 and T2 and is
-2.4$\pm0.3$ for group T3 and -1.6$\pm0.3$ for group T4. We confirmed the
relationship of a decreasing trend in binary fractions towards late-type stars.
No correlation between the spectral type and the orbital period distribution
has been found yet, possibly due to the limitation of observational cadence.


  In classification, it is usual to observe that models trained on a given set
of classes can generalize to previously unseen ones, suggesting the ability to
learn beyond the initial task. This ability is often leveraged in the context
of transfer learning where a pretrained model can be used to process new
classes, with or without fine tuning. Surprisingly, there are a few papers
looking at the theoretical roots beyond this phenomenon. In this work, we are
interested in laying the foundations of such a theoretical framework for
transferability between sets of classes. Namely, we establish a partially
ordered set of subsets of classes. This tool allows to represent which subset
of classes can generalize to others. In a more practical setting, we explore
the ability of our framework to predict which subset of classes can lead to the
best performance when testing on all of them. We also explore few-shot
learning, where transfer is the golden standard. Our work contributes to better
understanding of transfer mechanics and model generalization.


  Computer vision in general presented several advances such as training
optimizations, new architectures (pure attention, efficient block, vision
language models, generative models, among others). This have improved
performance in several tasks such as classification, and others. However, the
majority of these models focus on modifications that are taking distance from
realistic neuroscientific approaches related to the brain. In this work, we
adopt a more bio-inspired approach and present the Yin Yang Convolutional
Network, an architecture that extracts visual manifold, its blocks are intended
to separate analysis of colors and forms at its initial layers, simulating
occipital lobe's operations. Our results shows that our architecture provides
State-of-the-Art efficiency among low parameter architectures in the dataset
CIFAR-10. Our first model reached 93.32\% test accuracy, 0.8\% more than the
older SOTA in this category, while having 150k less parameters (726k in total).
Our second model uses 52k parameters, losing only 3.86\% test accuracy. We also
performed an analysis on ImageNet, where we reached 66.49\% validation accuracy
with 1.6M parameters. We make the code publicly available at:
https://github.com/NoSavedDATA/YinYang_CNN.


  One of the most common control decisions faced by power system operators is
the question of how to dispatch generation to meet demand for power. This is a
complex optimization problem that includes many nonlinear, non convex
constraints as well as inherent uncertainties about future demand for power and
available generation. In this paper we develop convex formulations to
appropriately model crucial classes of nonlinearities and stochastic effects.
We focus on solving a nonlinear optimal power flow (OPF) problem that includes
loss of synchrony constraints and models wind-farm caused fluctuations. In
particular, we develop (a) a convex formulation of the deterministic
phase-difference nonlinear Optimum Power Flow (OPF) problem; and (b) a
probabilistic chance constrained OPF for angular stability, thermal overloads
and generation limits that is computationally tractable.


  Data augmentation is one of the most popular techniques for improving the
robustness of neural networks. In addition to directly training the model with
original samples and augmented samples, a torrent of methods regularizing the
distance between embeddings/representations of the original samples and their
augmented counterparts have been introduced. In this paper, we explore these
various regularization choices, seeking to provide a general understanding of
how we should regularize the embeddings. Our analysis suggests the ideal
choices of regularization correspond to various assumptions. With an invariance
test, we argue that regularization is important if the model is to be used in a
broader context than the accuracy-driven setting because non-regularized
approaches are limited in learning the concept of invariance, despite equally
high accuracy. Finally, we also show that the generic approach we identified
(squared $\ell_2$ norm regularized augmentation) outperforms several recent
methods, which are each specially designed for one task and significantly more
complicated than ours, over three different tasks.


  We explore the long-time dynamics of a system of identical charged particles
trapped on a closed helix. This system has recently been found to exhibit an
unconventional deformation of the linear spectrum when tuning the helix radius.
Here we show that the same geometrical parameter can affect significantly also
the dynamical behaviour of an initially broad excitation for long times. In
particular, for small values of the radius, the excitation disperses into the
whole crystal whereas within a specific narrow regime of larger radii the
excitation self-focuses, assuming finally a localized form. Beyond this regime,
the excitation defocuses and the dispersion gradually increases again. We
analyze this geometrically controlled nonlinear behaviour using an effective
discrete nonlinear Schr\"{o}dinger model, which allows us among others to
identify a number of breather-like excitations.


  The influence of a modifier based on multi walled carbon nanotubes (MWCNT) is
investigated using C11000 copper alloy. The influence of the modifier addition
into the melt was investigated using tensile test, hardness measurements, X-ray
diffraction method and microstructural investigations. It was evaluated that
the yield and tensile strengths of the metal increased due to the
microstructural changes in the formed metal after addition of 0.01wt.% of the
MWCNTs. It was also evaluated that the addition of mentioned amount of MWCNT
into alloy has no influence to the phase composition of the formed metal.


  Tracking 3D human motion in real-time is crucial for numerous applications
across many fields. Traditional approaches involve attaching artificial
fiducial objects or sensors to the body, limiting their usability and
comfort-of-use and consequently narrowing their application fields. Recent
advances in Artificial Intelligence (AI) have allowed for markerless solutions.
However, most of these methods operate in 2D, while those providing 3D
solutions compromise accuracy and real-time performance. To address this
challenge and unlock the potential of visual pose estimation methods in
real-world scenarios, we propose a markerless framework that combines
multi-camera views and 2D AI-based pose estimation methods to track 3D human
motion. Our approach integrates a Weighted Least Square (WLS) algorithm that
computes 3D human motion from multiple 2D pose estimations provided by an
AI-driven method. The method is integrated within the Open-VICO framework
allowing simulation and real-world execution. Several experiments have been
conducted, which have shown high accuracy and real-time performance,
demonstrating the high level of readiness for real-world applications and the
potential to revolutionize human motion capture.


  In this paper, we investigate the Cauchy problem for the tridimensional
Boussinesq equations with horizontal dissipation. Under the assumption that the
initial data is an axisymmetric without swirl, we prove the global
well-posedness for this system. In the absence of vertical dissipation, there
is no smoothing effect on the vertical derivatives. To make up this
shortcoming, we first establish a magic relationship between $\frac{u^{r}}{r}$
and $\frac{\omega_\theta}{r}$ by taking full advantage of the structure of the
axisymmetric fluid without swirl and some tricks in harmonic analysis. This
together with the structure of the coupling of \eqref{eq1.1} entails the
desired regularity.


  We start with the compressible Oldroyd--B model derived in
\cite{Barrett-Lu-Suli} ({\em J. W. Barrett, Y. Lu, E. S\"uli. Existence of
large-data finite-energy global weak solutions to a compressible Oldroyd--B
model. Comm. Math. Sci. 15 (2017), 1265--1323}), where the existence of
global-in-time finite-energy weak solutions was shown in two dimensional
setting with stress diffusion. In the paper, we investigate the case without
stress diffusion. We first restrict ourselves to the corotational setting as in
\cite{LM00} ({\em P. L. Lions, N. Masmoudi. Global solutions for some Oldroyd
models of non-Newtonian flows. Chin. Ann. Math., Ser. B 21(2) (2000),
131--146.}) We further assume the extra stress tensor is a scalar matrix and we
derive a simplified model which takes a similar form as the multi-component
compressible Navier--Stokes equations, where, however, the pressure term
related to the scalar extra stress tensor has the opposite sign. By employing
the techniques developed in \cite{VWY19, Novotny-Pokorny-19}, we can still
prove the global-in-time existence of finite energy weak solutions in two or
three dimensions, without the presence of stress diffusion.


  We calculate the transformation from the Sloan Digital Sky Survey (SDSS)
photometric system to the Johnson-Morgan-Cousins System in the HK Survey. This
research was done in late 2001, so the SDSS photometry was taken from the
database prior to the release of DR1. This paper is being posted because it is
referenced in other papers in the literature, but will not be submitted to a
refereed journal because it uses unpublished versions of the catalogs.


  In this paper we develop methods for classifying Baker-Richter-Szymik's
Azumaya algebras over a commutative ring spectrum, especially in the largely
inaccessible case where the ring is nonconnective. We give
obstruction-theoretic tools, constructing and classifying these algebras and
their automorphisms with Goerss-Hopkins obstruction theory, and give
descent-theoretic tools, applying Lurie's work on $\infty$-categories to show
that a finite Galois extension of rings in the sense of Rognes becomes a
homotopy fixed-point equivalence on Brauer spaces.
  For even-periodic ring spectra $E$, we find that the "algebraic" Azumaya
algebras whose coefficient ring is projective are governed by the Brauer-Wall
group of $\pi_0(E)$, recovering a result of Baker-Richter-Szymik. This allows
us to calculate many examples. For example, we find that the algebraic Azumaya
algebras over Lubin-Tate spectra have either 4 or 2 Morita equivalence classes
depending on whether the prime is odd or even, that all algebraic Azumaya
algebras over the complex K-theory spectrum $KU$ are Morita trivial, and that
the group of the Morita classes of algebraic Azumaya algebras over the
localization $KU[1/2]$ is $\Bbb Z/8 \times \Bbb Z/2$.
  Using our descent results and an obstruction theory spectral sequence, we
also study Azumaya algebras over the real K-theory spectrum $KO$ which become
Morita-trivial $KU$-algebras. We show that there exist exactly two Morita
equivalence classes of these. The nontrivial Morita equivalence class is
realized by an "exotic" $KO$-algebra with the same coefficient ring as
$End_{KO}(KU)$. This requires a careful analysis of what happens in the
homotopy fixed-point spectral sequence for the Picard space of $KU$, previously
studied by Mathew and Stojanoska.


  Research has shown that various environmental factors impact smartphone
interaction and lead to Situationally-Induced Impairments and Disabilities. In
this work we discuss the importance of thoroughly understanding the effects of
these situational impairments on smartphone interaction. We argue that
systematic investigation of the effects of different situational impairments is
quintessential for conducting successful research in the field of SIIDs that
might lead to building appropriate sensing, modelling, and adapting techniques.
We also provide insights for future work identifying potential directions to
conduct research in SIIDs.


  In this paper, some new characterizations on Gorenstein projective, injective
and flat modules over commutative noetherian local ring are given.


  Topological Weyl semimetals can host Weyl nodes with monopole charges in
momentum space. How to detect the signature of the monopole charges in quantum
transport remains a challenging topic. Here, we reveal the connection between
the parity of monopole charge in topological semimetals and the quantum
interference corrections to the conductivity. We show that the parity of
monopole charge determines the sign of the quantum interference correction,
with odd and even parity yielding the weak anti-localization and weak
localization effects, respectively. This is attributed to the Berry phase
difference between time-reversed trajectories circulating the Fermi sphere that
encloses the monopole charges. From standard Feynman diagram calculations, we
further show that the weak-field magnetoconductivity at low temperatures is
proportional to $+\sqrt{B}$ in double-Weyl semimetals and $-\sqrt{B}$ in Weyl
semimetals, respectively, which could be verified experimentally.


  Using the continuity of the scalar $\Psi_2$ (the mass aspect) at null
infinity through $i_o$ we show that the space of radiative solutions of general
relativity can be thought of a fibered space where the value of $\Psi_2$ at
$i_o$ plays the role of the base space. We also show that the restriction of
the available symplectic form to each ``fiber'' is degenerate. By finding the
orbit manifold of this degenerate direction we obtain the reduced phase space
for the radiation data. This reduced phase space posses a global structure,
i.e., it does not distinguishes between future or past null infinity. Thus, it
can be used as the space of quantum gravitons. Moreover, a Hilbert space can be
constructed on each ``fiber'' if an appropriate definition of scalar product is
provided. Since there is no natural correspondence between the Hilbert spaces
of different foliations they define superselection sectors on the space of
asymptotic quantum states.


  Device fingerprints like sensor pattern noise (SPN) are widely used for
provenance analysis and image authentication. Over the past few years, the
rapid advancement in digital photography has greatly reshaped the pipeline of
image capturing process on consumer-level mobile devices. The flexibility of
camera parameter settings and the emergence of multi-frame photography
algorithms, especially high dynamic range (HDR) imaging, bring new challenges
to device fingerprinting. The subsequent study on these topics requires a new
purposefully built image dataset. In this paper, we present the Warwick Image
Forensics Dataset, an image dataset of more than 58,600 images captured using
14 digital cameras with various exposure settings. Special attention to the
exposure settings allows the images to be adopted by different multi-frame
computational photography algorithms and for subsequent device fingerprinting.
The dataset is released as an open-source, free for use for the digital
forensic community.


  Source analysis of Electroencephalography (EEG) data requires the computation
of the scalp potential induced by current sources in the brain. This so-called
EEG forward problem is based on an accurate estimation of the volume conduction
effects in the human head, represented by a partial differential equation which
can be solved using the finite element method (FEM). FEM offers flexibility
when modeling anisotropic tissue conductivities but requires a volumetric
discretization, a mesh, of the head domain. Structured hexahedral meshes are
easy to create in an automatic fashion, while tetrahedral meshes are better
suited to model curved geometries. Tetrahedral meshes thus offer better
accuracy, but are more difficult to create. Methods: We introduce CutFEM for
EEG forward simulations to integrate the strengths of hexahedra and tetrahedra.
It belongs to the family of unfitted finite element methods, decoupling mesh
and geometry representation. Following a description of the method, we will
employ CutFEM in both controlled spherical scenarios and the reconstruction of
somatosensory evoked potentials. Results: CutFEM outperforms competing FEM
approaches with regard to numerical accuracy, memory consumption and
computational speed while being able to mesh arbitrarily touching compartments.
Conclusion: CutFEM balances numerical accuracy, computational efficiency and a
smooth approximation of complex geometries that has previously not been
available in FEM-based EEG forward modeling.


  Context: Smart TVs have become one of the most popular television types. Many
app developers and service providers have designed TV versions for their
smartphone applications. Despite the extensive studies on mobile app analysis,
its TV equivalents receive far too little attention. The relationship between
phone and TV has not been the subject of research works. Objective: In this
paper, we aim to characterize the relationship between smartphone and smart TV
apps. To fill this gap, we conduct a comparative study on smartphone and smart
TV apps in this work, which is the starting and fundamental step to uncover the
domain-specific challenges. Method: We gather a large-scale phone/TV app pairs
from Google Play Store. We then analyzed the app pairs quantitatively and
qualitatively from a variety of perspectives, including non-code (e.g.,
metadata, resources, permissions, etc.), code (e.g., components, methods, user
interactions, etc.), security and privacy (e.g., reports of AndroBugs and
FlowDroid). Results: Our experimental results indicate that (1) the code of the
smartphone and TV apps can be released in the same app package or in separate
app packages with the same package name; (2) 43% of resource files and 50% of
code methods are reused between phone/TV app pairs; (3) TV and phone versions
of the same app often encounter different kinds of security vulnerabilities;
and (4) TV apps encounter fewer user interactions than their phone versions,
but the type of user interaction events, surprisingly, are similar between
phone/TV apps. Conclution: Our findings are valuable for developers and
academics in comprehending the TV app ecosystem by providing additional insight
into the migration of phone apps to TVs and the design mechanism of analysis
tools for TV apps.


  An $r$-graph $G$ is a pair $(V,E)$ such that $V$ is a set and $E$ is a family
of $r$-element subsets of $V$. The \emph{independence number} $\alpha(G)$ of
$G$ is the size of a largest subset $I$ of $V$ such that no member of $E$ is a
subset of $I$. The \emph{transversal number} $\tau(G)$ of $G$ is the size of a
smallest subset $T$ of $V$ that intersects each member of $E$. $G$ is said to
be \emph{connected} if for every distinct $v$ and $w$ in $V$ there exists a
\emph{path} from $v$ to $w$ (that is, a sequence $e_1, \dots, e_p$ of members
of $E$ such that $v \in e_1$, $w \in e_p$, and if $p \geq 2$, then for each $i
\in \{1, \dots, p-1\}$, $e_i$ intersects $e_{i+1}$). The \emph{degree} of a
member $v$ of $V$ is the number of members of $E$ that contain $v$. The maximum
of the degrees of the members of $V$ is denoted by $\Delta(G)$. We show that
for any $1 \leq k < n$, if $G = (V,E)$ is a connected $r$-graph, $|V| = n$, and
$\Delta(G) = k$, then \[\alpha(G) \leq n - \left \lceil \frac{n-1}{k(r-1)}
\right \rceil, \quad \tau(G) \geq \left \lceil \frac{n-1}{k(r-1)} \right
\rceil,\] and these bounds are sharp. The two bounds are equivalent.


  We study beam-transverse and normal single-spin asymmetry for electron-proton
inelastic scattering in the resonance region for the case where a pion is
observed in the final state. There is no beam single-spin asymmetry if the
observed particle has single-photon exchange as its only interaction, but this
is naturally circumvented when one observes a strongly interacting final state
particle. The asymmetries are not large as there is an electron mass divided by
momentum transfer suppression. We present results for the cases where the final
electron and a pion are both observed, with asymmetries of order tens of ppm,
and where only a final pion is observed, with asymmetries of order one ppm.


  It is shown that in equilibrium a canonical ensemble of particles with
two-particle interaction the Gibbs distribution function may be expressed
uniquely through a pair distribution function. It means, that for given values
of the particle number $N$, volume $V$, and temperature $T$, the pair
distribution function contains as many information about the system as a full
Gibbs distribution. The latter is represented as a series expansion in the pair
distribution function. A recurrence relation system is constructed, which
allows all terms of this expansion to be calculated successively.


  Let $X$ be a projective integral scheme with endomorphism $\sigma$, where
$\sigma$ is finite, but not an automorphism. We examine noncommutative
ampleness of bimodules defined by $\sigma$. In contrast to the automorphism
case, one-sided ampleness is possible. We also find that rings and bimodule
algebras associated with $\sigma$ are not noetherian.


  We consider light ray reflections in $n$-dimensional semi-infinite tube, for
$n\geq 3$, made of Lambertian material. The source of light is placed far away
from the exit, and the light ray is assumed to reflect so that the distribution
of the direction of the reflected light ray has the density proportional to the
cosine of the angle with the normal vector. We present new results on the exit
distribution from the tube, and generalizations of some theorems from an
earlier article, where the dimension was limited to $n=2$ and $3$.


  A quasistatic model due to Ericksen and Leslie describing incompressible
liquid crystals is studied for a general class of free energies. Global
existence of weak solutions is proven via a Galerkin approximation with
eigenfunctions of a strongly elliptic operator. A novelty is that the principal
part of the differential operator appearing in the director equation can be
nonlinear.


  Recovering surface albedos from photogrammetric images for realistic
rendering and synthetic environments can greatly facilitate its downstream
applications in VR/AR/MR and digital twins. The textured 3D models from
standard photogrammetric pipelines are suboptimal to these applications because
these textures are directly derived from images, which intrinsically embedded
the spatially and temporally variant environmental lighting information, such
as the sun illumination, direction, causing different looks of the surface,
making such models less realistic when used in 3D rendering under synthetic
lightings. On the other hand, since albedo images are less variable by
environmental lighting, it can, in turn, benefit basic photogrammetric
processing. In this paper, we attack the problem of albedo recovery for aerial
images for the photogrammetric process and demonstrate the benefit of albedo
recovery for photogrammetry data processing through enhanced feature matching
and dense matching. To this end, we proposed an image formation model with
respect to outdoor aerial imagery under natural illumination conditions; we
then, derived the inverse model to estimate the albedo by utilizing the typical
photogrammetric products as an initial approximation of the geometry. The
estimated albedo images are tested in intrinsic image decomposition,
relighting, feature matching, and dense matching/point cloud generation
results. Both synthetic and real-world experiments have demonstrated that our
method outperforms existing methods and can enhance photogrammetric processing.


  We review the known results about characteristically nilpotent complex Lie
algebras, as well as we comment recent developements in the theory.


  The PageRank of a graph is a scalar function defined on the node set of the
graph which encodes nodes centrality information of the graph. In this article,
we use the PageRank function along with persistent homology to obtain a
scalable graph descriptor and utilize it to compare the similarities between
graphs. For a given graph $G(V,E)$, our descriptor can be computed in
$O(|E|\alpha(|V|))$, where $\alpha$ is the inverse Ackermann function which
makes it scalable and computable on massive graphs. We show the effectiveness
of our method by utilizing it on multiple shape mesh datasets.


  We consider possible violations of the equivalence principle through the
exchange of a light `dilaton-like' scalar field. Using recent work on the
quark-mass dependence of nuclear binding, we find that the dilaton-quark-mass
coupling induces significant equivalence-principle-violating effects varying
like the inverse cubic root of the atomic number - A^{-1/3}. We provide a
general parameterization of the scalar couplings, but argue that two parameters
are likely to dominate the equivalence-principle phenomenology. We indicate the
implications of this framework for comparing the sensitivities of current and
planned experimental tests of the equivalence principle.


  We report the first observation of two-dimensional incommensurate magnetic
fluctuations in the layered metallic perovskite Sr3Ru2O7. The wavevectors where
the magnetic fluctuations are strongest are different from those observed in
the superconducting single layer ruthenate Sr2RuO4 and appear to be determined
by Fermi surface nesting. No antiferromagnetic ordering is observed for
temperatures down to 1.5K. For temperatures T<20K, the fluctuations become
predominately ferromagnetic. Our inelastic neutron scattering measurements
provide concrete evidence of the coexistence of competing interactions in
Sr3Ru2O7 and of the low energy scale of the fluctuations.


  The understanding of magnetic and electronic properties of rare-earth
intermetallics is summarized. The properties of NdNi5 or ErNi5 are understood
by considering a few electronic subsystems like the f electronic subsystem and
the conduction-electron subsystem. The localized f electrons can give a
substantial contribution to the low temperature specific heat with the entropy
of R ln2 in case of Kramers ions. In this view the heavy-fermion behaviour is
related with the removal of the Kramers degeneracy of the ground state of the f
electronic subsystem.


  The deployment of Deep Neural Networks (DNNs) on end-nodes at the extreme
edge of the Internet-of-Things is a critical enabler to support pervasive Deep
Learning-enhanced applications. Low-Cost MCU-based end-nodes have limited
on-chip memory and often replace caches with scratchpads, to reduce area
overheads and increase energy efficiency -- requiring explicit DMA-based memory
transfers between different levels of the memory hierarchy. Mapping modern DNNs
on these systems requires aggressive topology-dependent tiling and
double-buffering. In this work, we propose DORY (Deployment Oriented to memoRY)
- an automatic tool to deploy DNNs on low cost MCUs with typically less than
1MB of on-chip SRAM memory. DORY abstracts tiling as a Constraint Programming
(CP) problem: it maximizes L1 memory utilization under the topological
constraints imposed by each DNN layer. Then, it generates ANSI C code to
orchestrate off- and on-chip transfers and computation phases. Furthermore, to
maximize speed, DORY augments the CP formulation with heuristics promoting
performance-effective tile sizes. As a case study for DORY, we target
GreenWaves Technologies GAP8, one of the most advanced parallel ultra-low power
MCU-class devices on the market. On this device, DORY achieves up to 2.5x
better MAC/cycle than the GreenWaves proprietary software solution and 18.1x
better than the state-of-the-art result on an STM32-F746 MCU on single layers.
Using our tool, GAP-8 can perform end-to-end inference of a 1.0-MobileNet-128
network consuming just 63 pJ/MAC on average @ 4.3 fps - 15.4x better than an
STM32-F746. We release all our developments - the DORY framework, the optimized
backend kernels, and the related heuristics - as open-source software.


  Motivated by the practical interest in the third-body perturbation as a
natural cleaning mechanism for high-altitude Earth orbits, we investigate the
dynamics stemming from the secular Hamiltonian associated with the lunar
perturbation, assuming that the Moon lies on the ecliptic plane. The secular
Hamiltonian defined in that way is characterized by two timescales. We compare
the location and stability of the fixed points associated with the secular
Hamiltonian averaged with respect to the fast variable with the corresponding
periodic orbits of the full system. Focusing on the orbit of the Galileo
satellites, it turns out that the two dynamics cannot be confused, as the
relative difference depends on the ratio between the semi-major axis of Galileo
and the one of the Moon, that is not negligible.
  The result is relevant to construct rigorously the Arnold diffusion mechanism
that can drive a natural growth in eccentricity that allows a satellite
initially on a circular orbit in Medium Earth Orbit to reenter into the Earth's
atmosphere.


  Assessment of spontaneous movements can predict the long-term developmental
disorders in high-risk infants. In order to develop algorithms for automated
prediction of later disorders, highly precise localization of segments and
joints by infant pose estimation is required. Four types of convolutional
neural networks were trained and evaluated on a novel infant pose dataset,
covering the large variation in 1 424 videos from a clinical international
community. The localization performance of the networks was evaluated as the
deviation between the estimated keypoint positions and human expert
annotations. The computational efficiency was also assessed to determine the
feasibility of the neural networks in clinical practice. The best performing
neural network had a similar localization error to the inter-rater spread of
human expert annotations, while still operating efficiently. Overall, the
results of our study show that pose estimation of infant spontaneous movements
has a great potential to support research initiatives on early detection of
developmental disorders in children with perinatal brain injuries by
quantifying infant movements from video recordings with human-level
performance.


  The physics of M5 branes placed near an M9 plane on an A-type ALE singularity
exhibits a variety of phenomena that introduce additional massless degrees of
freedom. There are tensionless strings whenever two M5 branes coincide or
whenever an M5 brane approaches the M9 plane. These systems do not admit a
low-energy Lagrangian description so new techniques are desirable to shed light
on the physics of these phenomena. The 6-dimensional N=(1,0) world-volume
theory on the M5 branes is composed of massless vector, tensor, and hyper
multiplets, and has two branches of the vacuum moduli space where either the
scalar fields in the tensor or hyper multiplets receive vacuum expectation
values. Focusing on the Higgs branch of the low-energy theory, previous works
suggest the conjecture that a new Higgs branch arises whenever a BPS-string
becomes tensionless. Consequently, a single theory admits a multitude of Higgs
branches depending on the types of tensionless strings in the spectrum. The two
main phenomena discrete gauging and small E8 instanton transition can be
treated in a concise and effective manner by means of Coulomb branches of
3-dimensional N=4 gauge theories. In this paper, a formalism is introduced that
allows to derive a novel object from a brane configuration, called the magnetic
quiver. The main features are as follows: (i) the 3d Coulomb branch of the
magnetic quiver yields the Higgs branch of the 6d system, (ii) all discrete
gauging and E8 instanton transitions have an explicit brane realisation, and
(iii) exceptional symmetries arise directly from brane configurations. The
formalism facilitates the description of Higgs branches at finite and infinite
gauge coupling as spaces of dressed monopole operators.


  As the number of observed Gamma-Ray Bursts (GRBs) continues to grow,
follow-up resources need to be used more efficiently in order to maximize
science output from limited telescope time. As such, it is becoming
increasingly important to rapidly identify bursts of interest as soon as
possible after the event, before the afterglows fade beyond detectability.
Studying the most distant (highest redshift) events, for instance, remains a
primary goal for many in the field. Here we present our Random forest Automated
Triage Estimator for GRB redshifts (RATE GRB-z) for rapid identification of
high-redshift candidates using early-time metrics from the three telescopes
onboard Swift. While the basic RATE methodology is generalizable to a number of
resource allocation problems, here we demonstrate its utility for
telescope-constrained follow-up efforts with the primary goal to identify and
study high-z GRBs. For each new GRB, RATE GRB-z provides a recommendation -
based on the available telescope time - of whether the event warrants
additional follow-up resources. We train RATE GRB-z using a set consisting of
135 Swift bursts with known redshifts, only 18 of which are z > 4.
Cross-validated performance metrics on this training data suggest that ~56% of
high-z bursts can be captured from following up the top 20% of the ranked
candidates, and ~84% of high-z bursts are identified after following up the top
~40% of candidates. We further use the method to rank 200+ Swift bursts with
unknown redshifts according to their likelihood of being high-z.


  We investigate effects of doped holes' hopping on Neel order in the
two-dimensional Hubbard model. Semiclassical staggered moments are computed by
solving saddle point equations derived from a path-integral formalism. Effects
of quantum fluctuations are taken into account by the Schwinger boson mean
field theory. We argue that hopping of doped holes is ineffective in
suppressing Neel order compared to rapid supprestion of Neel order in
high-temperature superconductors. After destruction of Neel order, the quantum
disordered phase sets in. Taking the strong coupling limit in the quantum
disordered phase leads to a model of spinless fermions and bosons but no gauge
field interaction.


  The recent report of an association of the gravitational-wave (GW) binary
black hole (BBH) merger GW190521 with a flare in the Active Galactic Nuclei
(AGN) J124942.3+344929 has generated tremendous excitement. However, GW190521
has one of the largest localization volumes amongst all of the GW events
detected so far. The 90\% localization volume likely contains $7,400$
unobscured AGN brighter than $g \leq 20.5$ AB mag, and it results in a $\gtrsim
70\%$ probability of chance coincidence for an AGN flare consistent with the GW
event. We present a Bayesian formalism to estimate the confidence of an AGN
association by analyzing a population of BBH events with dedicated follow-up
observations. Depending on the fraction of BBH arising from AGNs, counterpart
searches of $\mathcal{O}(1)-\mathcal{O}(100)$ GW events are needed to establish
a confident association, and more than an order of magnitude more for searches
without followup (i.e, using only the locations of AGNs and GW events).
Follow-up campaigns of the top $\sim 5\%$ (based on volume localization and
binary mass) of BBH events with total rest frame mass $\ge 50~M_\odot$ are
expected to establish a confident association during the next LIGO/Virgo/KAGRA
observing run (O4), as long as the true value of the fraction of BBH giving
rise to AGN flares is $>0.1$. Our formalism allows us to jointly infer
cosmological parameters from a sample of BBH events that include chance
coincidence flares. Until the confidence of AGN associations is established,
the probability of chance coincidence must be taken into account to avoid
biasing astrophysical and cosmological constraints.


  Finding the shortest path distance between an arbitrary pair of vertices is a
fundamental problem in graph theory. A tremendous amount of research has been
successfully attempted on this problem, most of which is limited to static
graphs. Due to the dynamic nature of real-world networks, there is a pressing
need to address this problem for dynamic networks undergoing changes. In this
paper, we propose an \emph{online incremental} method to efficiently answer
distance queries over very large dynamic graphs. Our proposed method
incorporates incremental update operations, i.e. edge and vertex additions,
into a highly scalable framework of answering distance queries. We
theoretically prove the correctness of our method and the preservation of
labelling minimality. We have also conducted extensive experiments on 12 large
real-world networks to empirically verify the efficiency, scalability, and
robustness of our method.


  The policy gradient approach is a flexible and powerful reinforcement
learning method particularly for problems with continuous actions such as robot
control. A common challenge in this scenario is how to reduce the variance of
policy gradient estimates for reliable policy updates. In this paper, we
combine the following three ideas and give a highly effective policy gradient
method: (a) the policy gradients with parameter based exploration, which is a
recently proposed policy search method with low variance of gradient estimates,
(b) an importance sampling technique, which allows us to reuse previously
gathered data in a consistent way, and (c) an optimal baseline, which minimizes
the variance of gradient estimates with their unbiasedness being maintained.
For the proposed method, we give theoretical analysis of the variance of
gradient estimates and show its usefulness through extensive experiments.


  The broad band spectra of two Swift/BAT AGNs obtained from Suzaku follow-up
observations are studied: NGC 612 and NGC 3081. Fitting with standard models,
we find that both sources show similar spectra characterized by a heavy
absorption with $N_{\rm{H}} \simeq 10^{24} \ \rm{cm}^{-2}$, the fraction of
scattered light is $f_{\rm{scat}} = 0.5-0.8%$, and the solid angle of the
reflection component is $\Omega/2\pi = 0.4-1.1$. To investigate the geometry of
the torus, we apply numerical spectral models utilizing Monte Carlo simulations
by Ikeda et al. (2009) to the Suzaku spectra. We find our data are well
explained by this torus model, which has four geometrical parameters. The fit
results suggest that NGC 612 has the torus half opening-angle of $\simeq
60^{\circ}-70^{\circ}$ and is observed from a nearly edge-on angle with a small
amount of scattering gas, while NGC 3081 has a very small opening angle $\simeq
15^\circ$ and is observed on a face-on geometry, more like the deeply buried
"new type" AGNs found by Ueda et al. (2007). We demonstrate the potential power
of direct application of such numerical simulations to the high quality broad
band spectra to unveil the inner structure of AGNs.


  In transition metal dichalcogenides the spin-orbit interaction affects
differently the conduction and valence band energies as functions of $k$ and
the band gap is large. Consequently, when a perpendicular magnetic field $B$ is
applied the conduction and valence band Landau levels are also different and
this leads to a splitting of the interband optical absorption lines in both the
absence and presence of an external electric field $E_{z}$. When $B$ and
$E_{z}$ are present the peaks in the imaginary part of the Hall conductivity
give two distinct contributions of opposite sign to the interband spectrum. The
real part of the right- and left-handed interband conductivity, however,
retains its two-peak structure but the peaks are shifted in energy and
amplitude with respect to each other in contrast with graphene. The response of
the intraband conductivity is significantly modified when the Fermi energy
$E_{F}$ and the field $B$ are varied. Its optical spectral weight is found to
increase with $E_{F}$ in contrast with the decrease observed in graphene.
Further, the position and amplitude of the intraband response depends on the
field $B$. The absorption peaks vary linearly with $B$ for all fields similar
to bilayer graphene for low fields but in contrast with the high-field
$\sqrt{B}$ dependence in it.


  In the above paper, the optimal-ordered successive interference cancellation
(SIC) detector proposed for multiple input multiple output (MIMO) systems was
claimed to require a lower computational complexity than the optimal-ordered
SIC detector proposed in the paper "An Improved Square-Root Algorithm for
V-BLAST Based on Efficient Inverse Cholesky Factorization" (IEEE Trans.
Wireless Commun., vol. 10, no. 1, Jan. 2011), since several incorrect
complexities were quoted or claimed. In this comment, we revise the incorrect
complexities, to draw the conclusion that the above-mentioned two detectors
actually require the same dominant complexity.


  It is shown that Misner metric can be obtained as solution of dynamo waves
equations and Friedmann hyperbolic metrics are obtained when the dynamo waves
are absent. In the case of dynamo waves ICM fields are computed and galactic
dynamos are obtained.


  Even for common NLP tasks, sufficient supervision is not available in many
languages -- morphological tagging is no exception. In the work presented here,
we explore a transfer learning scheme, whereby we train character-level
recurrent neural taggers to predict morphological taggings for high-resource
languages and low-resource languages together. Learning joint character
representations among multiple related languages successfully enables knowledge
transfer from the high-resource languages to the low-resource ones, improving
accuracy by up to 30% over a monolingual model.


  We report the X-ray study for the pyrochlore oxide Cd2Re2O7. Two
symmetry-lowering structural transitions were observed at Ts1=200K and
Ts2=120K. The former is of the second order from the ideal cubic pyrochlore
structure with space group Fd-3m to a tetragonally distorted structure with
I-4m2, while the latter is of the first order likely to another tetragonal
space group I4122. We discuss the feature of the lattice deformation.


  We report on a comprehensive study of the unique adhesive properties of mats
of polymethylmethacrylate (PMMA) nanofibers produced by electrospinning. Fibers
are deposited on glass, varying the diameter and the relative orientation of
the polymer filaments (random vs aligned configuration). While no significant
variation is observed in the static contact angle (about 130{\deg}) of
deposited water drops upon changing the average fiber diameter up to the
micrometer scale, fibers are found to exhibit unequalled water adhesion. Placed
vertically, they can hold up water drops as large as 60 microL, more than twice
the values typically obtained with hairy surfaces prepared by different
methods. For aligned fibers with anisotropic wetting behavior, the maximum
volume measured in the direction perpendicular to the fibers goes up to 90
{\mu}L. This work suggests new routes to tailor the wetting behavior on
extended areas by nanofiber coatings, with possible applications in adsorbing
and catalytic surfaces, microfluidic devices, and filtration technologies.


  Deformable object manipulation stands as one of the most captivating yet
formidable challenges in robotics. While previous techniques have predominantly
relied on learning latent dynamics through demonstrations, typically
represented as either particles or images, there exists a pertinent limitation:
acquiring suitable demonstrations, especially for long-horizon tasks, can be
elusive. Moreover, basing learning entirely on demonstrations can hamper the
model's ability to generalize beyond the demonstrated tasks. In this work, we
introduce a demonstration-free hierarchical planning approach capable of
tackling intricate long-horizon tasks without necessitating any training. We
employ large language models (LLMs) to articulate a high-level, stage-by-stage
plan corresponding to a specified task. For every individual stage, the LLM
provides both the tool's name and the Python code to craft intermediate subgoal
point clouds. With the tool and subgoal for a particular stage at our disposal,
we present a granular closed-loop model predictive control strategy. This
leverages Differentiable Physics with Point-to-Point correspondence
(DiffPhysics-P2P) loss in the earth mover distance (EMD) space, applied
iteratively. Experimental findings affirm that our technique surpasses multiple
benchmarks in dough manipulation, spanning both short and long horizons.
Remarkably, our model demonstrates robust generalization capabilities to novel
and previously unencountered complex tasks without any preliminary
demonstrations. We further substantiate our approach with experimental trials
on real-world robotic platforms. Our project page:
https://qq456cvb.github.io/projects/donut.


  The propeller regime of disk accretion to a rapidly rotating magnetized star
is investigated here for the first time by axisymmetric 2.5D
magnetohydrodynamic simulations. An expanded, closed magnetosphere forms in
which the magnetic field is predominantly toroidal. A smaller fraction of the
star's poloidal magnetic flux inflates vertically, forming a magnetically
dominated tower. Matter accumulates in the equatorial region outside
magnetosphere and accretes to the star quasi-periodically through elongated
funnel streams which cause the magnetic field to reconnect. The star spins-down
owing to the interaction of the closed magnetosphere with the disk. For the
considered conditions, the spin-down torque varies with the angular velocity of
the star omega* as omega*^1.3 for fixed mass accretion rate. The propeller
stage may be important in the evolution of X-ray pulsars, cataclysmic variables
and young stars. In particular, it may explain the present slow rotation of the
classical T Tauri stars.


  We characterize nonforking (Morley) sequences in dependent theories in terms
of a generalization of Poizat's special sequences and show that average types
of Morley sequences are stationary over their domains. We characterize
generically stable types in terms of the structure of the "eventual" type. We
then study basic properties of "strict Morley sequences", based on Shelah's
notion of strict nonforking. In particular we prove "Kim's lemma" for such
sequences, and a weak version of local character.


  We study the supersymmetric hybrid model near and after the end of inflation.
As usual, we reduce the model to a purely scalar hybrid model on the level of
the classical fields. But on the level of quantum fluctuations and their
backreaction we take into account all superpartners of the waterfall field in a
large-N approximation. The evolution after slow roll displays two phases with a
different characteristic behaviour of the classical and fluctuation fields. We
find that the fluctuations of the pseudoscalar superpartner are of particular
importance in the late time phase. The motion of the waterfall field towards
its classical expectation value is found to be very slow and suggests a rather
flat potential and a stochastic force.


  We investigate the existence of self-dual configurations in the restricted
gauged baby Skyrme model enlarged with a $Z_2$--symmetry, which introduces a
real scalar field. For such a purpose, we implement the Bogomol'nyi procedure
that provides a lower bound for the energy and the respective self-dual
equations whose solutions saturate such a bound. Aiming to solve the self-dual
equations, we specifically focused on a class of topological structures called
compacton. We obtain the corresponding numerical solutions within two distinct
scenarios, each defined by a scalar field, allowing us to describe different
magnetic media. Finally, we analyze how the compacton profiles change when
immersed in each medium.


  Human activities are hugely restricted by COVID-19, recently. Robots that can
conduct inter-floor navigation attract much public attention, since they can
substitute human workers to conduct the service work. However, current robots
either depend on human assistance or elevator retrofitting, and fully
autonomous inter-floor navigation is still not available. As the very first
step of inter-floor navigation, elevator button segmentation and recognition
hold an important position. Therefore, we release the first large-scale
publicly available elevator panel dataset in this work, containing 3,718 panel
images with 35,100 button labels, to facilitate more powerful algorithms on
autonomous elevator operation. Together with the dataset, a number of deep
learning based implementations for button segmentation and recognition are also
released to benchmark future methods in the community. The dataset will be
available at \url{https://github.com/zhudelong/elevator_button_recognition


  While the continuous Entropic Optimal Transport (EOT) field has been actively
developing in recent years, it became evident that the classic EOT problem is
prone to different issues like the sensitivity to outliers and imbalance of
classes in the source and target measures. This fact inspired the development
of solvers that deal with the unbalanced EOT (UEOT) problem $-$ the
generalization of EOT allowing for mitigating the mentioned issues by relaxing
the marginal constraints. Surprisingly, it turns out that the existing solvers
are either based on heuristic principles or heavy-weighted with complex
optimization objectives involving several neural networks. We address this
challenge and propose a novel theoretically-justified, lightweight, unbalanced
EOT solver. Our advancement consists of developing a novel view on the
optimization of the UEOT problem yielding tractable and a non-minimax
optimization objective. We show that combined with a light parametrization
recently proposed in the field our objective leads to a fast, simple, and
effective solver which allows solving the continuous UEOT problem in minutes on
CPU. We prove that our solver provides a universal approximation of UEOT
solutions and obtain its generalization bounds. We give illustrative examples
of the solver's performance.


  In the framework of the extended Linear Sigma Model (eLSM) we investigate the
masses and decays of the three scalar-isoscalar resonances $f_{0}(1370)$,
$f_{0}(1500)$ and $f_{0}(1710)$. The degrees of freedom of the eLSM are
(pseudo)scalars and (axial)vectors as well as the scalar glueball. Although
still preliminary, present results, based on the physical masses of the above
mentioned resonances, show that $f_{0}(1710)$ is the predominantly glueball
state. However, acceptable decays for this resonance can be obtained only for a
(very) large gluon condensate.


  In this paper we study a stochastic version of an inviscid shell model of
turbulence with multiplicative noise. The deterministic counterpart of this
model is quite general and includes inviscid GOY and Sabra shell models of
turbulence. We prove global weak existence and uniqueness of solutions for any
finite energy initial condition. Moreover energy dissipation of the system is
proved in spite of its formal energy conservation.


  The delensing of cosmic microwave background (CMB) maps will be increasingly
valuable for extracting as much information as possible from future CMB
surveys. Delensing provides many general benefits, including sharpening of the
acoustic peaks, more accurate recovery of the damping tail, and reduction of
lensing-induced $B$-mode power. In this paper we present several applications
of delensing focused on testing theories of early-universe inflation with
observations of the CMB. We find that delensing the CMB results in improved
parameter constraints for reconstructing the spectrum of primordial curvature
fluctuations, probing oscillatory features in the primordial curvature
spectrum, measuring the spatial curvature of the universe, and constraining
several different models of isocurvature perturbations. In some cases we find
that delensing can recover almost all of the constraining power contained in
unlensed spectra, and it will be a particularly valuable analysis technique to
achieve further improvements in constraints for model parameters whose
measurements are not expected to improve significantly when utilizing only
lensed CMB maps from next-generation CMB surveys. We also quantify the
prospects of testing the single-field inflation tensor consistency condition
using delensed CMB data; we find it to be out of reach of current and proposed
experimental technology and advocate for alternative detection methods.


  We investigate the main tensions within the current standard model of
cosmology from the perspective of the main statistics of cosmic voids, using
the final BOSS DR12 data set. For this purpose, we present the first estimate
of the $S_8\equiv \sigma_8\sqrt{\Omega_{\rm m}/0.3}$ and $H_0$ parameters
obtained from void number counts and shape distortions. To analyze void counts
we relied on an extension of the popular volume-conserving model for the void
size function, tailored to the application on data, including geometric and
dynamic distortions. We calibrated the two nuisance parameters of this model
with the official BOSS collaboration mock catalogs and propagated their
uncertainty through the statistical analysis of the BOSS void number counts.
The constraints from void shapes come from the study of the geometric
distortions of the stacked void-galaxy cross-correlation function. In this work
we focus our analysis on the $\Omega_{\rm m}$-$\sigma_8$ and $\Omega_{\rm
m}$-$H_0$ parameter planes and derive the marginalized constraints $S_8 =
0.813^{+0.093}_{-0.068}$ and $H_0 = 67.3^{+10.0}_{-9.1} \ \mathrm{km} \
\mathrm{s}^{-1} \ \mathrm{Mpc}^{-1}$, which are fully compatible with
constraints from the literature. These results are expected to notably improve
in precision when analyzed jointly with independent probes and will open a new
viewing angle on the rising cosmological tensions in the near future.


  Structural and energy stability results for a new class of decahedral
structural motif termed decmon (Montejano's decahedra) are presented. After
making proper truncations to the regular icosahedron, this structural motif
presents exposed <100> and <111> facets, whose energetic competition make the
structures very stable. It is also identified structural transitions as a
function of the cluster size, the appearing and competition of surface
reconstruction, and an outline for a path transformation from the Mackay
icosahedra (I_h) to the regular decahedra (D_h) symmetry structures, as well as
experimental evidence of the decmon decahedral motif in metallic nanoparticles.


  The Galactic Central Molecular Zone (CMZ) is a region containing massive and
dense molecular clouds, with dynamics driven by a variety of energy sources
including a massive black hole. It is thus the nearest template for
understanding physical processes in extragalactic nuclei. The CMZ's neutral
interstellar gas has been mapped spectrally in many neutral atomic and
molecular gas tracers, but the ionized and CO-dark H2 regions are less well
traced spectroscopically. We mapped the fine structure line of C+ at 158
microns, [C II], to identify and characterize features of the ionized gas in
the CMZ, including UV irradiated neutral gas, photon dominated regions (PDRs),
CO-dark H2 gas, and highly ionized gas. We observed the [C II] 158-micron fine
structure line with high spectral resolution using Herschel HIFI with two
perpendicular On-the-Fly strip scans, along l = -0.8 to +0.8 and b = -0.8 to
+0.8, both centered on (l,b) = (0,0). We analyzed the spatial-velocity
distribution of the [C II] data and compared them to those of [C I] and CO, and
to dust continuum maps, in order to determine the properties and distribution
of the UV irradiated gas and its dynamics within the CMZ. The longitude- and
latitude-velocity maps of [C II] trace portions of the orbiting open gas
streams of dense molecular clouds, the cloud G0.253+0.016, also known as the
Brick, the Arched Filaments, and the ionized gas near Sgr A and Sgr B2. We use
the [C II] and auxiliary data to determine the physical and dynamical
properties of these CMZ features. The [C II] emission arises primarily from
dense PDRs and highly ionized gas, and is an important tracer of the kinematics
and physical conditions of this gas.


  Current status of (the lack of) understanding Blazhko effect is reviewed. We
focus mostly on the various components of the failure of the models and touch
upon the observational issues only at a degree needed for the theoretical
background. Attention is to be paid to models based on radial mode resonances,
since they seem to be not fully explored yet, especially if we consider
possible non-standard effects (e.g., heavy element enhancement). To aid further
modeling efforts, we stress the need for accurate time-series spectral line
analysis to reveal any possible non-radial component(s) and thereby let to
include (or exclude) non-radial modes in explaining the Blazhko phenomenon.


  Randomized matrix compression techniques, such as the Johnson-Lindenstrauss
transform, have emerged as an effective and practical way for solving
large-scale problems efficiently. With a focus on computational efficiency,
however, forsaking solutions quality and accuracy becomes the trade-off. In
this paper, we investigate compressed least-squares problems and propose new
models and algorithms that address the issue of error and noise introduced by
compression. While maintaining computational efficiency, our models provide
robust solutions that are more accurate--relative to solutions of uncompressed
least-squares--than those of classical compressed variants. We introduce tools
from robust optimization together with a form of partial compression to improve
the error-time trade-offs of compressed least-squares solvers. We develop an
efficient solution algorithm for our Robust Partially-Compressed (RPC) model
based on a reduction to a one-dimensional search. We also derive the first
approximation error bounds for Partially-Compressed least-squares solutions.
Empirical results comparing numerous alternatives suggest that robust and
partially compressed solutions are effectively insulated against aggressive
randomized transforms.


  Backpropagation is a classic automatic differentiation algorithm computing
the gradient of functions specified by a certain class of simple, first-order
programs, called computational graphs. It is a fundamental tool in several
fields, most notably machine learning, where it is the key for efficiently
training (deep) neural networks. Recent years have witnessed the quick growth
of a research field called differentiable programming, the aim of which is to
express computational graphs more synthetically and modularly by resorting to
actual programming languages endowed with control flow operators and
higher-order combinators, such as map and fold. In this paper, we extend the
backpropagation algorithm to a paradigmatic example of such a programming
language: we define a compositional program transformation from the
simply-typed lambda-calculus to itself augmented with a notion of linear
negation, and prove that this computes the gradient of the source program with
the same efficiency as first-order backpropagation. The transformation is
completely effect-free and thus provides a purely logical understanding of the
dynamics of backpropagation.


  A balanced edge-coloring of the complete graph is an edge-coloring such that
every vertex is incident to each color the same number of times. In this short
note, we present a construction of a balanced edge-coloring with six colors of
the complete graph on $n=13^k$ vertices, for every positive integer $k$, with
no rainbow $K_4$. This solves a problem by Erd\H{o}s and Tuza.


  In this paper, we address a new image forensics task, namely the detection of
fake flood images generated by ClimateGAN architecture. We do so by proposing a
hybrid deep learning architecture including both a detection and a localization
branch, the latter being devoted to the identification of the image regions
manipulated by ClimateGAN. Even if our goal is the detection of fake flood
images, in fact, we found that adding a localization branch helps the network
to focus on the most relevant image regions with significant improvements in
terms of generalization capabilities and robustness against image processing
operations. The good performance of the proposed architecture is validated on
two datasets of pristine flood images downloaded from the internet and three
datasets of fake flood images generated by ClimateGAN starting from a large set
of diverse street images.


  We give the full solution of the following problem: obtain sharp inequalities
between the moduli of smoothness $\omega_\alpha(f,t)_q$ and
$\omega_\beta(f,t)_p$ for $0<p<q\le \infty$. A similar problem for the
generalized $K$-functionals and their realizations between the couples $(L_p,
W_p^\psi)$ and $(L_q, W_q^\varphi)$ is also solved.
  The main tool is the new Hardy-Littlewood-Nikol'skii inequalities. More
precisely, we obtained the asymptotic behavior of the quantity $$ \sup_{T_n}
\frac{\Vert \mathcal{D}(\psi)(T_n)\Vert_q}{\Vert
\mathcal{D}(\varphi)(T_n)\Vert_p},\qquad 0<p<q\le \infty, $$ where the supremum
is taken over all nontrivial trigonometric polynomials $T_n$ of degree at most
$n$ and $\mathcal{D}(\psi), \mathcal{D}(\varphi)$ are the Weyl-type
differentiation operators.
  We also prove the Ulyanov and Kolyada-type inequalities in the Hardy spaces.
Finally, we apply the obtained estimates to derive new embedding theorems for
the Lipschitz and Besov spaces.


  Recently, there has been considerable interest in the study of spontaneous
synchronization, particularly within the framework of the Kuramoto model. The
model comprises oscillators with distributed natural frequencies interacting
through a mean-field coupling, and serves as a paradigm to study
synchronization. In this review, we put forward a general framework in which we
discuss in a unified way known results with more recent developments obtained
for a generalized Kuramoto model that includes inertial effects and noise. We
describe the model from a different perspective, highlighting the long-range
nature of the interaction between the oscillators, and emphasizing the
equilibrium and out-of-equilibrium aspects of its dynamics from a statistical
physics point of view. In the first main section, we introduce the model and
discuss for the noiseless and noisy dynamics and unimodal frequency
distributions the synchronization transition that occurs in the stationary
state. In the second section, we introduce the generalized model, and discuss
its synchronization phase diagram for unimodal frequency distributions. In the
third section, we describe deviations from the mean-field setting of the
Kuramoto model by considering the generalized dynamics on a one-dimensional
periodic lattice on the sites of which the oscillators reside and interact with
a coupling that decays as an inverse power-law of their separation. For two
specific cases, namely, in the absence of noise and inertia, and in the case
when the natural frequencies are the same for all the oscillators, we discuss
how the long-time transition to synchrony is governed by the dynamics of the
mean-field mode (zero Fourier mode) of the spatial distribution of the
oscillator phases.


  The focus of this work is to show how to combine Zech's logarithms and each
of the cycle joining and cross-join pairing methods to construct binary de
Bruijn sequences of any order. A basic implementation is supplied as a
proof-of-concept.
  The cycles, in the cycle joining method, are typically generated by a linear
feedback shift register. We prove a crucial characterization that determining
Zech's logarithms is equivalent to identifying conjugate pairs shared by any
two distinct cycles. This speeds up the task of building a connected adjacency
subgraph that contains all vertices of the complete adjacency graph. Distinct
spanning trees in either graph correspond to cyclically inequivalent de Bruijn
sequences. As the cycles are being joined, guided by the conjugate pairs, we
track the changes in the feedback function. Certificates of star or almost-star
spanning trees conveniently handle large order cases.
  The characterization of conjugate pairs via Zech's logarithms, as positional
markings, is then adapted to identify cross-join pairs. A modified $m$-sequence
is initially used, for ease of generation. The process can be repeated on each
of the resulting de Bruijn sequences. We show how to integrate an analytic
tool, attributed to Fryers, in the process.
  Most prior constructions in the literature measure the complexity of the
corresponding bit-by-bit algorithms. Our approach is different. We aim first to
build a connected adjacency subgraph that is certified to contain all of the
cycles as vertices. The ingredients are computed just once and concisely
stored. Simple strategies are offered to keep the complexities low as the order
grows.


  We analyze the Kim, Lee & Lee model of information erasure by black holes and
find contradictions with standard physical laws. We demonstrate that the
erasure model leads to arbitrarily fast information erasure; the proposed
physical interpretation of information freezing at the event horizon as
observed by an asymptotic observer is problematic; and information erasure,
whatever the process may be, near the black hole horizon leads to
contradictions with quantum mechanics if Landauer's principle is assumed. The
later part of the work demonstrates the significance of the "erasure entropy."
We show that the erasure entropy is the mutual information between two
subsystems.


  Quantum coherence is one of the primary non-classical features of quantum
systems. While protocols such as the Leggett-Garg inequality (LGI) and quantum
tomography can be used to test for the existence of quantum coherence and
dynamics in a given system, unambiguously detecting inherent "quantumness"
still faces serious obstacles in terms of experimental feasibility and
efficiency, particularly in complex systems. Here we introduce two "quantum
witnesses" to efficiently verify quantum coherence and dynamics in the time
domain, without the expense and burden of non-invasive measurements or full
tomographic processes. Using several physical examples, including quantum
transport in solid-state nanostructures and in biological organisms, we show
that these quantum witnesses are robust and have a much finer resolution in
their detection window than the LGI has. These robust quantum indicators may
assist in reducing the experimental overhead in unambiguously verifying quantum
coherence in complex systems.


  Virtual human techniques have been used a lot in industrial design in order
to consider human factors and ergonomics as early as possible. The physical
status (the physical capacity of virtual human) has been mostly treated as
invariable in the current available human simulation tools, while indeed the
physical capacity varies along time in an operation and the change of the
physical capacity depends on the history of the work as well. Virtual Human
Status is proposed in this paper in order to assess the difficulty of manual
handling operations, especially from the physical perspective. The decrease of
the physical capacity before and after an operation is used as an index to
indicate the work difficulty. The reduction of physical strength is simulated
in a theoretical approach on the basis of a fatigue model in which fatigue
resistances of different muscle groups were regressed from 24 existing maximum
endurance time (MET) models. A framework based on digital human modeling
technique is established to realize the comparison of physical status. An
assembly case in airplane assembly is simulated and analyzed under the
framework. The endurance time and the decrease of the joint moment strengths
are simulated. The experimental result in simulated operations under laboratory
conditions confirms the feasibility of the theoretical approach.


  We propose a group sparse optimization model for inpainting of a
square-integrable isotropic random field on the unit sphere, where the field is
represented by spherical harmonics with random complex coefficients. In the
proposed optimization model, the variable is an infinite-dimensional complex
vector and the objective function is a real-valued function defined by a hybrid
of the $\ell_2$ norm and non-Liptchitz $\ell_p (0<p<1)$ norm that preserves
rotational invariance property and group structure of the random complex
coefficients.
  We show that the infinite-dimensional optimization problem is equivalent to a
convexly-constrained finite-dimensional optimization problem. Moreover, we
propose a smoothing penalty algorithm to solve the finite-dimensional problem
via unconstrained optimization problems. We provide an approximation error
bound of the inpainted random field defined by a scaled KKT point of the
constrained optimization problem in the square-integrable space on the sphere
with probability measure. Finally, we conduct numerical experiments on
band-limited random fields on the sphere and images from Earth topography data
to show the promising performance of the smoothing penalty algorithm for
inpainting of random fields on the sphere.


  Understanding adaptive human driving behavior, in particular how drivers
manage uncertainty, is of key importance for developing simulated human driver
models that can be used in the evaluation and development of autonomous
vehicles. However, existing traffic psychology models of adaptive driving
behavior either lack computational rigor or only address specific scenarios
and/or behavioral phenomena. While models developed in the fields of machine
learning and robotics can effectively learn adaptive driving behavior from
data, due to their black box nature, they offer little or no explanation of the
mechanisms underlying the adaptive behavior. Thus, a generalizable,
interpretable, computational model of adaptive human driving behavior is still
lacking. This paper proposes such a model based on active inference, a
behavioral modeling framework originating in computational neuroscience. The
model offers a principled solution to how humans trade progress against caution
through policy selection based on the single mandate to minimize expected free
energy. This casts goal-seeking and information-seeking (uncertainty-resolving)
behavior under a single objective function, allowing the model to seamlessly
resolve uncertainty as a means to obtain its goals. We apply the model in two
apparently disparate driving scenarios that require managing uncertainty, (1)
driving past an occluding object and (2) visual time sharing between driving
and a secondary task, and show how human-like adaptive driving behavior emerges
from the single principle of expected free energy minimization.


  Atomic layer deposition (ALD) is a key technique for the continued scaling of
semiconductor devices, which increasingly relies on reproducible and scalable
processes for interface manipulation of 3D structured surfaces on the atomic
scale. While ALD allows the synthesis of conformal films at low temperature
with utmost control over the thickness, atomically-defined closed coatings and
surface modifications are still extremely difficult to achieve because of
three-dimensional growth during nucleation. Here, we present a route towards
sub-nanometer thin and continuous aluminum oxide (AlOx) coatings on silicon
(Si) substrates for the spatial control of the surface charge density and
interface energetics. We use trimethylaluminum (TMA) in combination with remote
hydrogen plasma instead of a gas-phase oxidant for the transformation of
silicon oxide into alumina (AlOx). During the initial ALD cycles, TMA reacts
with the surface oxide (SiO2) on silicon until there is a saturation of
bindings sites, after which the oxygen from the underlying surface oxide is
consumed, thereby transforming the silicon oxide into Si capped with AlOx.
Depending on the number of ALD cycles, the SiO2 can be partially or fully
transformed, which we exploit to create sub-nanometer thin and continuous AlOx
layers deposited in selected regions defined by lithographic patterning. The
resulting patterned surfaces are characterized by lateral AlOx/SiO2 interfaces
possessing step heights as small as 0.3 nm and surface potential steps in
excess of 0.4 V. In addition, the introduction of fixed negative charges of $9
\times 10^{12}$ cm$^{-2}$ enables modulation of the surface band bending, which
is relevant to the field-effect passivation of Si and low-impedance charge
transfer across contact interfaces.


  Extending the notion of bounded variation, a function $u \in L_c^1(\mathbb
R^n)$ is of bounded fractional variation with respect to some exponent $\alpha$
if there is a finite constant $C \geq 0$ such that the estimate \[ \biggl|\int
u(x) \det D(f,g_1,\dots,g_{n-1})_x \, dx\biggr| \leq
C\operatorname{Lip}^\alpha(f) \operatorname{Lip}(g_1) \cdots
\operatorname{Lip}(g_{n-1}) \] holds for all Lipschitz functions
$f,g_1,\dots,g_{n-1}$ on $\mathbb R^n$. Among such functions are characteristic
functions of domains with fractal boundaries and H\"older continuous functions.
We characterize functions of bounded fractional variation as a certain subspace
of Whitney's flat chains and as multilinear functionals in the setting of
Ambrosio-Kirchheim currents. Consequently we discuss extensions to H\"older
differential forms, higher integrability, an isoperimetric inequality, a Lusin
type property and change of variables. As an application we obtain sharp
integrability results for Brouwer degree functions with respect to H\"older
maps defined on domains with fractal boundaries.


  To date, the most widely-studied quantum anomalous Hall insulator (QAHI)
platform is achieved by dilute doping of magnetic ions into thin films of the
alloyed tetradymite topological insulator (TI) (Bi$_{1-x}$Sb$_x$)$_2$Te$_3$
(BST). In these films, long-range magnetic ordering of the transition metal
substituants opens an exchange gap $\Delta$ in the topological surface states,
stabilizing spin-polarized, dissipationless edge channels with a nonzero Chern
number $\mathcal{C}$. The long-range ordering of the spatially separated
magnetic ions is itself mediated by electronic states in the host TI, leading
to a sophisticated feedback between magnetic and electronic properties. Here we
present a study of the electronic and magnetic response of a BST-based QAHI
system to structural tuning via hydrostatic pressure. We identify a systematic
closure of the topological gap under compressive strain accompanied by a
simultaneous enhancement in the magnetic ordering strength. Combining these
experimental results with first-principle calculations we identify structural
deformation as a strong tuning parameter to traverse a rich topological phase
space and modify magnetism in the magnetically doped BST system.


  We calculate the annihilation decay widths of spin-singlet heavy quarkonia
$h_c, h_b$ and $\eta_b$} into light hadrons with both QCD and relativistic
corrections at order $O(\alpha_{s}v^{2})$ in nonrelativistic QCD. With
appropriate estimates for the long-distance matrix elements by using the
potential model and operator evolution method, we find that our predictions of
these decay widths are consistent with recent experimental measurements. We
also find that the $O(\alpha_{s}v^{2})$ corrections are small for $b\bar{b}$
states but substantial for $c\bar{c}$ states. In particular, the negative
contribution of $O(\alpha_{s}v^{2})$ correction to the $h_{c}$ decay can lower
the decay width, as compared with previous predictions without the
$O(\alpha_{s}v^{2})$ correction, and thus result in a good agreement with the
recent BESIII measurement.


  We study a two-orbital $t$-$J_1$-$J_2$ model, originally developed to
describe iron-based superconductors at low energies, in the presence of bond
disorder (via next-nearest-neighbor $J_2$-bond dilution). By using the
Bogoliubov--de Gennes approach, we self-consistently calculate the local
pairing amplitudes and the corresponding density of states, which demonstrate a
change of dominant pairing symmetry from $s_\pm$ wave to $d$ wave when
increasing disorder strength as long as $J_1\lesssim J_2$. Moreover, the
combined pairing interaction and strong bond disorder lead to the formation of
$s_\pm$ wave "islands" with length scale of the superconducting coherence
length embedded in a $d$ wave "sea." This picture is further complemented by
the disorder-averaged pair-pair correlation functions, distinct from the case
with potential disorder, where the "sea" is insulating. Due to this inevitable
formation of spatial inhomogeneity, the superconducting $T_c$ determined by the
superfluid density $\rho_s(T)$ obviously deviates from the value predicted by
the conventional Abrikosov-Gorkov theory, where the pairing amplitudes are
viewed as uniformly suppressed as the disorder increases.


  We propose a model that accounts for the budding transition of asymmetric
two-component lipid domains, where the two monolayers (leaflets) have different
average compositions controlled by independent chemical potentials. Assuming a
coupling between the local curvature and local lipid composition in each of the
leaflets, we discuss the morphology and thermodynamic behavior of asymmetric
lipid domains. The membrane free-energy contains three contributions: the
bending energy, the line tension, and a Landau free-energy for a lateral phase
separation. Within a mean-field treatment, we obtain various phase diagrams
containing fully budded, dimpled, and flat states as a function of the two
leaflet compositions. The global phase behavior is analyzed, and depending on
system parameters, the phase diagrams include one-phase, two-phase and
three-phase regions. In particular, we predict various phase coexistence
regions between different morphologies of domains, which may be observed in
multi-component membranes or vesicles.