  We consider a two-dimensional rigid rotator system coupled to a
two-dimensional heat bath. The Caldeira-Leggett (Brownian) model for the
rotator and the spin-Boson model have been used to describe such systems, but
they do not possess rotational symmetry, they cannot describe the discretized
rotational bands in absorption and emission spectra that have been found
experimentally. Here, to address this problem, we introduce a rotationally
invariant system-bath (RISB) model that is described by two sets of
harmonic-oscillator baths independently coupled to the rigid rotator as sine
and cosine functions of the rotator angle. Due to a difference in the energy
discretization of the total Hamiltonian, the dynamics described by the RISB
model differ significantly from those described by the rotational
Caldeira-Legget (RCL) model, while both models reduce to the Langevin equation
for a rotator in the classical limit. To demonstrate this point, we compute the
rotational absorption spectrum defined by the linear response function of a
rotator dipole. For this purpose, we derive a quantum master equation for the
RISB model in the high-temperature Markovian case. We find that the spectral
profiles of the calculated signals exhibit a transition from quantized
rotational bands to a single peak after spectrum collapse. This is a
significant finding, because previous approaches cannot describe such phenomena
in a unified manner.


  We describe methods designed to determine the astrophysical parameters of
quasars based on spectra coming from the red and blue spectrophotometers of the
Gaia satellite. These methods principally rely on two already published
algorithms that are the weighted principal component analysis and the weighted
phase correlation. The presented approach benefits from a fast implementation;
an intuitive interpretation as well as strong diagnostic tools on the potential
errors that may arise during predictions. The production of a semi-empirical
library of spectra as they will be observed by Gaia is also covered and
subsequently used for validation purpose. We detail the pre-processing that is
necessary in order for these spectra to be fully exploitable by our algorithms
along with the procedures that are used in order to predict the redshifts of
the quasars; their continuum slopes; the total equivalent width of their
emission lines and whether these are broad absorption line (BAL) quasars or
not. Performances of these procedures were assessed in comparison with the
Extremely Randomized Trees learning method and were proven to provide better
results on the redshift predictions and on the ratio of correctly classified
observations though the probability of detection of BAL quasars remains
restricted by the low resolution of these spectra as well as by their limited
signal-to-noise ratio. Finally, the triggering of some warning flags allows us
to obtain an extremely pure subset of redshift predictions where approximately
99% of the observations come along with absolute errors that are below 0.1.


  We study the twisted index of 4d $\mathcal{N}$ = 2 class S theories on a
closed hyperbolic 3-manifold $M_3$. Via 6d picture, the index can be written in
terms of topological invariants called analytic torsions twisted by irreducible
flat connections on the 3-manifold. Using the topological expression, we
determine the full perturbative 1/N expansion of the twisted index. The leading
part nicely matches the Bekestein-Hawking entropy of a magnetically charged
black hole in the holographic dual $AdS_5$ with $AdS_2\times M_3$ near-horizon.


  For every prime p we give infinitely many examples of torsors under abelian
varieties over Q that are locally trivial but not divisible by p in the
Weil-Ch\^atelet group. We also give an example of a locally trivial torsor
under an elliptic curve over Q which is not divisible by 4 in the
Weil-Ch\^atelet group. This gives a negative answer to a question of Cassels.


  In recent years, more research has been devoted to studying the subtask of
the complete shallow discourse parsing, such as indentifying discourse
connective and arguments of connective. There is a need to design a full
discourse parser to pull these subtasks together. So we develop a discourse
parser turning the free text into discourse relations. The parser includes
connective identifier, arguments identifier, sense classifier and non-explicit
identifier, which connects with each other in pipeline. Each component applies
the maximum entropy model with abundant lexical and syntax features extracted
from the Penn Discourse Tree-bank. The head-based representation of the PDTB is
adopted in the arguments identifier, which turns the problem of indentifying
the arguments of discourse connective into finding the head and end of the
arguments. In the non-explicit identifier, the contextual type features like
words which have high frequency and can reflect the discourse relation are
introduced to improve the performance of non-explicit identifier. Compared with
other methods, experimental results achieve the considerable performance.


  Recent advances in deep learning have led to significant improvements in
single image super-resolution (SR) research. However, due to the amplification
of noise during the upsampling steps, state-of-the-art methods often fail at
reconstructing high-resolution images from noisy versions of their
low-resolution counterparts. However, this is especially important for images
from unknown cameras with unseen types of image degradation. In this work, we
propose to jointly perform denoising and super-resolution. To this end, we
investigate two architectural designs: "in-network" combines both tasks at
feature level, while "pre-network" first performs denoising and then
super-resolution. Our experiments show that both variants have specific
advantages: The in-network design obtains the strongest results when the type
of image corruption is aligned in the training and testing dataset, for any
choice of denoiser. The pre-network design exhibits superior performance on
unseen types of image corruption, which is a pathological failure case of
existing super-resolution models. We hope that these findings help to enable
super-resolution also in less constrained scenarios where source camera or
imaging conditions are not well controlled. Source code and pretrained models
are available at https://github.com/
angelvillar96/super-resolution-noisy-images.


  We study the effects of surface tension between normal and superfluid regions
of a trapped Fermi gas at unitarity. We find that surface tension causes
notable distortions in the shape of large aspect ratio clouds. Including these
distortions in our theories resolves many of the apparent discrepancies among
different experiments and between theory and experiments.


  We consider a rough differential equation with a non-linear damping drift
term: \begin{align*} dY(t) = - |Y|^{m-1} Y(t) dt + \sigma(Y(t)) dX(t),
\end{align*} where $X$ is a branched rough path of arbitrary regularity $\alpha
>0$, $m>1$ and where $\sigma$ is smooth and satisfies an $m$ and
$\alpha$-dependent growth property. We show a strong a priori bound for $Y$,
which includes the "coming down from infinity" property, i.e. the bound on
$Y(t)$ for a fixed $t>0$ holds uniformly over all choices of initial datum
$Y(0)$. The method of proof builds on recent work by Chandra, Moinat and Weber
on a priori bounds for the $\phi^4$ SPDE in arbitrary subcritical dimension. A
key new ingredient is an extension of the algebraic framework which permits to
derive an estimate on higher order conditions of a coherent controlled rough
path in terms of the regularity condition at lowest level.


  An absorption spectrum of H$_2$$^{16}$O at 1950 K is recorded in a premixed
methane/air flat flame using a cavity-enhanced optical frequency comb-based
Fourier transform spectrometer. 2417 absorption lines are identified in the
6250 -- 6670 cm region with an accuracy of about 0.01 cm.
  Absolute line intensities are retrieved using temperature and concentration
values obtained by tunable diode laser absorption spectroscopy. Line
assignments are made using a combination of empirically known energy levels and
predictions from the new POKAZATEL variational line list. 2030 of the observed
lines are assigned to 2937 transitions, once blends are taken into account. 126
new energy levels of H$_2$$^{16}$O are identified. The assigned transitions
belong to 136 bands and span rotational states up to $J=27$.


  Emergent color centers with accessible spins hosted by van der Waals
materials have attracted substantial interest in recent years due to their
significant potential for implementing transformative quantum sensing
technologies. Hexagonal boron nitride (hBN) is naturally relevant in this
context due to its remarkable ease of integration into devices consisting of
low-dimensional materials. Taking advantage of boron vacancy spin defects in
hBN, we report nanoscale quantum imaging of low-dimensional ferromagnetism
sustained in Fe3GeTe2/hBN van der Waals heterostructures. Exploiting spin
relaxometry methods, we have further observed spatially varying magnetic
fluctuations in the exfoliated Fe3GeTe2 flake, whose magnitude reaches a peak
value around the Curie temperature. Our results demonstrate the capability of
spin defects in hBN of investigating local magnetic properties of layered
materials in an accessible and precise way, which can be extended readily to a
broad range of miniaturized van der Waals heterostructure systems.


  We construct a rank-3 finite temperature logarithmic conformal field theory
(LCFT) starting from a higher-derivative scalar field model in the BTZ black
hole background. Its zero temperature limit reduces to a rank-3 LCFT in the
AdS$_3$ background. For a tricritical generalized massive gravity, we read off
the log-square quasinormal frequencies of graviton from the poles of the
retarded Green's function in the momentum space. After using the truncation
process, we find quasinormal frequencies from a unitary conformal field theory.
Finally, employing the retarded Green's functions on the boundary, we compute
the absorption cross sections of BTZ black hole which show feature of
higher-order differential equations for scalars.


  The post-Newtonian dynamics of black hole binaries in
Einstein-scalar-Gauss-Bonnet theories of gravity depends on the so-called
"sensitivities", quantities which characterize a black hole's adiabatic
response to the time-dependent scalar field environment sourced by its
companion. In this work, we calculate numerically the sensitivities of
nonrotating black holes, including spontaneously scalarized ones, in three
classes of Einstein-scalar-Gauss-Bonnet gravity: the shift-symmetric, dilatonic
and Gaussian theories. When possible, we compare our results against
perturbative analytical results, finding excellent agreement. Unlike their
general relativistic counterparts, black holes in Einstein-scalar-Gauss-Bonnet
gravity only exist in a restricted parameter space controlled by the theory's
coupling constant. A preliminary study of the role played by the sensitivities
in black hole binaries suggests that, in principle, black holes can be driven
outside of their domain of existence during the inspiral, for binary parameters
which we determine.


  Millisecond pulsars (MSPs) are a growing class of gamma-ray emitters. Pulsed
gamma-ray signals have been detected from more than 40 MSPs with the Fermi
Large Area Telescope (LAT). The wider radio beams and more compact
magnetospheres of MSPs enable studies of emission geometries over a broader
range of phase space than non-recycled radio-loud gamma-ray pulsars. We have
modeled the gamma-ray light curves of 40 LAT-detected MSPs using geometric
emission models assuming a vacuum retarded-dipole magnetic field. We modeled
the radio profiles using a single-altitude hollow-cone beam, with a core
component when indicated by polarimetry; however, for MSPs with gamma-ray and
radio light curve peaks occurring at nearly the same rotational phase we assume
that the radio emission is co-located with the gamma rays and caustic in
nature. The best-fit parameters and confidence intervals are determined using a
maximum likelihood technique. We divide the light curves into three model
classes, with gamma-ray peaks trailing (Class I), aligned (Class II) or leading
(Class III) the radio peaks. Outer gap and slot gap (two-pole caustic) models
best fit roughly equal numbers of Class I and II, while Class III are
exclusively fit with pair-starved polar cap models. Distinguishing between the
model classes based on typical derived parameters is difficult. We explore the
evolution of magnetic inclination angle with period and spin-down power,
finding possible correlations. While the presence of significant off-peak
emission can often be used as a discriminator between outer gap and slot gap
models, a hybrid model may be needed.


  In this paper we introduce operator s-convex func- tions and establish some
Hermite-Hadamard type inequalities in which some operator s-convex functions of
positive operators in Hilbert spaces are involved.


  We study the renormalization of the quasiparticle properties in weak
ferromagnetic metals, due to spin fluctuations, away from the quantum critical
point for small magnetic moment. We explain the origin of the s-wave
superconducting instability in the ferromagnetic phase and find that the vertex
corrections are small and Migdal's theorem is satisfied away from the quantum
critical point.


  We test whether halo age and galaxy age are correlated at fixed halo and
galaxy mass. The formation histories, and thus ages, of dark matter halos
correlate with their large-scale density $\rho$, an effect known as assembly
bias. We test whether this correlation extends to galaxies by measuring the
dependence of galaxy stellar age on $\rho$. To clarify the comparison between
theory and observation, and to remove the strong environmental effects on
satellites, we use galaxy group catalogs to identify central galaxies and
measure their quenched fraction, $f_Q$, as a function of large-scale
environment. Models that match halo age to central galaxy age predict a strong
positive correlation between $f_Q$ and $\rho$. However, we show that the
amplitude of this effect depends on the definition of halo age: assembly bias
is significantly reduced when removing the effects of splashback halos---those
halos that are central but have passed through a larger halo or experienced
strong tidal encounters. Defining age using halo mass at its peak value rather
than current mass removes these effects. In SDSS data, at M$_{\rm gal}\gtrsim
10^{10.0}$ M_sol/h$^2$, there is a $\sim 5\%$ increase in $f_Q$ from low to
high densities, which is in agreement with predictions of dark matter halos
using peak halo mass. At lower stellar mass there is little to no correlation
of $f_Q$ with $\rho$. For these galaxies, age-matching is inconsistent with the
data across the wide range the halo formation metrics that we tested. This
implies that halo formation history has a small but statistically significant
impact on quenching of star formation at high masses, while the quenching
process in low-mass central galaxies is uncorrelated with halo formation
history.


  We describe a method of analysis which allows for reconstructing the
nonlinear disturbance of a high Q harmonic oscillator. When the oscillator is
driven with two or more frequencies, the nonlinearity causes intermodulation of
the drives, resulting in a complicated spectral response. Analysis of this
spectrum allows one to approximate the nonlinearity. The method, which is
generally applicable to measurements based on resonant detection, increases the
information content of the measurement without requiring large detection
bandwidth, and optimally uses the enhanced sensitivity near resonance to
extract information and minimize error due to detector noise.


  We study the time evolution of a complex scalar field in the symmetry broken
phase in the presence of oscillating spacetime metric background. In our
(2+1)-dimensional simulations, we show that the spacetime oscillations can
excite an initial field configuration, which ultimately leads to the formation
of topological vortices in the system. At late times, field configuration
achieves a disordered state. A detailed study of the momentum and frequency
modes of the field reveals that these field excitations are driven by the
phenomenon of parametric resonance. In extremely high frequency regime where
frequency of spacetime oscillations is much larger than the field-mass, the
formed vortices are not topological in nature. Interestingly in this regime,
for a suitable choice of parameters of the simulation, we observe a persistent
lattice structure of vortex-antivortex pairs. We discuss applications of our
study to the dynamics of interior superfluidity of neutron stars during binary
neutron star mergers, in generation of excitation in ultralight axion-like
field near a strong gravitational wave source, etc.


  We study the partial Brauer monoid and its planar submonoid, the Motzkin
monoid. We conduct a thorough investigation of the structure of both monoids,
providing information on normal forms, Green's relations, regularity, ideals,
idempotent generation, minimal (idempotent) generating sets, and so on. We
obtain necessary and sufficient conditions under which the ideals of these
monoids are idempotent-generated. We find formulae for the rank (smallest size
of a generating set) of each ideal, and for the idempotent rank (smallest size
of an idempotent generating set) of the idempotent-generated subsemigroup of
each ideal; in particular, when an ideal is idempotent-generated, the rank and
idempotent rank are equal. Along the way, we obtain a number of results of
independent interest, and we demonstrate the utility of the semigroup theoretic
approach by applying our results to obtain new proofs of important
representation theoretic results concerning the corresponding diagram algebras,
the partial (or rook) Brauer algebra and Motzkin algebra.


  We study Liouville type of theorems for the Navier-Stokes and the Euler
equations on $\Bbb R^N$, $N\geq 2$. Specifically, we prove that if a weak
solution $(v,p)$ satisfies $|v|^2 +|p| \in L^1 (0,T; L^1(\Bbb R^N, w_1(x)dx))$
and $\int_{\Bbb R^N} p(x,t)w_2 (x)dx \geq0$ for some weight functions $w_1(x)$
and $w_2 (x)$, then the solution is trivial, namely $v=0$ almost everywhere on
$\Bbb R^N \times (0, T)$. Similar results hold for the MHD Equations on $\Bbb
R^N$, $N\geq3$.


  We extend the usual gravitational action principle by promoting the bare
cosmological constant (CC) from a parameter to a field which can take many
possible values. Variation leads to a new integral constraint equation which
determines the classical value of the effective CC that dominates the wave
function of the universe. In a realistic cosmological model, the expected value
of the effective CC, is calculated from measurable quantities to be O(t_U), as
observed, where t_U is the present age of the universe in Planck units,. Any
application of our model produces a falsifiable prediction for $\Lambda $ in
terms of other measurable quantities. This leads to a specific falsifiable
prediction for the observed spatial curvature parameter of Omega_k0=-0.0055.
Our testable proposal requires no fine tunings or extra dark-energy fields but
does suggest a new view of time and cosmological evolution.


  In 1992 Wang & Larsen extended the may- and must preorders of De Nicola and
Hennessy to processes featuring probabilistic as well as nondeterministic
choice. They concluded with two problems that have remained open throughout the
years, namely to find complete axiomatisations and alternative
characterisations for these preorders. This paper solves both problems for
finite processes with silent moves. It characterises the may preorder in terms
of simulation, and the must preorder in terms of failure simulation. It also
gives a characterisation of both preorders using a modal logic. Finally it
axiomatises both preorders over a probabilistic version of CSP.


  At the center of the ZEUS detector situated on the collider HERA at DESY in
Hamburg, a Micro Vertex Detector has been installed in 2000/01. Situated close
to the beam line, this subdetector is designed to measure precisely the tracks
near the interaction point (the vertex). A package called KFFIT is designated
to perform the track fit of the Micro Vertex Detector hits using a Kalman
Filter. This paper is a report of all improvements done in this package. After
a brief description of the algorithm, the improvements of KFFIT will be
presented comparing the last version (v10 released in December 2006) to the
initial one (v1 released in December 2005 (=v2005a.1)).


  We introduce slant Riemannian submersions from Sasakian manifolds onto
Riemannian manifolds. We survey main results of slant Riemannian submersions
defined on Sasakian manifolds. We also give an example of such slant
submersions.


  Within commercial wind energy generation, the monitoring and predictive
maintenance of wind turbine blades in-situ is a crucial task, for which remote
monitoring via aerial survey from an Unmanned Aerial Vehicle (UAV) is
commonplace. Turbine blades are susceptible to both operational and
weather-based damage over time, reducing the energy efficiency output of
turbines. In this study, we address automating the otherwise time-consuming
task of both blade detection and extraction, together with fault detection
within UAV-captured turbine blade inspection imagery. We propose BladeNet, an
application-based, robust dual architecture to perform both unsupervised
turbine blade detection and extraction, followed by super-pixel generation
using the Simple Linear Iterative Clustering (SLIC) method to produce regional
clusters. These clusters are then processed by a suite of semi-supervised
detection methods. Our dual architecture detects surface faults of glass fibre
composite material blades with high aptitude while requiring minimal prior
manual image annotation. BladeNet produces an Average Precision (AP) of 0.995
across our {\O}rsted blade inspection dataset for offshore wind turbines and
0.223 across the Danish Technical University (DTU) NordTank turbine blade
inspection dataset. BladeNet also obtains an AUC of 0.639 for surface anomaly
detection across the {\O}rsted blade inspection dataset.


  Dark energy and dark matter constitute 95% of the observable Universe. Yet
the physical nature of these two phenomena remains a mystery. Einstein
suggested a long-forgotten solution: gravitationally repulsive negative masses,
which drive cosmic expansion and cannot coalesce into light-emitting
structures. However, contemporary cosmological results are derived upon the
reasonable assumption that the Universe only contains positive masses. By
reconsidering this assumption, I have constructed a toy model which suggests
that both dark phenomena can be unified into a single negative mass fluid. The
model is a modified $\Lambda$CDM cosmology, and indicates that
continuously-created negative masses can resemble the cosmological constant and
can flatten the rotation curves of galaxies. The model leads to a cyclic
universe with a time-variable Hubble parameter, potentially providing
compatibility with the current tension that is emerging in cosmological
measurements. In the first three-dimensional N-body simulations of negative
mass matter in the scientific literature, this exotic material naturally forms
haloes around galaxies that extend to several galactic radii. These haloes are
not cuspy. The proposed cosmological model is therefore able to predict the
observed distribution of dark matter in galaxies from first principles. The
model makes several testable predictions and seems to have the potential to be
consistent with observational evidence from distant supernovae, the cosmic
microwave background, and galaxy clusters. These findings may imply that
negative masses are a real and physical aspect of our Universe, or
alternatively may imply the existence of a superseding theory that in some
limit can be modelled by effective negative masses. Both cases lead to the
surprising conclusion that the compelling puzzle of the dark Universe may have
been due to a simple sign error.


  We describe realizations of the color analogue of the Heisenberg Lie algebra
by power series in non-commuting indeterminates satisfying Heisenberg's
canonical commutation relations of quantum mechanics. The obtained formulas are
used to construct new operator representations of the color analogue of the
Heisenberg Lie algebra. These representations are shown to be closely connected
with some combinatorial identities and functional difference-differential
interpolation formulae involving Euler, Bernoulli and Stirling numbers.


  We reconsider the supersymmetric Wess-Zumino-Witten (SWZW) term in four
dimensions. It has been known that the manifestly supersymmetric form of the
SWZW term includes derivative terms on auxiliary fields, the highest components
of chiral superfields, and then we cannot eliminate them by their equations of
motion. We discuss a possibility for the elimination of such derivative terms
by adding total derivative terms. Although the most of derivative terms can be
eliminated as in this way, we find that all the derivative terms can be
canceled, if and only if an anomalous term in SWZW term vanishes. As a
byproduct, we find the first example of a higher derivative term free from such
a problem.


  We review the derivation of the pulsations equations for spherically
symmetric boson stars and then make a thorough study of the radial oscillation
frequencies for the fundamental and first excited modes. We do this for
self-interacting boson stars and consider a range of values for the
self-coupling constant. We also numerically evolve boson stars and Fourier
transform the dynamic solutions. The Fourier transform gives an independent
computation of the radial oscillation frequencies and allows us to verify our
results obtained from the pulsation equations. We find excellent agreement
between the two methods.


  We tackle the quantification of synchrony in globally coupled populations.
Furthermore, we treat the problem of incomplete observations when the
population mean field is unavailable, but only a small subset of units is
observed. We introduce a new order parameter and demonstrate its efficiency for
quantifying synchrony via monitoring general observables, regardless of whether
the oscillations can be characterized in terms of the phases. Under condition
of a significant irregularity in the dynamics of the coupled units, this order
parameter provides a unified description of synchrony in populations of units
of various complexity. The main examples include noise-induced oscillations,
coupled strongly chaotic systems, and noisy periodic oscillations. Furthermore,
we explore how this parameter works for the standard Kuramoto model of coupled
regular phase oscillators. The most significant advantage of our approach is
its ability to infer and quantify synchrony from the observation of a small
percentage of the units and even from a single unit, provided the observations
are sufficiently long.


  The recently discovered electrical-induced switching of antiferromagnetic
(AF) materials that have spatial inversion asymmetry has enriched the field of
spintronics immensely and opened the door for the concept of antiferromagnetic
MRAM. CuMnAs is one promising AF material that exhibits such electrical
switching ability, and has been studied to switch using electrical pulses of
length millisecond down to picosecond, but with little focus on nanosecond
regime. We demonstrate here switching of CuMnAs/GaP using nanosecond pulses.
Our results showed that in the nanosecond regime low-energy switching, high
readout signal with highly reproducible behaviour down to a single pulse can be
achieved. Moreover, a comparison of the two switching methods of orthogonal
switching and polarity switching was done on same device showing two different
behaviours that can be exploited selectively for different future
memory/processing applications.


  Measurements of dijet azimuthal decorrelations in pp collisions at sqrt(s) =
7 TeV using the CMS detector at the CERN LHC are presented. The analysis is
based on an inclusive dijet event sample corresponding to an integrated
luminosity of 2.9 inverse picobarns. The results are compared to predictions
from perturbative QCD calculations and various Monte Carlo event generators.
The dijet azimuthal distributions are found to be sensitive to initial-state
gluon radiation.


  Learning rate schedule has a major impact on the performance of deep learning
models. Still, the choice of a schedule is often heuristical. We aim to develop
a precise understanding of the effects of different learning rate schedules and
the appropriate way to select them. To this end, we isolate two distinct phases
of training, the first, which we refer to as the "large-step" regime, exhibits
a rather poor performance from an optimization point of view but is the primary
contributor to model generalization; the latter, "small-step" regime exhibits
much more "convex-like" optimization behavior but used in isolation produces
models that generalize poorly. We find that by treating these regimes
separately-and em specializing our training algorithm to each one of them, we
can significantly simplify learning rate schedules.


  Two of the most important features of the solar atmosphere are its hot,
smooth coronal loops and the concentrations of magnetic shear, known as
filament channels, that reside above photospheric polarity inversion lines
(PILs). The shear observed in filament channels represents magnetic helicity,
while the smoothness of the coronal loops indicates an apparent lack of
magnetic helicity in the rest of the corona. At the same time, models that
attempt to explain the high temperatures observed in these coronal loops
require magnetic energy, in the form of twist, to be injected at the
photosphere. In addition to magnetic energy, this twist also represents
magnetic helicity. Unlike magnetic energy, magnetic helicity is conserved under
reconnection, and is consequently expected to accumulate and be observed in the
corona. However, filament channels, rather than the coronal loops, are the
locations in the corona where magnetic helicity is observed, and it manifests
itself in the form of shear, rather than twist. This naturally raises the
question: if magnetic helicity needs to be injected to heat coronal loops, why
is it only observed in filament channels, while coronal loops are observed to
be laminar and smooth? This thesis addresses this question using a series of
numerical simulations that demonstrate that magnetic helicity is transported
throughout the solar corona by magnetic reconnection in such a way that it
accumulates above PILs, forming filament channels, and leaving the rest of the
corona generally smooth. In the process, it converts magnetic energy into heat,
accounting for the large observed temperatures. This thesis presents a model
for the formation of filament channels in the solar corona and the presence of
smooth, hot coronal loops, and shows how the transport of magnetic helicity
throughout the solar corona by magnetic reconnection is responsible for both of
these phenomena.


  Reactions $n_{\gamma }\gamma +$ $d+$ $_{z_{2}}^{A_{2}}X\rightarrow \left(
n_{\gamma }\pm 1\right) \gamma +$ $p+$ $_{z_{2}}^{A_{2}+1}X$ and especially the
reaction $d+$ $_{z_{2}}^{A_{2}}X\rightarrow \gamma +$ $p+$ $%
_{z_{2}}^{A_{2}+1}X$, called photo-induced nuclear cooperation and cooperative
spontaneous $\gamma $ emission with neutron exchange, respectively, are
investigated theoretically. In the case of photo-induced nuclear cooperation it
is supposed that the energy of $\gamma $ photons of the beam is less than the
binding energy of the deuteron. The cross section and the transition
probability per unit time, respectively, are determined with the aid of
standard second order perturbation calculation of quantum mechanics. The
calculations are extended to photo-induced nuclear cooperation and cooperative
spontaneous $\gamma $ emission with proton exchange as well. With the aid of
the results obtained, recent observations of nuclear activity of samples of
large deuteron content after irradiation by photon-flux of photon energy
smaller than the deuteron binding energy are discussed.


  A statistical manifold $\left(M,D,g\right)$ is a manifold $M$ endowed with a
torsion-free connection $D$ and a Riemannian metric $g$ such that the tensor $D
g$ is totally symmetric. If $D$ is flat then $\left(M,g,D\right)$ is a Hessian
manifold. A locally conformally Hessian (l.c.H) manifold is a quotient of a
Hessian manifold $(C,\nabla,g)$ such that the monodromy group acts on $C$ by
Hessian homotheties, i.e. this action preserves $\nabla$ and multiplies $g$ by
a group character. The l.c.H. rank is the rank of the image of this character
considered as a function from the monodromy group to real numbers. A l.c.H.
manifold is called radiant if the Lee vector field $\xi$ is Killing and
satisfies $\nabla \xi =\lambda \Id$. We prove that the set of radiant l.c.H.
metrics of l.c.H. rank 1 is dense in the set of all radiant l.c.H. metrics. We
prove a structure theorem for compact radiant l.c.H. manifold of l.c.H. rank 1.
Every such manifold $C$ is fibered over a circle, the fibers are statistical
manifolds of constant curvature, the fibration is locally trivial, and $C$ is
reconstructed from the statistical structure on the fibers and the monodromy
automorphism induced by this fibration.


  Datasets extracted from social networks and online forums are often prone to
the pitfalls of natural language, namely the presence of unstructured and noisy
data. In this work, we seek to enable the collection of high-quality
question-answer datasets from social media by proposing a novel task for
automated quality analysis and data cleaning: question-answer (QA)
plausibility. Given a machine or user-generated question and a crowd-sourced
response from a social media user, we determine if the question and response
are valid; if so, we identify the answer within the free-form response. We
design BERT-based models to perform the QA plausibility task, and we evaluate
the ability of our models to generate a clean, usable question-answer dataset.
Our highest-performing approach consists of a single-task model which
determines the plausibility of the question, followed by a multi-task model
which evaluates the plausibility of the response as well as extracts answers
(Question Plausibility AUROC=0.75, Response Plausibility AUROC=0.78, Answer
Extraction F1=0.665).


  We use Lightcone Conformal Truncation (LCT) -- a version of Hamiltonian
truncation -- to study the nonperturbative, real-time dynamics of
$\phi^4$-theory in 2+1 dimensions. This theory has UV divergences that need to
be regulated. We review how, in a Hamiltonian framework with a total energy
cutoff, renormalization is necessarily \emph{state-dependent}, and UV
sensitivity cannot be canceled with standard local operator counterterms. To
overcome this problem, we present a prescription for constructing the
appropriate state-dependent counterterms for (2+1)d $\phi^4$-theory in
lightcone quantization. We then use LCT with this counterterm prescription to
study $\phi^4$-theory, focusing on the $\mathbb{Z}_2$ symmetry-preserving
phase. Specifically, we compute the spectrum as a function of the coupling and
demonstrate the closing of the mass gap at a (scheme-dependent) critical
coupling. We also compute Lorentz-invariant two-point functions, both at
generic strong coupling and near the critical point, where we demonstrate IR
universality and the vanishing of the trace of the stress tensor.


  Most stars are formed in a cluster or association, where the number density
of stars can be high. This means that a large fraction of initially-single
stars will undergo close encounters with other stars and/or exchange into
binaries. We describe how such close encounters and exchange encounters can
affect the properties of a planetary system around a single star. We define a
singleton as a single star which has never suffered close encounters with other
stars or spent time within a binary system. It may be that planetary systems
similar to our own solar system can only survive around singletons. Close
encounters or the presence of a stellar companion will perturb the planetary
system, often leaving planets on tighter and more eccentric orbits. Thus
planetary systems which initially resembled our own solar system may later more
closely resemble some of the observed exoplanet systems.


  The duality of content and style is inherent to the nature of art. For
humans, these two elements are clearly different: content refers to the objects
and concepts in the piece of art, and style to the way it is expressed. This
duality poses an important challenge for computer vision. The visual appearance
of objects and concepts is modulated by the style that may reflect the author's
emotions, social trends, artistic movement, etc., and their deep comprehension
undoubtfully requires to handle both. A promising step towards a general
paradigm for art analysis is to disentangle content and style, whereas relying
on human annotations to cull a single aspect of artworks has limitations in
learning semantic concepts and the visual appearance of paintings. We thus
present GOYA, a method that distills the artistic knowledge captured in a
recent generative model to disentangle content and style. Experiments show that
synthetically generated images sufficiently serve as a proxy of the real
distribution of artworks, allowing GOYA to separately represent the two
elements of art while keeping more information than existing methods.


  In this paper we discuss abundance ratios and their relation to stellar
nucleosynthesis and other parameters of chemical evolution models, reviewing
and clarifying the correct use of the observed abundance ratios in several
astrophysical contests. In particular, we start from the well known fact that
abundance ratios depend on stellar yields, initial mass function and stellar
lifetimes and we show, by means of specific examples, that in some cases it is
not correct to infer constraints on the contributions from different SN types
(Ia, II), and particularly on different sets of yields, in the absence of a
complete chemical evolution model taking into account stellar lifetimes. In
spite of the fact that some of these results should be well known, we believe
that it is useful to discuss the meaning of abundance ratios in the light of
severel recent claims based upon an incorrect interpretation of observed
abundance ratios. In particular, the procedure, often used in the recent
literature, of deriving directly conclusions about stellar nucleosynthesis,
just by relating abundance ratios to yield ratios, implicitly assumes the
instantaneous recycling approximation (I.R.A.). This approximation is clearly
not correct when one analyzes the contributions of SNIa relative to SNII as
functions of cosmic time. In this paper we show that the uncertainty which
arises from adopting this oversimplified procedure in a variety of
astrophysical objects, such as elliptical galaxies, the intracluster medium and
high redshift objects, does not allow us to draw any firm conclusion, and that
the differences between abundance ratios predicted by models with I.R.A. and
models with detailed stellar lifetimes is of the same order as the differences
between different sets of yields. (Abridged)


  With the constraint that $T_c = 39$ K, as observed for MgB$_2$, we use the
Eliashberg equations to compute possible allowed values of the isotope
coefficient, $\beta$. We find that while the observed value $\beta= 0.32$ can
be obtained in principle, it is difficult to reconcile a recently calculated
spectral function with such a low observed value.


  In this paper, we are concerned with the local-in-time well-posedness of a
fluid-kinetic model in which the BGK model with density dependent collision
frequency is coupled with the inhomogeneous Navier-Stokes equation through drag
forces. To the best knowledge of authors, this is the first result on the
existence of local-in-time smooth solution for particle-fluid model with
nonlinear inter-particle operator for which the existence of time can be
prolonged as the size of initial data gets smaller.


  We apply the Tannaka-Krein duality theory for quantum homogeneous spaces,
developed in the first part of this series of papers, to the case of the
quantum SU(2) groups. We obtain a classification of their quantum homogeneous
spaces in terms of weighted oriented graphs. The equivariant maps between these
quantum homogeneous spaces can be characterized by certain quadratic equations
associated with the braiding on the representations of SUq(2). We show that,
for |q| close to 1, all quantum homogeneous spaces are realized by coideals.


  Despite the wealth of research into provably efficient reinforcement learning
algorithms, most works focus on tabular representation and thus struggle to
handle exponentially or infinitely large state-action spaces. In this paper, we
consider episodic reinforcement learning with a continuous state-action space
which is assumed to be equipped with a natural metric that characterizes the
proximity between different states and actions. We propose ZoomRL, an online
algorithm that leverages ideas from continuous bandits to learn an adaptive
discretization of the joint space by zooming in more promising and frequently
visited regions while carefully balancing the exploitation-exploration
trade-off. We show that ZoomRL achieves a worst-case regret
$\tilde{O}(H^{\frac{5}{2}} K^{\frac{d+1}{d+2}})$ where $H$ is the planning
horizon, $K$ is the number of episodes and $d$ is the covering dimension of the
space with respect to the metric. Moreover, our algorithm enjoys improved
metric-dependent guarantees that reflect the geometry of the underlying space.
Finally, we show that our algorithm is robust to small misspecification errors.


  Amorphous packings of spheres have been intensely investigated in order to
understand the mechanical and flow behaviour of dense granular matter, and to
explore universal aspects of the transition from fluid to structurally arrested
or jammed states. Considerable attention has recently been focussed on
anisotropic packings of frictional grains generated by shear deformation
leading to shear jamming, which occurs below the jamming density for isotropic
packings of frictionless grains. With the aim of disentangling the role of
shear deformation induced structures and friction in generating shear jamming,
we study sheared assemblies of frictionless spheres computationally, over a
wide range of densities, extending far below the isotropic jamming point. We
demonstrate the emergence of a variety of geometric features characteristic of
jammed packings with the increase of shear strain. The average contact number
and the distributions of contact forces suggest the presence of a threshold
density, well below the isotropic jamming point, above which a qualitative
change occurs in the jamming behaviour of sheared configurations. We show that
above this threshold density, friction stabilizes the sheared configurations we
generate. Our results thus reveal the emergence of geometric features
characteristic of jammed states as a result of shear deformation alone, while
friction is instrumental in stabilising packings over a range of densities
below the isotropic jamming point.


  Topology plays a fundamental role in our understanding of many-body physics,
from vortices and solitons in classical field theory, to phases and excitations
in quantum matter. Topological phenomena are intimately connected to the
distribution of information content - that, differently from ordinary matter,
is now governed by non-local degrees of freedom. However, a precise
characterization of how topological effects govern the complexity of a
many-body state - i.e., its partition function - is presently unclear. In this
work, we show how topology and complexity are directly intertwined concepts in
the context of classical statistical mechanics. In concrete, we present a
theory that shows how the Kolmogorov complexity of a classical partition
function sampling carries unique, distinctive features depending on the
presence of topological excitations in the system. We confront two-dimensional
Ising, Heisenberg, and XY models on several topologies and study the
corresponding samplings as high-dimensional manifolds in configuration space,
quantifying their complexity via the intrinsic dimension. While for the Ising
and Heisenberg models the intrinsic dimension is independent of the real-space
topology, for the XY model it depends crucially on temperature: across the
Berezkinskii-Kosterlitz-Thouless (BKT) transition, complexity becomes topology
dependent. In the BKT phase, it displays a characteristic dependence on the
homology of the real-space manifold, and, for $g$-torii, it follows a scaling
that is solely genus dependent. We argue that this behavior is intimately
connected to the emergence of an order parameter in data space, the conditional
connectivity, that displays scaling behavior.


  Lattice QCD plays an increasing role in reducing theoretical uncertainties in
kaon decays. Here we focus on kaon decay channels $K\to \ell\nu_\ell \ell'^+
\ell'^-$, which are closely related to radiative kaon decays since the lepton
pairs $\ell'^+ \ell'^-$ come from virtual photon emission: $K\to \ell\nu_\ell
\gamma^* \to \ell\nu_\ell \ell'^+ \ell'^-$. Compared with real photon emission,
these channels involve more complicated form factors due to the off-shell
photon with possible large momentum transfer, which causes a challenge to
lattice-QCD studies. In this work, we introduce a lattice calculation procedure
for their decay width, which can avoid parameterization of form factors. The
systematic errors in our method are found to be controllable. Infinite volume
reconstruction method is adopted to remove the temporal truncation effects and
reduce finite volume effects from kaon intermediate state. This approach sets
up a bridge between lattice QCD calculation and experimental measurement of
decay width.


  We study the category $\mathcal{F}_n$ of finite-dimensional integrable
representations of the periplectic Lie superalgebra $\mathfrak{p}(n)$. We
define an action of the Temperley--Lieb algebra with infinitely many generators
and defining parameter $0$ on the category $\mathcal{F}_n$ by translation
functors. We also introduce combinatorial tools, called weight diagrams and
arrow diagrams for $\mathfrak{p}(n)$ resembling those for $\mathfrak{gl}(m|n)$.
Using the Temperley--Lieb algebra action and the combinatorics of weight and
arrow diagrams, we then calculate the multiplicities of standard and costandard
modules in indecomposable projective modules and classify the blocks of
$\mathcal{F}_n$. We also prove that indecomposable projective modules in this
category are multiplicity-free.


  We present the results of the search for spherical volumes containing no
galaxies with luminosities brighter than the Magellanic Clouds in the Local
Supercluster and its vicinity. Within a distance of 40 Mpc from us, 89 cosmic
voids were discovered with the diameters of 24 to 12 Mpc, containing no
galaxies with absolute magnitudes brighter than M_K < -18.4. A list of these
voids and the sky distribution maps are given. It was found that 93% of
spherical voids overlap, forming three more extended percolated voids
(hypervoids). The largest of them, HV1, has 56 initial spherical cells and
extends in a horseshoe shape, enveloping the Local Volume and the Virgo
cluster. The Local Void (Tully, 1988) in the Hercules-Aquila region is the
closest part of the HV1. Another hypervoid, HV2, contains 22 spherical voids in
the Eridanus constellation, and the third compact hypervoid (HV3) comprises 6
spherical cells in the Bootes. The total volume of these voids incorporates
about 30% of the Local Universe. Among 2906 dwarf galaxies excluded from the
original sample (n = 10502) in the search for spherical volumes, only 68 are
located in the voids we have discovered. They are characterized by late
morphological types (85% are Ir, Im, BCD, Sm), absolute magnitudes M_B ranging
from -13.0 to -16.7, moderate star formation rates (log SSFR ~ -10
M_sun/(yr*L_sun) and gas reserves per luminosity unit twice to three times
larger than in the other dwarf galaxies located in normal environments. The
dwarf population of the voids shows a certain tendency to sit shallow near the
surfaces of cosmic voids.


  Based on our first detailed $^{181}$Ta nuclear quadrupole resonance (NQR)
studies from 2017 on the Weyl semimetal TaP, we now extended our NQR studies to
another Ta-based monopnictide TaAs. In the present work, we have determined the
temperature-dependent $^{181}$Ta-NQR spectra, the spin-lattice relaxation time
$T_{1}$, and the spin-spin relaxation time $T_{2}$. We found the following
characteristic features that showed great contrast to what was found in TaP:
(1) The quadrupole coupling constant and asymmetry parameter of EFG, extracted
from three NQR frequencies, have a strong temperature dependence above $\sim$80
K that cannot be explained by the density functional theory calculation
incorporating the thermal expansion of the lattice. (2) The temperature
dependence of the spin-lattice relaxation rate, $1/T_{1} T$, shows a $T^{4}$
power law behavior above $\sim$30 K. This is a great contrast with the $1/T_{1}
T \propto T^{2}$ behavior found in TaP, which was ascribed to the magnetic
excitations at the Weyl nodes with a temperature-dependent orbital hyperfine
coupling. (3) Regarding the nuclear spin-spin interaction, we found the
spin-echo signal decays with the pulse separation simply by a Lorentzian
function in TaAs, but we have observed spin-echo modulations in TaP that is
most likely due to the indirect nuclear spin-spin coupling via virtually
excited Weyl fermions. From our experimental findings, we conclude that the
present NQR results do not show dominant contributions from Weyl fermion
excitations in TaAs.


  Spectra, triple and quartic gauge couplings of the Higgsless model with gauge
group $SU(2)_L\times SU(2)_R\times U(1)_{B-L}$ defined in warped space are
explored with numerical method. We extend the equation of motions, boundary
conditions and formalism of multi-gauge-boson vertices to the Hirn-Sanz
scenario. By assuming the ideally delocalized fermion profile, we study the
spectra of vector bosons as well as the triple and quartic gauge couplings
among vector bosons. It is found that mass spectra can be greatly modified by
the parameters of QCD power corrections. Meanwhile, the triple and quartic
gauge couplings can deviate from the values of the standard model to at least
$\pm 10%$ and can saturate the LEP2 bounds. We find the triple gauge couplings
of $Z{\bar W}W$ can be $ 50 %$ smaller than the unitarity bounds. While the
triple gauge couplings of ${\bar Z}WW$ is 20% smaller than the unitarity
bounds, which might challenge the detection of ${\bar Z}$ via s channel at LHC
if $m_{\bar Z}> 500$ GeV.


  In this paper we show that for any affine complete rational surface
singularity there is a correspondence between the dual graph of the minimal
resolution and the quiver of the endomorphism ring of the special CM modules.
We thus call such an algebra the reconstruction algebra. As a consequence the
derived category of the minimal resolution is equivalent to the derived
category of an algebra whose quiver is determined by the dual graph. Also, for
any finite subgroup G of GL(2,C), it means that the endomorphism ring of the
special CM C[[x,y]]^G modules can be used to build the dual graph of the
minimal resolution of C^2/G, extending McKay's observation for finite subgroups
of SL(2,C) to all finite subgroups of GL(2,C).


  In electronic systems with long-range Coulomb interaction, the nonlocal Fock
exchange term has a band-widening effect. While this effect is included in
combined many-body perturbation theory and dynamical mean field theory schemes,
it is not taken into account in standard extended DMFT (EDMFT) calculations.
Here, we include this instantaneous term in both approaches and investigate its
effect on the phase diagram and dynamically screened interaction. We show that
the largest deviations between previously presented EDMFT and $GW$+EDMFT
results originate from the nonlocal Fock term, and that the quantitative
differences are especially large in the strong-coupling limit. Furthermore, we
show that the charge-ordering phase diagram obtained in $GW$+EDMFT methods for
moderate interaction values is very similar to the one predicted by dual boson
methods that include the fermion-boson or four-point vertex.


  In recent years, there have been significant advances in the use of deep
learning methods in inverse problems such as denoising, compressive sensing,
inpainting, and super-resolution. While this line of works has predominantly
been driven by practical algorithms and experiments, it has also given rise to
a variety of intriguing theoretical problems. In this paper, we survey some of
the prominent theoretical developments in this line of works, focusing in
particular on generative priors, untrained neural network priors, and unfolding
algorithms. In addition to summarizing existing results in these topics, we
highlight several ongoing challenges and open problems.


  We investigate the behaviour of low angular momentum viscous accretion flows
around black holes using Smooth Particle Hydrodynamics (SPH) method. Earlier,
it has been observed that in a significant part of the energy and angular
momentum parameter space, rotating transonic accretion flow undergoes shock
transition before entering in to the black hole and a part of the post-shock
matter is ejected as bipolar outflows, which are supposed to be the precursor
of relativistic jets. In this work, we simulate accretion flows having
injection parameters from the inviscid shock parameter space, and study the
response of viscosity on them. With the increase of viscosity, shock becomes
time dependent and starts to oscillate when the viscosity parameter crosses its
critical value. As a result, the in falling matter inside the post-shock region
exhibits quasi-periodic variations and causes periodic ejection of matter from
the inner disc as outflows. In addition, the same hot and dense post-shock
matter emits high energy radiation and the emanating photon flux also modulates
quasi-periodically. Assuming a ten solar mass black hole, the corresponding
power density spectrum peaks at the fundamental frequency of few Hz followed by
multiple harmonics. This feature is very common in several outbursting black
hole candidates. We discuss the implications of such periodic variations.


  Deep learning-based face restoration models, increasingly prevalent in smart
devices, have become targets for sophisticated backdoor attacks. These attacks,
through subtle trigger injection into input face images, can lead to unexpected
restoration outcomes. Unlike conventional methods focused on classification
tasks, our approach introduces a unique degradation objective tailored for
attacking restoration models. Moreover, we propose the Adaptive Selective
Frequency Injection Backdoor Attack (AS-FIBA) framework, employing a neural
network for input-specific trigger generation in the frequency domain,
seamlessly blending triggers with benign images. This results in imperceptible
yet effective attacks, guiding restoration predictions towards subtly degraded
outputs rather than conspicuous targets. Extensive experiments demonstrate the
efficacy of the degradation objective on state-of-the-art face restoration
models. Additionally, it is notable that AS-FIBA can insert effective backdoors
that are more imperceptible than existing backdoor attack methods, including
WaNet, ISSBA, and FIBA.


  Pre-trained models have been a foundational approach in speech recognition,
albeit with associated additional costs. In this study, we propose a
regularization technique that facilitates the training of visual and
audio-visual speech recognition models (VSR and AVSR) from scratch. This
approach, abbreviated as \textbf{MSRS} (Multimodal Speech Recognition from
Scratch), introduces a sparse regularization that rapidly learns sparse
structures within the dense model at the very beginning of training, which
receives healthier gradient flow than the dense equivalent. Once the sparse
mask stabilizes, our method allows transitioning to a dense model or keeping a
sparse model by updating non-zero values. MSRS achieves competitive results in
VSR and AVSR with 21.1% and 0.9% WER on the LRS3 benchmark, while reducing
training time by at least 2x. We explore other sparse approaches and show that
only MSRS enables training from scratch by implicitly masking the weights
affected by vanishing gradients.


  We introduce a solvable stochastic model inspired by granular gases for
driven dissipative systems. We characterize far from equilibrium steady states
of such systems through the non-Boltzmann energy distribution and compare
different measures of effective temperatures. As an example we demonstrate that
fluctuation-dissipation relations hold, however with an effective temperature
differing from the effective temperature defined from the average energy.


  In quantizing classical mechanical systems one often sums over the classical
trajectories as in localization formulas, but also takes into account the
contributions of the "instanton gas": a set of approximate solutions of the
equations of motion. This paper attempts to alleviate some of the frustrations
of this 40+ years old approach by finding the honest solutions of equations of
motion of the complexified classical mechanical system. These ideas originate
in the Bethe/gauge correspondence. The examples include algebraic integrable
systems, from the abstract Hitchin systems to the well-studied anharmonic
oscillator. We also speculate on the applications to the black hole radiation.
We elucidate the relation between Lefschetz thimbles and the $\Omega$-deformed
$B$-model. We propose the notion of the topological renormalization group.


  Scattering from conformal interfaces in two dimensions is universal in that
the flux of reflected and transmitted energy does not depend on the details of
the initial state. In this letter, we present the first gravitational
calculation of energy reflection and transmission coefficients for interfaces
with thin-brane holographic duals. Our result for the reflection coefficient
depends monotonically on the tension of the dual string anchored at the
interface, and obeys the lower bound recently derived from the ANEC in
conformal field theory. The B(oundary)CFT limit is recovered for infinite ratio
of the central charges.


  Microarchitectural timing side channels have been thoroughly investigated as
a security threat in hardware designs featuring shared buffers (e.g., caches)
or parallelism between attacker and victim task execution. However,
contradicting common intuitions, recent activities demonstrate that this threat
is real even in microcontroller SoCs without such features. In this paper, we
describe SoC-wide timing side channels previously neglected by security
analysis and present a new formal method to close this gap. In a case study on
the RISC-V Pulpissimo SoC, our method detected a vulnerability to a previously
unknown attack variant that allows an attacker to obtain information about a
victim's memory access behavior. After implementing a conservative fix, we were
able to verify that the SoC is now secure w.r.t. the considered class of timing
side channels.


  Lattice modulations in the high magnetic field phase and close to impurities
in spin-Peierls systems are considered and compared to experiment. Necessary
extensions of existing theories are proposed. The influence of zero-point
fluctuations on magnetic amplitudes is shown.


  In recent years, the DBLP computer science bibliography has been prominently
used for searching scholarly information, such as publications, scholars, and
venues. However, its current search service lacks the capability to handle
complex queries, which limits the usability of DBLP. In this paper, we present
NLQxform-UI, a web-based natural language interface that enables users to query
DBLP directly with complex natural language questions. NLQxform-UI
automatically translates given questions into SPARQL queries and executes the
queries over the DBLP knowledge graph to retrieve answers. The querying process
is presented to users in an interactive manner, which improves the transparency
of the system and helps examine the returned answers. Also, intermediate
results in the querying process can be previewed and manually altered to
improve the accuracy of the system. NLQxform-UI has been completely
open-sourced: https://github.com/ruijie-wang-uzh/NLQxform-UI.


  We investigate the configurations consisting of massive, dense and hot tori
around stellar mass Kerr black holes as possible sources of energy for the
gamma ray bursts in cosmological hypothesis of their origin. We limit
parameters of our models to the values resulting from neutron stars merger
calculations or suggested in the ``failed supernova'' scenario. We investigate
models with different angular momentum distributions and different specific
entropies. We construct also approximate evolutionary tracks of our systems
postulating some viscosity mechanism to be present. We find, that models
resulting from a merger of two neutron stars give too little energy to be
likely sources of gamma ray bursts. This conclusion remains true despite the
artificially high values of specific entropy and viscosity, which we use in our
calculations. The promising models should contain a high angular momentum black
hole ($a \sim 1$) and/or a torus with almost constant specific angular
momentum. The configurations resulting from a collapse of rapidly rotating WR
stars are not excluded as sources of the bursts due to a greater freedom in
choosing their initial parameters.


  It is proved the existence of large algebraic structures \break --including
large vector subspaces or infinitely generated free algebras-- inside, among
others, the family of Lebesgue measurable functions that are surjective in a
strong sense, the family of nonconstant differentiable real functions vanishing
on dense sets, and the family of non-continuous separately continuous real
functions. Lineability in special spaces of sequences is also investigated.
Some of our findings complete or extend a number of results by several authors.


  A new semi-parametric Expected Shortfall (ES) estimation and forecasting
framework is proposed. The proposed approach is based on a two-step estimation
procedure. The first step involves the estimation of Value-at-Risk (VaR) at
different quantile levels through a set of quantile time series regressions.
Then, the ES is computed as a weighted average of the estimated quantiles. The
quantiles weighting structure is parsimoniously parameterized by means of a
Beta weight function whose coefficients are optimized by minimizing a joint VaR
and ES loss function of the Fissler-Ziegel class. The properties of the
proposed approach are first evaluated with an extensive simulation study using
two data generating processes. Two forecasting studies with different
out-of-sample sizes are then conducted, one of which focuses on the 2008 Global
Financial Crisis (GFC) period. The proposed models are applied to 7 stock
market indices and their forecasting performances are compared to those of a
range of parametric, non-parametric and semi-parametric models, including
GARCH, Conditional AutoRegressive Expectile (CARE), joint VaR and ES quantile
regression models and simple average of quantiles. The results of the
forecasting experiments provide clear evidence in support of proposed models.


  An interference channel is said to have strong interference if for all input
distributions, the receivers can fully decode the interference. This definition
of strong interference applies to discrete memoryless, scalar and vector
Gaussian interference channels. However, there exist vector Gaussian
interference channels that may not satisfy the strong interference condition
but for which the capacity can still be achieved by jointly decoding the signal
and the interference. This kind of interference is called generally strong
interference. Sufficient conditions for a vector Gaussian interference channel
to have generally strong interference are derived. The sum-rate capacity and
the boundary points of the capacity region are also determined.


  Electronic commerce is emerging as the killer domain for data mining
technology.
  The following are five desiderata for success. Seldom are they they all
present in one data mining application.
  1. Data with rich descriptions. For example, wide customer records with many
potentially useful fields allow data mining algorithms to search beyond obvious
correlations.
  2. A large volume of data. The large model spaces corresponding to rich data
demand many training instances to build reliable models.
  3. Controlled and reliable data collection. Manual data entry and integration
from legacy systems both are notoriously problematic; fully automated
collection is considerably better.
  4. The ability to evaluate results. Substantial, demonstrable return on
investment can be very convincing.
  5. Ease of integration with existing processes. Even if pilot studies show
potential benefit, deploying automated solutions to previously manual processes
is rife with pitfalls. Building a system to take advantage of the mined
knowledge can be a substantial undertaking. Furthermore, one often must deal
with social and political issues involved in the automation of a previously
manual business process.


  Lattice motivated triplet color scalar field theory is analyzed. We consider
non-minimal as well as covariant derivative coupling with SU(2) gauge fields.
Field configurations generated by external electric sources are presented.
Moreover non-Abelian magnetic monopoles are found. Dependence on the spatial
coordinates in the obtained solutions is identical as in the usual Abelian
case. We show also that after a decomposition of the fields a modified
Faddeev-Niemi action can be obtained. It contains explicit O(3) symmetry
breaking term parameterized by the condensate of an isoscalar field. Due to
that Goldstone bosons observed in the original Faddeev-Niemi model are removed.


  We give a general class of exact solutions to the (1+2)-dimensional
topologically massive gravity model coupled with Maxwell-Chern-Simons theory
where a "self-duality" condition is imposed on the Maxwell field.


  The first part of the present paper is devoted to a systematic construction
of continuous-time finite-dimensional integrable systems arising from the
rational su(2) Gaudin model through certain contraction procedures. In the
second part, we derive an explicit integrable Poisson map discretizing a
particular Hamiltonian flow of the rational su(2) Gaudin model. Then, the
contraction procedures enable us to construct explicit integrable
discretizations of the continuous systems derived in the first part of the
paper.


  The combination of Reinforcement Learning (RL) with deep learning has led to
a series of impressive feats, with many believing (deep) RL provides a path
towards generally capable agents. However, the success of RL agents is often
highly sensitive to design choices in the training process, which may require
tedious and error-prone manual tuning. This makes it challenging to use RL for
new problems, while also limits its full potential. In many other areas of
machine learning, AutoML has shown it is possible to automate such design
choices and has also yielded promising initial results when applied to RL.
However, Automated Reinforcement Learning (AutoRL) involves not only standard
applications of AutoML but also includes additional challenges unique to RL,
that naturally produce a different set of methods. As such, AutoRL has been
emerging as an important area of research in RL, providing promise in a variety
of applications from RNA design to playing games such as Go. Given the
diversity of methods and environments considered in RL, much of the research
has been conducted in distinct subfields, ranging from meta-learning to
evolution. In this survey we seek to unify the field of AutoRL, we provide a
common taxonomy, discuss each area in detail and pose open problems which would
be of interest to researchers going forward.


  We propose a new transformer model for the task of unsupervised learning of
skeleton motion sequences. The existing transformer model utilized for
unsupervised skeleton-based action learning is learned the instantaneous
velocity of each joint from adjacent frames without global motion information.
Thus, the model has difficulties in learning the attention globally over
whole-body motions and temporally distant joints. In addition, person-to-person
interactions have not been considered in the model. To tackle the learning of
whole-body motion, long-range temporal dynamics, and person-to-person
interactions, we design a global and local attention mechanism, where, global
body motions and local joint motions pay attention to each other. In addition,
we propose a novel pretraining strategy, multi-interval pose displacement
prediction, to learn both global and local attention in diverse time ranges.
The proposed model successfully learns local dynamics of the joints and
captures global context from the motion sequences. Our model outperforms
state-of-the-art models by notable margins in the representative benchmarks.
Codes are available at https://github.com/Boeun-Kim/GL-Transformer.


  Let $k$ be a field of positive characteristic $p$, and $X$ be a separated of
finite type $k$-scheme of dimension $d$. We construct a cycle map from the
additive cycle complex to the residual complex of Serre-Grothendieck coherent
duality theory. This map is compatible with a cubical version of the map
constructed in [Ren23] arXiv:2104.09662 when $k$ is perfect. As a corollary, we
get injectivity statements for (additive) higher Chow groups as well as for
motivic cohomology (with modulus) with $\mathbb{Z}/p$ coefficients when $k$ is
algebraically closed.


  The individual data collected throughout patient follow-up constitute crucial
information for assessing the risk of a clinical event, and eventually for
adapting a therapeutic strategy. Joint models and landmark models have been
proposed to compute individual dynamic predictions from repeated measures to
one or two markers. However, they hardly extend to the case where the complete
patient history includes much more repeated markers possibly. Our objective was
thus to propose a solution for the dynamic prediction of a health event that
may exploit repeated measures of a possibly large number of markers. We
combined a landmark approach extended to endogenous markers history with
machine learning methods adapted to survival data. Each marker trajectory is
modeled using the information collected up to landmark time, and summary
variables that best capture the individual trajectories are derived. These
summaries and additional covariates are then included in different prediction
methods. To handle a possibly large dimensional history, we rely on machine
learning methods adapted to survival data, namely regularized regressions and
random survival forests, to predict the event from the landmark time, and we
show how they can be combined into a superlearner. Then, the performances are
evaluated by cross-validation using estimators of Brier Score and the area
under the Receiver Operating Characteristic curve adapted to censored data. We
demonstrate in a simulation study the benefits of machine learning survival
methods over standard survival models, especially in the case of numerous
and/or nonlinear relationships between the predictors and the event. We then
applied the methodology in two prediction contexts: a clinical context with the
prediction of death for patients with primary biliary cholangitis, and a public
health context with the prediction of death in the general elderly population
at different ages. Our methodology, implemented in R, enables the prediction of
an event using the entire longitudinal patient history, even when the number of
repeated markers is large. Although introduced with mixed models for the
repeated markers and methods for a single right censored time-to-event, our
method can be used with any other appropriate modeling technique for the
markers and can be easily extended to competing risks setting.


  By an effective Lagrangian plus QCD sum-rule approach, we investigate the
mass shift of the $J/\psi$ state in medium, in symmetric nuclear matter with
zero and finite temperature, and cold strange matter. The in-medium mass of the
$J/\psi$ state is evaluated through the intermediate pseudoscalar $D$-meson
loop for the $J/\psi$ self-energy. The effect of medium is incorporated through
the in-medium mass of $D$ meson calculated using chiral SU(3) model plus QCD
sum-rule approach. The self energy loop integral is regularized using the
phenomenological form factor of the dipole form. We compare our results with
some of the results in the literature. The present results should be helpful to
understand better the expected data from heavy ion collision experiments, such
as CBM and PANDA.


  The RR Lyrae distance scale is reviewed. In particular, we discuss
theoretical and empirical methods currently adopted in the literature.
Moreover, we also outline pros and cons of optical and near-infrared mean
magnitudes to overcome some of the problems currently affecting RR Lyrae
distances. The importance of the K-band Period-Luminosity-Metallicity (PLZ_K)
relation for RR Lyrae is also discussed, together with the absolute calibration
of the zero-point. We also mention some preliminary results based on NIR (J,K)
time series data of the LMC cluster Reticulum. This cluster hosts a sizable
sample of RR Lyrae and its distance is found to be 18.45 +/- 0.04 mag using the
predicted PLZ_K relation and 18.51 +/- 0.06 using the PLZ_J relation. We
briefly discuss the evolutionary status of Anomalous Cepheids and their
possible use as distance indicators. Finally, we point out some possible
improvements to improve the intrinsic accuracy of theory and observations.


  Real-world problems are often comprised of many objectives and require
solutions that carefully trade-off between them. Current approaches to
many-objective optimization often require challenging assumptions, like
knowledge of the importance/difficulty of objectives in a weighted-sum
single-objective paradigm, or enormous populations to overcome the curse of
dimensionality in multi-objective Pareto optimization. Combining elements from
Many-Objective Evolutionary Algorithms and Quality Diversity algorithms like
MAP-Elites, we propose Many-objective Optimization via Voting for Elites
(MOVE). MOVE maintains a map of elites that perform well on different subsets
of the objective functions. On a 14-objective image-neuroevolution problem, we
demonstrate that MOVE is viable with a population of as few as 50 elites and
outperforms a naive single-objective baseline. We find that the algorithm's
performance relies on solutions jumping across bins (for a parent to produce a
child that is elite for a different subset of objectives). We suggest that this
type of goal-switching is an implicit method to automatic identification of
stepping stones or curriculum learning. We comment on the similarities and
differences between MOVE and MAP-Elites, hoping to provide insight to aid in
the understanding of that approach $\unicode{x2013}$ and suggest future work
that may inform this approach's use for many-objective problems in general.


  Two-dimensional almost-Riemannian structures are generalized Riemannian
structures on surfaces for which a local orthonormal frame is given by a Lie
bracket generating pair of vector fields that can become collinear. We consider
the Carnot--Caratheodory distance canonically associated with an
almost-Riemannian structure and study the problem of Lipschitz equivalence
between two such distances on the same compact oriented surface. We analyse the
generic case, allowing in particular for the presence of tangency points, i.e.,
points where two generators of the distribution and their Lie bracket are
linearly dependent. The main result of the paper provides a characterization of
the Lipschitz equivalence class of an almost-Riemannian distance in terms of a
labelled graph associated with it.


  Due to popularity surge social networks became lucrative targets for spammers
and guerilla marketers, who are trying to game ranking systems and broadcast
their messages at little to none cost. Ranking systems, for example Twitter's
Trends, can be gamed by scripted users also called bots, who are automatically
or semi-automatically twitting essentially the same message. Judging by the
prices and abundance of supply from PR firms this is an easy to implement and
widely used tactic, at least in Russian blogosphere. Aggregative analysis of
social networks should at best mark those messages as spam or at least
correctly downplay their importance as they represent opinions only of a few,
if dedicated, users. Hence bot detection plays a crucial role in social network
mining and analysis. In this paper we propose technique called RepRank which
could be viewed as Markov chain based model for reputation propagation on
graphs utilizing simultaneous trust and anti-trust propagation and provide
effective numerical approach for its computation. Comparison with another
models such as TrustRank and some of its modifications on sample of 320000
Russian speaking Twitter users is presented. The dataset is presented as well.


  Eliciting scalability requirements during agile software development is
complicated and poorly described in previous research. This article presents a
lightweight artifact for eliciting scalability requirements during agile
software development: the ScrumScale model. The ScrumScale model is a simple
spreadsheet. The scalability concepts underlying the ScrumScale model are
clarified in this design science research, which also utilizes coordination
theory. This paper describes the open banking case study, where a legacy
banking system becomes open. This challenges the scalability of this legacy
system. The first step in understanding this challenge is to elicit the new
scalability requirements. In the open banking case study, key stakeholders from
TietoEVRY spent 55 hours eliciting TietoEVRY's open banking project's
scalability requirements. According to TietoEVRY, the ScrumScale model provided
a systematic way of producing scalability requirements. For TietoEVRY, the
scalability concepts behind the ScrumScale model also offered significant
advantages in dialogues with other stakeholders.


  The (D+1)-dimensional $(\beta,\beta')$-two-parameter Lorentz-covariant
deformed algebra introduced by Quesne and Tkachuk [C. Quesne and V. M. Tkachuk,
J. Phys. A: Math. Gen. \textbf {39}, 10909 (2006).], leads to a nonzero minimal
uncertainty in position (minimal length). The Klein-Gordon equation in a
(3+1)-dimensional space-time described by Quesne-Tkachuk Lorentz-covariant
deformed algebra is studied in the case where $\beta'=2\beta$ up to first order
over deformation parameter $\beta$. It is shown that the modified Klein-Gordon
equation which contains fourth-order derivative of the wave function describes
two massive particles with different masses. We have shown that physically
acceptable mass states can only exist for $\beta<\frac{1}{8m^{2}c^{2}}$ which
leads to an isotropic minimal length in the interval $10^{-17}m<(\bigtriangleup
X^{i})_{0}<10^{-15}m$. Finally, we have shown that the above estimation of
minimal length is in good agreement with the results obtained in previous
investigations.


  Rotational Freudenthal duality (RFD) relates two extremal Kerr-Newman (KN)
black holes (BHs) with different angular momenta and electric-magnetic charges,
but with the same Bekenstein-Hawking entropy. Through the Kerr/CFT
correspondence (and its KN extension), a four-dimensional, asymptotically flat
extremal KN BH is endowed with a dual thermal, two-dimensional conformal field
theory (CFT) such that the Cardy entropy of the CFT is the same as the
Bekenstein-Hawking entropy of the KN BH itself. Using this connection, we study
the effect of the RFD on the thermal CFT dual to the KN extremal BH. We find
that the RFD maps two different thermal, two-dimensional CFTs with different
temperatures and central charges, but with the same asymptotic density of
states, thereby matching the Cardy entropy. In an appendix, we discuss the
action of the RFD on doubly-extremal rotating BHs, finding a spurious branch in
the non-rotating limit, and determining that for this class of BH solutions the
image of the RFD necessarily over-rotates.


  The aim of the present study is to make for the first time in the literature
a systematic and quantitative assessment of the evaluation of the imaginary
part of the optical potential calculated within the folding model and its
consequences on the localization of surface reactions. Comparing theoretical
and experimental reaction cross sections, for some light projectiles on a
$^9$Be target, it has recently been shown that a single-folded s.f. (light-)
nucleus-$^9$Be imaginary optical potential is more accurate than a
double-folded d.f. optical potential. Within the eikonal formalism for the
cross sections and phase shifts, the single-folded potential was obtained using
a n-$^9$Be phenomenological optical potential and microscopic projectile
densities. This paper is a follow-up in which we systematically study a series
of different light and medium-mass projectile induced reactions on $^9$Be. Our
results confirm that the s.f. cross sections are larger than the d.f. cross
sections and the effect increases with the projectile mass. Furthermore the
strong absorption radius parameter extracted from the $S$ matrices calculated
with the s.f. has a stable value $r_s$ =1.3 - 1.4 fm for all projectile masses
in the range of incident energies 40-100AMeV. This indicates that a clear
geometrical separation can be made between the region of surface reactions, the
region of strong absorption into other channels and the region of weak nuclear
interaction. The d.f. results are instead much scattered and the separation
between surface reactions and other channels does not seem to be consistent.
Excellent agreement with recent experimental results confirms the validity of
our approach.


  The Time Projection Chamber is the main tracking and particle identification
detector of the ALICE experiment. The high luminosities delivered by the CERN
LHC in Run 2 (2015-2018) posed new challenges in terms of detector performance
and efficiency. The hardware components and calibration software were optimized
and further developed to meet those challenges and maximize the quality of the
data. In addition, unexpectedly large local distortions of the drift paths of
ionization electrons have been observed at the edges of specific readout
chambers. These distortions are caused by ions which originate at the readout
chambers, leading to local space-charge accumulation in the drift volume of the
TPC. A new calibration procedure has been developed to correct for the
space-charge distortions. Extensive studies have been performed to understand
the origin of the space charge as well as to find a way to effectively mitigate
the effect. For Run 3 starting in 2021, the new readout chambers of the
upgraded TPC will be based on Gas Electron Multipliers. This implies an
intrinsic backflow of ions which leads to large space-charge distortions in
most of the TPC drift volume at the highest luminosities. The simulation and
calibration of the space-charge effect are a major part of the new detector
software framework.


  It has been recently conjectured that the state-independency of quantum
contextuality may be lost when the indistinguishability of identical particles
is taken into account. Here, we show that quantum state-independent
contextuality exists for any system of more than one identical bosonic qudits,
and for most systems of fermionic qudits. The only exception is the case of d
fermionic qudits, since there the dimension of the antisymmetric subspace is 1,
which is insufficient for contextuality. For all the other cases, either the
symmetry precludes the existence of physical states, or we provide an explicit
method to produce quantum state-independent contextual correlations.


  This paper describes a formal general-purpose automated program repair (APR)
framework based on the concept of program invariants. In the presented repair
framework, the execution traces of a defected program are dynamically analyzed
to infer specifications $\varphi_{correct}$ and $\varphi_{violated}$, where
$\varphi_{correct}$ represents the set of likely invariants (good patterns)
required for a run to be successful and $\varphi_{violated}$ represents the set
of likely suspicious invariants (bad patterns) that result in the bug in the
defected program. These specifications are then refined using rigorous program
analysis techniques, which are also used to drive the repair process towards
feasible patches and assess the correctness of generated patches.We demonstrate
the usefulness of leveraging invariants in APR by developing an invariant-based
repair system for performance bugs. The initial analysis shows the
effectiveness of invariant-based APR in handling performance bugs by producing
patches that ensure program's efficiency increase without adversely impacting
its functionality.


  Remote sensing measurements have been an important data source of ocean
surface roughness. Scatterometers operating at moderate and high incidence
angles provide information on the Bragg resonance spectral components of the
ocean surface waves. Monostatic and bistatic reflectometers provide spectrally
integrated information of ocean waves longer than several times the incident
electromagnetic (EM) wavelengths. The integrated surface roughness is generally
expressed as the lowpass mean square slope (LPMSS). Tilting modification of the
local incidence angle for the specular facets located on slanted background
surfaces is an important factor in relating the LPMSS and microwave specular
returns. For very high wind condition, it is necessary to consider the
modification of relative permittivity by air in foam and whitecaps produced by
wave breaking. This paper describes the application of these considerations to
monostatic and bistatic microwave specular returns from the ocean surface.
Measurements from Ku band altimeters and L band reflectometers are used for
illustration. It remains a challenge to acquire sufficient number of high wind
collocated and simultaneous reference measurements for algorithm development or
validation and verification effort. Solutions from accurate forward computation
can supplement the sparse high wind databases. Modeled specular normalized
radar cross sections (NRCSs) for L, C, X, Ku, and Ka bands with wind speeds up
to 99 m/s are provided.


  The popularity of graphene--a pseudospin-1/2 two-dimensional Dirac-Weyl
material--has prompted the search for related materials and the
characterization of their properties. In this work, the magneto-optical
conductivity is calculated for systems that obey the general pseudospin-s
two-dimensional Dirac-Weyl Hamiltonian, with particular focus on s = {1/2, 1,
3/2, 2}. This generalizes calculations that have been made for s = 1/2 and
follows previous work on the optical response of these systems in zero field.
In the presence of a magnetic field, Landau levels condense out of the 2s+1
energy bands. As the chemical potential in a system is shifted, patterns arise
in the appearance and disappearance of certain peaks within the optical
spectra. These patterns are markedly different for each case considered,
creating unique signatures in the magneto-optics. The general structure of each
spectrum and how they compare is discussed.


  We present True2F, a system for second-factor authentication that provides
the benefits of conventional authentication tokens in the face of phishing and
software compromise, while also providing strong protection against token
faults and backdoors. To do so, we develop new lightweight two-party protocols
for generating cryptographic keys and ECDSA signatures, and we implement new
privacy defenses to prevent cross-origin token-fingerprinting attacks. To
facilitate real-world deployment, our system is backwards-compatible with
today's U2F-enabled web services and runs on commodity hardware tokens after a
firmware modification. A True2F-protected authentication takes just 57ms to
complete on the token, compared with 23ms for unprotected U2F.


  We introduce a methodology for analysis of multiwavelength data from X-ray
selected BL Lac (XBL) objects detected in the TeV regime. By assuming that the
radio--through--X-ray flux from XBLs is nonthermal synchrotron radiation
emitted by isotropically-distributed electrons in the randomly oriented
magnetic field of a relativistic blazar jet, we obtain the electron spectrum.
This spectrum is then used to deduce the synchrotron self-Compton (SSC)
spectrum as a function of the Doppler factor, magnetic field, and variability
timescale. The variability timescale is used to infer the comoving blob radius
from light travel-time arguments, leaving only two parameters. With this
approach, we accurately simulate the synchrotron and SSC spectrum of flaring
XBLs in the Thomson through Klein-Nishina regimes. Photoabsorption by
interactions with internal jet radiation and the intergalactic background light
(IBL) is included. Doppler factors, magnetic fields, and absolute jet powers
are obtained by fitting the {\em HESS} and {\em Swift} data of the recent giant
TeV flare observed from \object{PKS 2155--304}. For the contemporaneous {\em
Swift} and {\em HESS} data from 28 and 30 July 2006, respectively, Doppler
factors $\gtrsim 60$ and absolute jet powers $\gtrsim 10^{46}$ ergs s$^{-1}$
are required for a synchrotron/SSC model to give a good fit to the data, for a
low intensity of the IBL and a ratio of 10 times more energy in hadrons than
nonthermal electrons. Fits are also made to a TeV flare observed in 2001 from
Mkn 421 which require Doppler factors $\gtrsim 30$ and jet powers $\gtrsim
10^{45}$ erg s$^{-1}$.


  By employing CFT techniques, we show how to compute in the context of
\lambda-deformations of current algebras and coset CFTs the exact in the
deformation parameters C-function for a wide class of integrable theories that
interpolate between a UV and an IR point. We explicitly consider RG flows for
integrable deformations of left-right asymmetric current algebras and coset
CFTs. In all cases, the derived exact C-functions obey all the properties
asserted by Zamolodchikov's c-theorem in two-dimensions.


  Discovering precise and interpretable rules from knowledge graphs is regarded
as an essential challenge, which can improve the performances of many
downstream tasks and even provide new ways to approach some Natural Language
Processing research topics. In this paper, we present a fundamental theory for
rule-based knowledge graph reasoning, based on which the connectivity
dependencies in the graph are captured via multiple rule types. It is the first
time for some of these rule types in a knowledge graph to be considered. Based
on these rule types, our theory can provide precise interpretations to unknown
triples. Then, we implement our theory by what we call the RuleDict model.
Results show that our RuleDict model not only provides precise rules to
interpret new triples, but also achieves state-of-the-art performances on one
benchmark knowledge graph completion task, and is competitive on other tasks.


  Modifiable combining functions are a synthesis of two common approaches to
combining evidence. They offer many of the advantages of these approaches and
avoid some disadvantages. Because they facilitate the acquisition,
representation, explanation, and modification of knowledge about combinations
of evidence, they are proposed as a tool for knowledge engineers who build
systems that reason under uncertainty, not as a normative theory of evidence.


  The Fortran code SDECAY calculates the decay widths and branching ratios of
all supersymmetric (SUSY) particles in the Minimal Supersymmetric Standard
Model (MSSM), including higher order effects. The usual two-body decays of
sfermions and gauginos as well as the three-body decay modes of charginos,
neutralinos and gluinos are included. Furthermore, the three-body stop and
sbottom decays and even the four-body stop decays are calculated. The important
loop-induced decays, the QCD corrections to the two-body widths involving
strongly interacting particles and the dominant electroweak effects to all
processes are evaluated as well.


  Context. The combination of wideband receivers and spectrometers currently
available in (sub-)millimeter observatories deliver wide- field hyperspectral
imaging of the interstellar medium. Tens of spectral lines can be observed over
degree wide fields in about fifty hours. This wealth of data calls for
restating the physical questions about the interstellar medium in statistical
terms. Aims. We aim at gaining information on the physical structure of the
interstellar medium from a statistical analysis of many lines from different
species over a large field of view, without requiring detailed radiative
transfer or astrochemical modeling. Methods. We coupled a nonlinear rescaling
of the data with one of the simplest multivariate analysis methods, namely the
Principal Component Analysis, to decompose the observed signal into components
that we interpret first qualitatively and then quantitatively based on our deep
knowledge of the observed region and of the astrochemistry at play. Results. We
identify 3 principal components, linear compositions of line brightness
temperatures, that are correlated at various levels with the column density,
the volume density and the UV radiation field. Conclusions. When sampling a
sufficiently diverse mixture of physical parameters, it is possible to
decompose the molecular emission in order to gain physical insight on the
observed interstellar medium. This opens a new avenue for future studies of the
interstellar medium.


  We present new classes of supersymmetric Standard-like models from type IIA
$\IT^6/(\IZ_2\times \IZ_2)$ orientifold with intersecting D6-branes. D6-branes
can wrap general supersymmetric three-cycles of $\IT^6=\IT^2\times \IT^2\times
\IT^2$, and any $\IT^2$ is allowed to be tilted. The models still suffer from
additional exotics, however we obtained solutions with fewer Higgs doublets, as
well as models with all three families of left-handed quarks and leptons
arising from the same intersecting sector, and examples of a genuine left-right
symmetric model with three copies of left-handed and right-handed families of
quarks and leptons.


  Rate-Splitting (RS) has recently been shown to provide significant
performance benefits in various multi-user transmission scenarios. In parallel,
the huge degrees-of-freedom provided by the appealing massive Multiple-Input
Multiple-Output (MIMO) necessitate the employment of inexpensive hardware,
being more prone to hardware imperfections, in order to be a cost-efficient
technology. Hence, in this work, we focus on a realistic massive Multiple-Input
Single-Output (MISO) Broadcast Channel (BC) hampered by the inevitable hardware
impairments. We consider a general experimentally validated model of hardware
impairments, accounting for the presence of \textit{multiplicative distortion}
due to phase noise, \textit{additive distortion noise} and \textit{thermal
noise amplification}. Under both scenarios with perfect and imperfect channel
state information at the transmitter (CSIT), we analyze the potential
robustness of RS to each separate hardware imperfection. We analytically assess
the sum-rate degradation due to hardware imperfections. Interestingly, in the
case of imperfect CSIT, we demonstrate that RS is a robust strategy for
multiuser MIMO in the presence of phase and amplified thermal noise, since its
sum-rate does not saturate at high signal-to-noise ratio (SNR), contrary to
conventional techniques. On the other hand, the additive impairments always
lead to a sum-rate saturation at high SNR, even after the application of RS.
However, RS still enhances the performance. Furthermore, as the number of users
increases, the gains provided by RS decrease not only in ideal conditions, but
in practical conditions with RTHIs as well.


  Recent deep learning based face recognition methods have achieved great
performance, but it still remains challenging to recognize very low-resolution
query face like 28x28 pixels when CCTV camera is far from the captured subject.
Such face with very low-resolution is totally out of detail information of the
face identity compared to normal resolution in a gallery and hard to find
corresponding faces therein. To this end, we propose a Resolution Invariant
Model (RIM) for addressing such cross-resolution face recognition problems,
with three distinct novelties. First, RIM is a novel and unified deep
architecture, containing a Face Hallucination sub-Net (FHN) and a Heterogeneous
Recognition sub-Net (HRN), which are jointly learned end to end. Second, FHN is
a well-designed tri-path Generative Adversarial Network (GAN) which
simultaneously perceives facial structure and geometry prior information, i.e.
landmark heatmaps and parsing maps, incorporated with an unsupervised
cross-domain adversarial training strategy to super-resolve very low-resolution
query image to its 8x larger ones without requiring them to be well aligned.
Third, HRN is a generic Convolutional Neural Network (CNN) for heterogeneous
face recognition with our proposed residual knowledge distillation strategy for
learning discriminative yet generalized feature representation. Quantitative
and qualitative experiments on several benchmarks demonstrate the superiority
of the proposed model over the state-of-the-arts. Codes and models will be
released upon acceptance.