  We present the first successful potential model description of Li-6 -- He-4
scattering. The differential cross-sections for three energies and the vector
analyzing powers for two energies were fitted by a single potential with energy
dependent imaginary components. An essential ingredient is a set of Majorana
terms in each component. The potential was determined using a recently
developed direct data-to-potential inversion method which is a generalisation
of the IP S-matrix-to-potential inversion algorithm. We discuss the problems
related to this phenomenological approach, and discuss the relationship of our
results to existing and future theories.


  We review the finite element approximation of the classical obstacle problem
in energy and max-norms and derive error estimates for both the solution and
the free boundary. On the basis of recent regularity results we present an
optimal error analysis for the thin obstacle problem. Finally, we discuss the
localization of the obstacle problem for the fractional Laplacian and prove
quasi-optimal convergence rates.


  In this work we study how to learn good algorithms for selecting reasoning
steps in theorem proving. We explore this in the connection tableau calculus
implemented by leanCoP where the partial tableau provides a clean and compact
notion of a state to which a limited number of inferences can be applied. We
start by incorporating a state-of-the-art learning algorithm -- a graph neural
network (GNN) -- into the plCoP theorem prover. Then we use it to observe the
system's behaviour in a reinforcement learning setting, i.e., when learning
inference guidance from successful Monte-Carlo tree searches on many problems.
Despite its better pattern matching capability, the GNN initially performs
worse than a simpler previously used learning algorithm. We observe that the
simpler algorithm is less confident, i.e., its recommendations have higher
entropy. This leads us to explore how the entropy of the inference selection
implemented via the neural network influences the proof search. This is related
to research in human decision-making under uncertainty, and in particular the
probability matching theory. Our main result shows that a proper entropy
regularisation, i.e., training the GNN not to be overconfident, greatly
improves plCoP's performance on a large mathematical corpus.


  The issue of holographic mapping between bulk and boundary in the plane-wave
limit of AdS/SYM correspondence is reexamined from the viewpoint of correlation
functions. We first study the limit of large angular momentum for the so-called
GKP-W relation in supergeravity approximation, connecting directly the
effective action in the bulk and the generating functional of correlation
functions on the boundary. The spacetime tunneling picture which has been
proposed in our previous works naturally emerges. This gives not only a
justification of our previous proposal, with some important refinements, on the
mapping between bulk effective interaction and the CFT coefficients on the
boundary in the plane-wave limit, but also implies various insights on the
interpretation of holography in the plane-wave limit. Based on this result, we
construct a new `holographic' string field theory. We confirm for several
nontrivial examples that this gives the CFT coefficients derived by
perturbation theory on the gauge-theory side.
  Our results are useful for understanding how apparently different duality
maps proposed from different standpoints are consistent with each other and
with our definite spacetime picture for the AdS holography in the plane-wave
limit.


  Aims. We investigate the configuration of a complex flux rope above a
{\delta} sunspot region in NOAA AR 11515, and its eruptive expansion during a
confined M5.3-class flare.
  Methods. We study the formation of the {\delta} sunspot using continuum
intensity images and photospheric vector magnetograms provided by SDO/HMI. We
use EUV and UV images provided by SDO/AIA, and hard X-ray emission recorded by
RHESSI to investigate the eruptive details. The coronal magnetic field is
extrapolated with a non-linear force free field (NLFFF) method, based on which
the flux rope is identified by calculating the twist number Tw and squashing
factor Q. We search the null point via a modified Powell hybrid method.
  Results. The collision between two emerging spot groups form the {\delta}
sunspot. A bald patch (BP) forms at the collision location, above which a
complex flux rope is identified. The flux rope has multiple layers, with one
compact end and one bifurcated end, having Tw decreasing from the core to the
boundary. A null point is located above the flux rope. The eruptive process
consists of precursor flaring at a 'v'-shaped coronal structure, rise of the
filament, and flaring below the filament, corresponding well with the NLFFF
topological structures, including the null point and the flux rope with BP and
hyperbolic flux tube (HFT). Two sets of post-flare loops and three flare
ribbons support the bifurcation configuration of the flux rope.
  Conclusions. The precursor reconnection, which occurs at the null point,
weakens the overlying confinement to allow the flux rope to rise, fitting the
breakout model. The main phase reconnection, which may occur at the BP or HFT,
facilitates the flux rope rising. The results suggest that the {\delta} spot
configuration presents an environment prone to the formation of complex
magnetic configurations which will work together to produce activities.


  The detection of gamma rays from a small number of Narrow Line Seyfert 1
galaxies by the LAT instrument onboard Fermi seriously challenged our
understanding of AGN physics. Among the most important findings associated with
their discovery has been the realisation that smaller-mass black holes seem to
be hosted by these systems. Immediately after their discovery a radio multi-
frequency monitoring campaign was initiated to understand their jet radio
emission. Here the first results of the campaign are presented. The light
curves and some first variability analyses are discussed, showing that the
brightness temperatures and Doppler factors are moderate. The phenomenologies
are typically blazar-like. The frequency domain on the other hand indicates
intense spectral evolution and the variability patterns indicate mechanisms
similar to those acting in the jets of BL Lacs and FSRQs. Finally, the linear
polarisation also reveals the presence of a quiescent, optically thin jet in
certain cases.


  We investigate the superfluid phases of a Rashba spin-orbit coupled
Bose-Einstein condensate residing on a two dimensional square optical lattice
in the presence of an effective Zeeman field $\Omega$. At a critical value
$\Omega=\Omega_c$, the single-particle spectrum $ E_k $ changes from having a
set of four degenerate minima to a single minimum at $k=0$, corresponding to
condensation at finite or zero momentum, respectively. We describe this quantum
phase transition and the symmetry breaking of the condensate phases. We use the
Bogoliubov theory to treat the superfluid phases and determine the phase
diagram, the excitation spectrum and the sound velocity of the phonon
excitations. A novel dynamically unstable superfluid regime occurring when
$\Omega$ is close to $\Omega_c$ is analytically identified and the behavior of
the condensate quantum depletion is discussed. Moreover, we show that there are
two types of roton excitations occurring in the $\Omega<\Omega_c$ regime and
obtain explicit values for the corresponding energy gaps.


  In recent years, disinformation including fake news, has became a global
phenomenon due to its explosive growth, particularly on social media. The wide
spread of disinformation and fake news can cause detrimental societal effects.
Despite the recent progress in detecting disinformation and fake news, it is
still non-trivial due to its complexity, diversity, multi-modality, and costs
of fact-checking or annotation. The goal of this chapter is to pave the way for
appreciating the challenges and advancements via: (1) introducing the types of
information disorder on social media and examine their differences and
connections; (2) describing important and emerging tasks to combat
disinformation for characterization, detection and attribution; and (3)
discussing a weak supervision approach to detect disinformation with limited
labeled data. We then provide an overview of the chapters in this book that
represent the recent advancements in three related parts: (1) user engagements
in the dissemination of information disorder; (2) techniques on detecting and
mitigating disinformation; and (3) trending issues such as ethics, blockchain,
clickbaits, etc. We hope this book to be a convenient entry point for
researchers, practitioners, and students to understand the problems and
challenges, learn state-of-the-art solutions for their specific needs, and
quickly identify new research problems in their domains.


  In this paper, we prove formulas for the action of Virasoro operators on
Hall-Littlewood polynomials at roots of unity.


  Terahertz (THz)-band communications are currently being celebrated as a key
technology that could fulfill the increasing demands for wireless data traffic
in the upcoming sixth-generation (6G) of wireless communications. Many
challenges, such as high propagation losses and power limitations, which result
in short communication distances, have yet to be addressed for this technology
to be realized. Ultra-massive multiple-input, multiple-output (UM-MIMO) antenna
systems have emerged as practical means for combatting this distance problem,
thereby increasing system capacity. Towards that end, graphene-based
nano-antennas have recently been proposed, as they can be individually tuned
and collectively controlled in compact UM-MIMO array-of-sub-arrays
architectures. In this paper, we present a holistic overview of THz UM-MIMO
systems. We assess recent advancements in transceiver design and channel
modeling, and discuss the major challenges and shortcomings of such designs by
deriving the relationship between communication range, array dimensions, and
system performance. We further highlight several research advances that could
enhance resource allocation at the THz band, including waveform designs,
multi-carrier configurations, and spatial modulations. Based on this
discussion, we highlight prospective use cases that can bring THz UM-MIMO into
reality in the context of sensing, data centers, cell-free systems, and
mid-range wireless communications.


  The SCIP Optimization Suite provides a collection of software packages for
mathematical optimization centered around the constraint integer programming
framework SCIP. This paper discusses enhancements and extensions contained in
version 8.0 of the SCIP Optimization Suite. Major updates in SCIP include
improvements in symmetry handling and decomposition algorithms, new cutting
planes, a new plugin type for cut selection, and a complete rework of the way
nonlinear constraints are handled. Additionally, SCIP 8.0 now supports
interfaces for Julia as well as Matlab. Further, UG now includes a unified
framework to parallelize all solvers, a utility to analyze computational
experiments has been added to GCG, dual solutions can be postsolved by PaPILO,
new heuristics and presolving methods were added to SCIP-SDP, and additional
problem classes and major performance improvements are available in SCIP-Jack.


  The electromagnetic signature of a point explosion near a Kerr black hole
(BH) is evaluated. The first repetitions produced by gravitational lensing are
not periodic in time; periodicity emerges only as the result of multiple
circuits of the prograde and retrograde light rings and is accompanied by
exponential dimming. Gravitational focusing creates a sequence of concentrated
caustic features and biases the detection of a repeating source toward
alignment of the BH spin with the plane of the sky. We consider the
polarization pattern in the case of emission by the Lorentz upboosting and
reflection of a magnetic field near the explosion site. Then the polarized
fraction of the detected pulse approaches unity, and rays propagating near the
equatorial plane maintain a consistent polarization direction. Near a slowly
accreting supermassive BH (SMBH), additional repetitions are caused by
reflection off annular fragments of an orbiting disk that has passed through an
ionization instability. These results are applied to the repeating fast radio
burst (FRB) source 121102, giving a concrete and predictive example of how FRB
detectability may be biased by lensing. A gravitational lensing delay of 10-30
s, and reflection delay up to $\sim 10^4$ s, are found for emission near the
innermost stable circular orbit of a $3\times 10^5\,M_\odot$ SMBH; these
effects combine to produce interesting correlations between delay time and
burst fluence. A similar repetitive pulse envelope could be seen in the
gravitational wave signal produced by a collision between compact stars near a
SMBH.


  Various attack methods against recommender systems have been proposed in the
past years, and the security issues of recommender systems have drawn
considerable attention. Traditional attacks attempt to make target items
recommended to as many users as possible by poisoning the training data.
Benifiting from the feature of protecting users' private data, federated
recommendation can effectively defend such attacks. Therefore, quite a few
works have devoted themselves to developing federated recommender systems. For
proving current federated recommendation is still vulnerable, in this work we
probe to design attack approaches targeting deep learning based recommender
models in federated learning scenarios. Specifically, our attacks generate
poisoned gradients for manipulated malicious users to upload based on two
strategies (i.e., random approximation and hard user mining). Extensive
experiments show that our well-designed attacks can effectively poison the
target models, and the attack effectiveness sets the state-of-the-art.


  The Tutte polynomial is originally a bivariate polynomial which enumerates
the colorings of a graph and of its dual graph. Ardila extended in 2007 the
definition of the Tutte polynomial on the real hyperplane arrangements. He
particularly computed the Tutte polynomials of the hyperplane arrangements
associated to the classical Weyl groups. Those associated to the exceptional
Weyl groups were computed by De Concini and Procesi one year later. This
article has two objectives: On one side, we extend the Tutte polynomial
computing to the complex hyperplane arrangements. On the other side, we
introduce a wider class of hyperplane arrangements which is that of the
symmetric hyperplane arrangements. Computing the Tutte polynomial of a
symmetric hyperplane arrangement permits us to deduce the Tutte polynomials of
some hyperplane arrangements, particularly of those associated to the
imprimitive reflection groups.


  We prove that if $e$ is a join-irreducible element of a semimodular lattice
$L$ of finite length and $h<e$ in $L$ such that $e$ does not cover $h$, then
$e$ can be "lowered" to a covering of $h$ by taking a length-preserving
semimodular extension $K$ of $L$ but not changing the rest of join-irreducible
elements. With the help of our "lowering construction", we prove a general
theorem on length-preserving semimodular extensions of semimodular lattices,
which implies some earlier results proved by G. Gr\"atzer and E. W. Kiss
(1986), M. Wild (1993), and G. Cz\'edli and E. T. Schmidt (2010) on extensions
to geometric lattices, and even an unpublished result of E. T. Schmidt on
higher dimensional rectangular lattices. Our method offers shorter proofs of
these results than the original ones. To obtain the main tool used in the
paper, we extend the bijective correspondence between finite semimodular
lattices and Faigle geometries to an analogous correspondence between
semimodular lattices of finite lengths and a larger class of geometries.


  In the last decade, convolutional neural networks (ConvNets) have been a
major focus of research in medical image analysis. However, the performances of
ConvNets may be limited by a lack of explicit consideration of the long-range
spatial relationships in an image. Recently Vision Transformer architectures
have been proposed to address the shortcomings of ConvNets and have produced
state-of-the-art performances in many medical imaging applications.
Transformers may be a strong candidate for image registration because their
substantially larger receptive field enables a more precise comprehension of
the spatial correspondence between moving and fixed images. Here, we present
TransMorph, a hybrid Transformer-ConvNet model for volumetric medical image
registration. This paper also presents diffeomorphic and Bayesian variants of
TransMorph: the diffeomorphic variants ensure the topology-preserving
deformations, and the Bayesian variant produces a well-calibrated registration
uncertainty estimate. We extensively validated the proposed models using 3D
medical images from three applications: inter-patient and atlas-to-patient
brain MRI registration and phantom-to-CT registration. The proposed models are
evaluated in comparison to a variety of existing registration methods and
Transformer architectures. Qualitative and quantitative results demonstrate
that the proposed Transformer-based model leads to a substantial performance
improvement over the baseline methods, confirming the effectiveness of
Transformers for medical image registration.


  We give a complete re-analysis of the leading twist quark-antiquark
light-cone distribution amplitudes of longitudinal and transverse $\rho$
mesons. We derive Wandzura-Wilczek type relations between different
distributions and update the coefficients in their conformal expansion using
QCD sum rules including next-to-leading order radiative corrections. We find
that the distribution amplitudes of quarks inside longitudinally and
transversely polarized $\rho$ mesons have a similar shape, which is in
contradiction to previous analyses.


  Let $V$ be a vertex operator algebra satisfying suitable conditions such that
in particular its module category has a natural vertex tensor category
structure, and consequently, a natural braided tensor category structure. We
prove that the notions of extension (i.e., enlargement) of $V$ and of
commutative associative algebra, with uniqueness of unit and with trivial
twist, in the braided tensor category of $V$-modules are equivalent.


  There has recently been surprising progress in understanding the spin and
flavor dependence of deep inelastic structure functions in terms of the same
physics needed in the simple quark models used for hadronic spectroscopy.
However, the corresponding scale is usually very low, casting doubt on the use
of leading order $QCD$ evolution. We show that the conclusions are not
significantly altered if one goes to next-to-leading order. In particular, the
excellent agreement with unpolarized and polarized valence quark distributions
is retained.


  Thin-film lithium niobate (TFLN) is superior for integrated nanophotonics due
to its outstanding properties in nearly all aspects: strong second-order
nonlinearity, fast and efficient electro-optic effects, wide transparency
window, and little two photon absorption and free carrier scattering. Together,
they permit highly integrated nanophotonic circuits capable of complex photonic
processing by incorporating disparate elements on the same chip. Yet, there has
to be a demonstration that synergizes those superior properties for system
advantage. Here we demonstrate such a chip that capitalizes on TFLNs favorable
ferroelectricity, high second-order nonlinearity, and strong electro-optic
effects. It consists of a monolithic circuit integrating a Z-cut, quasi-phase
matched microring with high quality factor and a phase modulator used in active
feedback control. By Pound-Drever-Hall locking, it realizes stable frequency
doubling at about 50% conversion with only milliwatt pump, marking the highest
by far among all nanophotonic platforms with milliwatt pumping. Our
demonstration addresses a long-outstanding challenge facing cavity-based
optical processing, including frequency conversion, frequency comb generation,
and all-optical switching, whose stable performance is hindered by
photorefractive or thermal effects. Our results further establish TFLN as an
excellent material capable of optical multitasking, as desirable to build
multi-functional chip devices.


  Smart cities have revolutionized urban living by incorporating sophisticated
technologies to optimize various aspects of urban infrastructure, such as
transportation systems. Effective traffic management is a crucial component of
smart cities, as it has a direct impact on the quality of life of residents and
tourists. Utilizing deep radial basis function (RBF) networks, this paper
describes a novel strategy for enhancing traffic intelligence in smart cities.
Traditional methods of traffic analysis frequently rely on simplistic models
that are incapable of capturing the intricate patterns and dynamics of urban
traffic systems. Deep learning techniques, such as deep RBF networks, have the
potential to extract valuable insights from traffic data and enable more
precise predictions and decisions. In this paper, we propose an RBF based
method for enhancing smart city traffic intelligence. Deep RBF networks combine
the adaptability and generalization capabilities of deep learning with the
discriminative capability of radial basis functions. The proposed method can
effectively learn intricate relationships and nonlinear patterns in traffic
data by leveraging the hierarchical structure of deep neural networks. The deep
RBF model can learn to predict traffic conditions, identify congestion
patterns, and make informed recommendations for optimizing traffic management
strategies by incorporating these rich and diverse data To evaluate the
efficacy of our proposed method, extensive experiments and comparisons with
real world traffic datasets from a smart city environment were conducted. In
terms of prediction accuracy and efficiency, the results demonstrate that the
deep RBF based approach outperforms conventional traffic analysis methods.
Smart city traffic intelligence is enhanced by the model capacity to capture
nonlinear relationships and manage large scale data sets.


  Dexterous robotic manipulation remains a challenging domain due to its strict
demands for precision and robustness on both hardware and software. While
dexterous robotic hands have demonstrated remarkable capabilities in complex
tasks, efficiently learning adaptive control policies for hands still presents
a significant hurdle given the high dimensionalities of hands and tasks. To
bridge this gap, we propose Tilde, an imitation learning-based in-hand
manipulation system on a dexterous DeltaHand. It leverages 1) a low-cost,
configurable, simple-to-control, soft dexterous robotic hand, DeltaHand, 2) a
user-friendly, precise, real-time teleoperation interface, TeleHand, and 3) an
efficient and generalizable imitation learning approach with diffusion
policies. Our proposed TeleHand has a kinematic twin design to the DeltaHand
that enables precise one-to-one joint control of the DeltaHand during
teleoperation. This facilitates efficient high-quality data collection of human
demonstrations in the real world. To evaluate the effectiveness of our system,
we demonstrate the fully autonomous closed-loop deployment of diffusion
policies learned from demonstrations across seven dexterous manipulation tasks
with an average 90% success rate.


  The momentum distribution of Lambda^0 hyperons produced from the quark-gluon
plasma (QGP) in ultra-relativistic heavy-ion collisions is calculated in
dependence on their polarization. The momentum distribution of Lambda^0
hyperons is defined by matrix elements of relativistic quark Wigner operators,
which are calculated within the Effective quark model with chiral U(3)xU(3)
symmetry and the Quark-Gluon transport theory. We show that the polarization of
the Lambda^0 hyperon depends of the spin of the strange quark that agrees well
with the DeGrand-Miettinen model. We show that Lambda^0 hyperons, produced from
the QGP, are fully unpolarized. This means that a detection of unpolarized
Lambda^0 hyperons, produced in ultra-relativistic heavy-ion collisions, should
serve as one of the signatures for the existence of the QGP in intermediate
states of ultra-relativistic heavy-ion collisions.


  Electromagnetic and gravitational radiation do not propagate solely on the
null cone in a generic curved spacetime. They develop "tails," traveling at all
speeds equal to and less than unity. If sizeable, this off-the-null-cone effect
could mean objects at cosmological distances, such as supernovae, appear dimmer
than they really are. Their light curves may be distorted relative to their
flat spacetime counterparts. These in turn could affect how we infer the
properties and evolution of the universe or the objects it contains. Within the
gravitational context, the tail effect induces a self-force that causes a
compact object orbiting a massive black hole to deviate from an otherwise
geodesic path. This needs to be taken into account when modeling the
gravitational waves expected from such sources. Motivated by these
considerations, we develop perturbation theory for solving the massless scalar,
photon and graviton retarded Green's functions in perturbed spacetimes,
assuming these Green's functions are known in the background spacetime. In
particular, we elaborate on the theory in perturbed Minkowski spacetime in
significant detail; and apply our techniques to compute the retarded Green's
functions in the weak field limit of the Kerr spacetime to first order in the
black hole's mass and angular momentum. Our methods build on and generalizes
work appearing in the literature on this topic to date, and lays the foundation
for a thorough, first principles based, investigation of how light propagates
over cosmological distances, within a spatially flat inhomogeneous
Friedmann-Lema\^{i}tre-Robertson-Walker (FLRW) universe. This perturbative
scheme applied to the graviton Green's function, when pushed to higher orders,
may provide approximate analytic (or semi-analytic) results for the self-force
problem in the weak field limits of the Schwarzschild and Kerr black hole
geometries.


  We suggest the new feature of primordial gravitational waves sourced by the
axion-gauge couplings, whose forms are motivated by the dimensional reduction
of the form field in the string theory.
  In our inflationary model, as an inflaton we adopt two types of axion, dubbed
the model-independent axion and the model-dependent axion, which couple with
two gauge groups with different sign combination each other.
  Due to these forms both polarization modes of gauge fields are amplified and
enhance both helicies of tensor modes during inflation.
  We point out the possibility that a primordial blue-tilted tensor power
spectra with small chirality are provided by the combination of these
axion-gauge couplings, intriguingly both amplitudes and chirality are
potentially testable by future space-based gravitational wave interferometers
such as DECIGO and BBO project.


  We develop a Wigner function representation of the quantum transport theory
of the conduction band electrons in Rashba effect resonant tunneling structures
with a phonon bath. In narrow band gap heterostructures, spin splitting occurs
mainly as a result of inversion asymmetry in the spatial dependence of the
potential or as a result of external electric field. This "zero magnetic field
spin splitting" is due to the Rashba term in the effective mass Hamiltonian.
The quantum transport equations are derived using multi-band non-equilibrium
Green's function formulation in generalized Kadanoff-Baym ansatz.


  We present a survey for neutral atomic-carbon (CI) along gamma-ray burst
(GRB) sightlines, which probes the shielded neutral gas-phase in the
interstellar medium (ISM) of GRB host galaxies at high redshift. We compile a
sample of 29 medium- to high-resolution GRB optical afterglow spectra spanning
a redshift range through most of cosmic time from $1 < z < 6$. We find that
seven ($\approx 25\%$) of the GRBs entering our statistical sample have CI
detected in absorption. It is evident that there is a strong excess of cold gas
in GRB hosts compared to absorbers in quasar sightlines. We investigate the
dust properties of the GRB CI absorbers and find that the amount of neutral
carbon is positively correlated with the visual extinction, $A_V$, and the
strength of the 2175 \AA\ dust extinction feature, $A_{\mathrm{bump}}$. GRBs
with CI detected in absorption are all observed above a certain threshold of
$\log N$(HI)$/\mathrm{cm}^{-2}$ + [X/H] > 20.7 and a dust-phase iron column
density of $\log N$(Fe)$_{\mathrm{dust}}/\mathrm{cm}^{-2}$ > 16.2. In contrast
to the SED-derived dust properties, the strength of the CI absorption does not
correlate with the depletion-derived dust properties. This indicates that the
GRB CI absorbers trace dusty systems where the dust composition is dominated by
carbon-rich dust grains. The observed higher metal and dust column densities of
the GRB CI absorbers compared to H$_2$- and CI-bearing quasar absorbers is
mainly a consequence of how the two absorber populations are selected, but is
also required in the presence of intense UV radiation fields in actively
star-forming galaxies.


  I present a concise account concerning the emergence of a research field,
which deals with the thermal properties of graphene, covering the refinement of
understanding of phonon transport in two-dimensional material systems. The
practical application of graphene and few-layer graphene in thermal interface
materials are also discussed.


  This paper presents an adaptive transformer model named SegmATRon for
embodied image semantic segmentation. Its distinctive feature is the adaptation
of model weights during inference on several images using a hybrid
multicomponent loss function. We studied this model on datasets collected in
the photorealistic Habitat and the synthetic AI2-THOR Simulators. We showed
that obtaining additional images using the agent's actions in an indoor
environment can improve the quality of semantic segmentation. The code of the
proposed approach and datasets are publicly available at
https://github.com/wingrune/SegmATRon.


  We consider least-squares problems with quadratic regularization and propose
novel sketching-based iterative methods with an adaptive sketch size. The
sketch size can be as small as the effective dimension of the data matrix to
guarantee linear convergence. However, a major difficulty in choosing the
sketch size in terms of the effective dimension lies in the fact that the
latter is usually unknown in practice. Current sketching-based solvers for
regularized least-squares fall short on addressing this issue. Our main
contribution is to propose adaptive versions of standard sketching-based
iterative solvers, namely, the iterative Hessian sketch and the preconditioned
conjugate gradient method, that do not require a priori estimation of the
effective dimension. We propose an adaptive mechanism to control the sketch
size according to the progress made in each step of the iterative solver. If
enough progress is not made, the sketch size increases to improve the
convergence rate. We prove that the adaptive sketch size scales at most in
terms of the effective dimension, and that our adaptive methods are guaranteed
to converge linearly. Consequently, our adaptive methods improve the
state-of-the-art complexity for solving dense, ill-conditioned least-squares
problems. Importantly, we illustrate numerically on several synthetic and real
datasets that our method is extremely efficient and is often significantly
faster than standard least-squares solvers such as a direct factorization based
solver, the conjugate gradient method and its preconditioned variants.


  In this work we derive some general features of the redshift measured by
radially moving observers in the black hole background. Let observer 1 cross
the black hole horizon emitting of a photon while observer 2 crossing the same
horizon later receives it. We show that if (i) the horizon is the outer one
(event horizon) and (ii) it is nonextremal, received frequency is redshifted.
This generalizes previous recent results in literature. For the inner horizon
(like in the Reissner-Nordstr\"{o}m metric) the frequency is blueshifted. If
the horizon is extremal, the frequency does not change. We derive explicit
formulas describing the frequency shift in generalized Kruskal- and
Lemaitre-like coordinates.


  Motivated by the importance of optical microscopes to science and
engineering, scientists have pondered for centuries how to improve their
resolution and the existence of fundamental resolution limits. In recent years,
a new class of microscopes that overcome a long-held belief about the
resolution have revolutionized biological imaging. Termed "superresolution"
microscopy, these techniques work by accurately locating optical point sources
from far field. To investigate the fundamental localization limits, here I
derive quantum lower bounds on the error of locating point sources in free
space, taking full account of the quantum, nonparaxial, and vectoral nature of
photons. These bounds are valid for any measurement technique, as long as it
obeys quantum mechanics, and serve as general no-go theorems for the resolution
of microscopes. To arrive at analytic results, I focus mainly on the cases of
one and two classical monochromatic sources with an initial vacuum optical
state. For one source, a lower bound on the root-mean-square position
estimation error is on the order of $\lambda_0/\sqrt{N}$, where $\lambda_0$ is
the free-space wavelength and $N$ is the average number of radiated photons.
For two sources, owing to the statistical effect of nuisance parameters, the
error bound diverges when their radiated fields overlap significantly. The use
of squeezed light to enhance further the accuracy of locating one classical
point source and the localization limits for partially coherent sources and
single-photon sources are also discussed. The presented theory establishes a
rigorous quantum statiscal inference framework for the study of superresolution
microscopy and points to the possibility of using quantum techniques for true
resolution enhancement.


  Relaxor ferroelectrics exhibit a unique competition between long-range and
short-range interactions that can be tuned electrically which prioritizes these
materials in a broad range of electro-mechanical energy-conversion
technologies, including biomedical imaging and electric-charge generators.
Here, we demonstrate differential negative piezoresponse by utilizing the
short-range interactions in relaxor ferroelectrics. The effect was observed
over a broad temperature range with local piezoresponse spectroscopy in unpoled
samples, while no negative piezoresponse was observed when the material was
pre-scan poled. These measurements suggest that the effect, that is promising
for power-generation applications, originates from non-ergodic behavior.
Complementary macroscale impedance and dielectric constant measurements as a
function of temperature and frequency supported the mesoscopic findings.
Bearing in mind the direct relationship between piezoresponse and capacitance,
relaxor ferroelectrics appear as an excellent platform for the emerging
technology of low-power negative-capacitance transistors.


  Complex activities of daily living (ADLs) often consist of multiple
micro-activities. When performed sequentially, these micro-activities help the
user accomplish the broad macro-activity. Naturally, a deeper understanding of
these micro-activities can help develop more sophisticated human activity
recognition (HAR) models and add explainability to their inferred conclusions.
Previous research has attempted to achieve this by utilizing fine-grained
annotated data that provided the required supervision and rules for associating
the micro-activities to identify the macro-activity. However, this
``bottom-up'' approach is unrealistic as getting such high-quality,
fine-grained annotated sensor datasets is challenging, costly, and
time-consuming. Understanding this, in this paper, we develop AmicroN, which
adapts a ``top-down'' approach by exploiting coarse-grained annotated data to
expand the macro-activities into their constituent micro-activities without any
external supervision. In the backend, AmicroN uses \textit{unsupervised}
change-point detection to search for the micro-activity boundaries across a
complex ADL. Then, it applies a \textit{generalized zero-shot} approach to
characterize it. We evaluate AmicroN on two real-life publicly available
datasets and observe that AmicroN can identify the micro-activities with micro
F\textsubscript{1}-score $>0.75$ for both datasets. Additionally, we also
perform an initial proof-of-concept on leveraging the state-of-the-art (SOTA)
large language models (LLMs) with attribute embeddings predicted by AmicroN to
enhance further the explainability surrounding the detection of
micro-activities.


  The highly efficient photocatalytic water splitting to produce clean energy
requires novel semiconductor materials to achieve high solar-to-hydrogen energy
conversion efficiency. Herein, the photocatalytic properties of anisotropic
$\beta$-PtX$_2$ (X=S, Se) and Janus $\beta$-PtSSe monolayers are investigated
based on density functional theory. Small cleavage energy for \{beta}-PtS2
(0.44 J/m2) and $\beta$-PtSe$_2$ (0.40 J/m$^2$) endorses the possibility of
their mechanical exfoliation from respective layered bulk material. The
calculated results find \{beta}-PtX2 monolayers to have an appropriate bandgap
(~1.8-2.6 eV) enclosing the water redox potential, light absorption
coefficients (~104 cm$^{-1}$), and excitons binding energy (~0.5-0.7 eV), which
facilitates excellent visible-light driven photocatalytic performance.
Remarkably, an inherent structural anisotropy leads to the anisotropic and high
carrier mobility (up to ~5 x 10$^3$ cm$^2$ V$^{-1}$ S$^{-1}$) leading to fast
transport of photogenerated carriers. Notably, the small required external
potential to derive hydrogen evolution reaction and oxygen evolution reaction
processes with an excellent solar-to-hydrogen energy conversion efficiency of
$\beta$-PtSe$_2$ (~16%) and $\beta$-PtSSe (~18%) makes them promising
candidates for solar water splitting applications.


  We prove an improved spectral large sieve inequality for the family of
$SL_3(\mathbb{Z})$ Hecke-Maass cusp forms. The method of proof uses duality and
its structure reveals unexpected connections to Heath-Brown's large sieve for
cubic characters.


  The spin distribution of massive black holes (MBHs) contains rich information
on the MBH growth history. In this paper, we investigate the spin evolution of
MBHs by assuming that each MBH experiences two-phase accretion, with an initial
phase of coherent-accretion via either the standard thin disc or
super-Eddington disc, followed by a chaotic-accretion phase composed of many
episodes with different disc orientations. If the chaotic-phase is significant
to the growth of an MBH, the MBH spin quickly reaches the maximum value because
of the initial coherent-accretion, then changes to a quasi-equilibrium state
and fluctuates around a value mainly determined by the mean ratio of the disc
to the MBH mass ($M_{\bullet}$) in the chaotic-accretion episodes, and further
declines due to late chaotic-accretion if $M_\bullet \gtrsim (1-3) \times 10^8
M_\odot$. The turning point to this decline is determined by the equality of
the disc warp radius and disc size. By matching the currently available spin
measurements with mock samples generated from the two-phase model(s) on the
spin-mass plane, we find that MBHs must experience significant
chaotic-accretion phase with many episodes and the mass accreted in each
episode is roughly 1-2 percent of M_bh or less. MBHs with $M_{\bullet}\gtrsim
10^8 M_{\odot}$ appear to have intermediate-to-high spins ($\sim 0.5-1$), while
lighter MBHs have higher spins ($\gtrsim 0.8$). The best matches also infer
that (1) the radiative efficiencies ($\eta$) of those active MBHs appear to
slightly decrease with $M_{\bullet}$; however, the correlation between $\eta$
and $M_{\bullet}$, if any, is weak; (2) the mean radiative efficiency of active
MBHs is $<\eta> \sim 0.09-0.15$, consistent with the global constraints.


  Full-reference (FR) point cloud quality assessment (PCQA) has achieved
impressive progress in recent years. However, in many cases, obtaining the
reference point clouds is difficult, so no-reference (NR) metrics have become a
research hotspot. Few researches about NR-PCQA are carried out due to the lack
of a large-scale PCQA dataset. In this paper, we first build a large-scale PCQA
dataset named LS-PCQA, which includes 104 reference point clouds and more than
22,000 distorted samples. In the dataset, each reference point cloud is
augmented with 31 types of impairments (e.g., Gaussian noise, contrast
distortion, local missing, and compression loss) at 7 distortion levels.
Besides, each distorted point cloud is assigned with a pseudo quality score as
its substitute of Mean Opinion Score (MOS). Inspired by the hierarchical
perception system and considering the intrinsic attributes of point clouds, we
propose a NR metric ResSCNN based on sparse convolutional neural network (CNN)
to accurately estimate the subjective quality of point clouds. We conduct
several experiments to evaluate the performance of the proposed NR metric. The
results demonstrate that ResSCNN exhibits the state-of-the-art (SOTA)
performance among all the existing NR-PCQA metrics and even outperforms some FR
metrics. The dataset presented in this work will be made publicly accessible at
http://smt.sjtu.edu.cn. The source code for the proposed ResSCNN can be found
at https://github.com/lyp22/ResSCNN.


  In this paper, we have designed and investigated the performance of radial
GaAs/AlGaAs pin junction nanocone array solar cells by performing coupled
optoelectronic simulations to obtain the most optimal design configuration
based on its photovoltaic properties. Each model has been compared with its
GaAs shell counterparts for different levels of surface passivations. It has
been observed that the nanocones with the AlGaAs shell has a much better
performance compared to those having GaAs shell. AlGaAs shell acts as a strong
barrier restricting most of the photogeneration to the inner GaAs regions and
it also acts as a strong passivation layer, reducing the recombination losses
due to surface effects. Further, it is observed that the nanocones achieve
their highest photoconversion efficiency when they are sparsely packed, with a
constant i-shell thickness of 7-9 nm and have an angle of tilt of 5 degrees.
This enhanced performance is attributed to a more effective and extended
photogeneration throughout the nanowire length, a strong overlapping built-in
electric field, and lower recombination losses.


  We suggest the new experimental method to explore the properties of slow
strange mesons at normal nuclear matter density. We show that the $K^{+}$ and
$K^{-}$ mesons with extremely small momenta relative to the surrounding medium
rest frame can be produced in nucleus-nucleon collisions and their production
cross sections are experimentally measurable. The experiments on study of the
momentum dependence of meson-nuclear potentials are discussed.


  A comprehensive study of a reduced version of Lust's equations, the extended
magnetohydrodynamic (XMHD) model obtained from the two-fluid theory for
electrons and ions with the enforcement of quasineutrality, is given. Starting
from the Hamiltonian structure of the fully three-dimensional theory, a
Hamiltonian two-dimensional incompressible four-field model is derived. In this
way energy conservation along with four families of Casimir invariants are
naturally obtained. The construction facilitates various limits leading to the
Hamiltonian forms of Hall, inertial, and ideal MHD, with their conserved
energies and Casimir invariants. Basic linear theory of the four-field model is
treated, and the growth rate for collisionless reconnection is obtained.
Results from nonlinear simulations of collisionless tearing are presented and
interpreted using, in particular normal fields, a product of the Hamiltonian
theory that gives rise to simplified equations of motion.


  In recent years, microservice architecture has become a popular architectural
style in software engineering, with its natural support for DevOps and
continuous delivery, as well as its scalability and extensibility, which drive
industry practitioners to migrate to microservice architecture. However, there
are many challenges in adopting a microservice architecture, the most important
of which is how to properly decomposition a monolithic system into
microservices. Currently, microservice decomposition decisions for monolithic
systems rely on subjective human experience, which is a costly, time-consuming
process with high uncertainty of results. To address this problem, this paper
proposes a method for microservice decomposition using Jackson Problem Frames.
In this method, requirements of the system are analysed, descriptions of the
interactions between the proposed software and its environment is obtained,
multiple problem diagrams are constructed, and then the problem diagrams are
merged by analyzing the correlation and similarity between them, resulting in a
microservice decomposition scheme. A case study is also conducted based on a
smart parking system. The results of the study show that the method can perform
microservice decomposition based on requirements and the software environment,
resulting in reducing the decisionmaking burden of developers, with reasonable
decomposition results.


  We construct a variational ground-state wave function of weakly interacting
M-component Bose-Einstein condensates beyond the mean-field theory by
incorporating the dynamical 3/2-body processes, where one of the two colliding
particles drops into the condensate and vice versa. Our numerical results with
various masses and particle numbers show that the 3/2-body processes between
different particles make finite contributions to lowering the ground-state
energy, implying that many-body correlation effects between different particles
are essential even in the weak-coupling regime of the Bose--Einstein
condensates. We also consider the stability condition for $2$-component
miscible states using the new ground-state wave function. Through this
calculation, we obtain the relation $U^{2}_{AB}/U_{AA}U_{BB}<1+\alpha$, where
$U_{ij}$ is the effective contact potential between particles $i$ and $j$ and
$\alpha$ is the correction, which originates from the $3/2$-body and $2$-body
processes.


  This study estimated the planning quality of intensity-modulated radiotherapy
in 42 lung cancer cases to provide preliminary data for the development of a
planning quality assurance algorithm. Organs in or near the thoracic cavity
(ipsilateral lung, contralateral lung, heart, liver, esophagus, spinal cord,
and bronchus) were selected as organs at risk (OARs). Radiotherapy plans were
compared using the conformity index (CI), coverage index (CVI), and homogeneity
index (HI) of the planning target volume (PTV), OAR-PTV distance and OAR-PTV
overlap volume, and the V10Gy, V20Gy, and equivalent uniform dose (EUD) of the
OARs. The CI, CVI, and HI of the PTV were 0.54 - 0.89 , 0.90 - 1.00 , and 0.11
- 0.41, respectively. The mean EUDs (V10Gy, V20Gy) of the ipsilateral lung,
contralateral lung, esophagus, cord, liver, heart, and bronchus were 8.07 Gy
(28.06, 13.17), 2.59 Gy (6.53, 1.18), 7.02 Gy (26.17, 12.32), 3.56 Gy (13.56,
4.48), 0.72 Gy (2.15, 0.91), 5.14 Gy (19.68, 8.62), and 10.56 Gy (36.08,
19.79), respectively. EUDs tended to decrease as OAR-PTV distance increased and
OAR-PTV overlap volume decreased. Because the plans in this study were from a
single department, relatively few people were involved in treatment planning.
Differences in treatment results for a given patient would be much more
pronounced if many departments were involved.


  PHENIX measures leptons at mid and forward rapidities and extracts leptons
resulting from semi-leptonic decays of heavy quarks. We present PHENIX results
related to heavy quark production, specifically the invariant cross section of
the non-photonic single electrons produced at midrapidity in p+p and d+Au
collisions at sqrt(sNN) = 200 GeV. The measured cross section for {\it p+p}
collisions is compared with the NLO prediction, and a possible excess over the
prediction is noted. The measured cross section for {\it d+Au} collisions
scales with the number of colliding nucleon pairs from the {\it p+p} spectra.


  We present evolutionary calculations for very-low-mass stars and brown dwarfs
based on synthetic spectra and non-grey atmosphere models which include dust
formation and opacity, i.e. objects with $\te\simle 2800$ K. The interior of
the most massive brown dwarfs is shown to develop a conductive core after $\sim
2$ Gyr which slows down their cooling. Comparison is made in optical and
infrared color-magnitude diagrams with recent late-M and L-dwarf observations.
The saturation in optical colors and the very red near-infrared colors of these
objects are well explained by the onset of dust formation in the atmosphere.
Comparison of the faintest presently observed L-dwarfs with these dusty
evolutionary models suggests that dynamical processes such as turbulent
diffusion and gravitational settling are taking place near the photosphere. As
the effective temperature decreases below $\te\approx 1300-1400$ K, the colors
of these objects move to very blue near-infrared colors, a consequence of the
ongoing methane absorption in the infrared. We suggest the possibility ofa
brown dwarf dearth in $J,H,K$ color-magnitude diagrams around this temperature.


  We develop a notion of nonlinear expectation --G-expectation-- generated by a
nonlinear heat equation with infinitesimal generator G. We first study
multi-dimensional G-normal distributions. With this nonlinear distribution we
can introduce our G-expectation under which the canonical process is a multi
dimensional G-Brownian motion. We then establish the related stochastic
calculus, especially stochastic integrals of Ito's type with respect to our
G-Brownian motion and derive the related Ito's formula. We have also obtained
the existence and uniqueness of stochastic differential equation under our
G-expectation.


  Sets of orthogonal basis functions over two-dimensional circular areas--most
often representing pupils in optical applications--are known in the literature
for the full circle (Zernike or Jacobi polynomials) and the annulus. This work
proposes an orthogonal set if the area is two non-overlapping circular pupils
of same size. The major free parameter is the ratio of the pupil radii over the
distance between both circles. Increasingly higher order aberrations--as
defined for a virtual larger pupil in which both pupils are embedded--are fed
into a Gram-Schmidt orthogonalization to implement one unique set of basis
functions. The key element is to work out the overlap integrals between a full
set of primitive basis functions (products of powers of the distance from the
mid-point between both pupils by azimuthal functions of the Fourier type).


  In this paper, we generalize the Nguyen-Spradlin-Volovich-Wen (NSVW) tree
formula from the MHV sector to any helicity sector. We find a close connection
between the Permutohedron and the KLT relation, and construct a non-trivial
mapping between them, linking the amplitudes in the gauge and gravity theories.
The gravity amplitude can also be mapped from a determinant followed from the
matrix-tree theorem. Besides, we use the binary tree graphs to manifest its Lie
structure. In our tree formula, there is an evident Hopf algebra of the
permutation group behind the gravity amplitudes. Using the tree formula, we can
directly re-derive the soft/collinear limit of the amplitudes.


  The influence of the Sustainable Development Goals (SDGs) has been widely
spread over the last years, establishing new public and privat policies.
Education has also been experiencing this change by aligning with the previous
goals. In this chapter, we briefly summarize the main activities conducted
under the Grant APS22.2003 'Service-based learning of the SDGs related to a
responsible production and consumption (A-BASE-DE-PROS)', which uses the SDG 12
as a guide line to raise the awareness of the importance of the 2030 Agenda
among undergraduate and secondary-school students. In general, the
service-based learning has increased the knowledge of the SDGs among the
students. Furthermore, most of the (university and secondary) students found
the service-learning


  Graph Neural Network (GNN) inference is used in many real-world applications.
Data sparsity in GNN inference, including sparsity in the input graph and the
GNN model, offer opportunities to further speed up inference. Also, many
pruning techniques have been proposed for model compression that increase the
data sparsity of GNNs. We propose Dynasparse, a comprehensive hardware-software
codesign on FPGA to accelerate GNN inference through dynamic sparsity
exploitation. For this, we decouple the GNN computation kernels from the basic
computation primitives, and explore hardware-software codesign as follows: 1)
Hardware design: We propose a novel unified accelerator design on FPGA to
efficiently execute various computation primitives. We develop a customized
soft processor that is tightly coupled with the accelerator to execute a
runtime system. Moreover, we develop efficient hardware mechanisms to profile
the data sparsity and perform on-the-fly data format transformation to prepare
the input data for various computation primitives; 2) Software design: We
develop a runtime system that works synergistically with the accelerator to
perform dynamic kernel-to-primitive mapping based on data sparsity. We
implement Dynasparse on a state-of-the-art FPGA platform, Xilinx Alveo U250,
and evaluate the design using widely used GNN models (GCN, GraphSAGE, GIN and
SGC). For the above GNN models and various input graphs, the proposed
accelerator and dynamic kernel-to-primitive mapping reduces the inference
latency by $3.73\times$ on the average compared with the static mapping
strategies employed in the state-of-the-art GNN accelerators. Compared with
state-of-the-art CPU (GPU) implementations, Dynasparse achieves up to
$56.9\times$ ($2.37\times$) speedup in end-to-end latency.


  Graph neural networks (GNNs) have been widely used in many graph-based tasks
such as node classification, link prediction, and node clustering. However,
GNNs gain their performance benefits mainly from performing the feature
propagation and smoothing across the edges of the graph, thus requiring
sufficient connectivity and label information for effective propagation.
Unfortunately, many real-world networks are sparse in terms of both edges and
labels, leading to sub-optimal performance of GNNs. Recent interest in this
sparse problem has focused on the self-training approach, which expands
supervised signals with pseudo labels. Nevertheless, the self-training approach
inherently cannot realize the full potential of refining the learning
performance on sparse graphs due to the unsatisfactory quality and quantity of
pseudo labels.
  In this paper, we propose ROD, a novel reception-aware online knowledge
distillation approach for sparse graph learning. We design three supervision
signals for ROD: multi-scale reception-aware graph knowledge, task-based
supervision, and rich distilled knowledge, allowing online knowledge transfer
in a peer-teaching manner. To extract knowledge concealed in the multi-scale
reception fields, ROD explicitly requires individual student models to preserve
different levels of locality information. For a given task, each student would
predict based on its reception-scale knowledge, while simultaneously a strong
teacher is established on-the-fly by combining multi-scale knowledge. Our
approach has been extensively evaluated on 9 datasets and a variety of
graph-based tasks, including node classification, link prediction, and node
clustering. The result demonstrates that ROD achieves state-of-art performance
and is more robust for the graph sparsity.


  A radio antenna is primarily designed to convert electromagnetic waves into
electrical current and vice versa. However, a part of the incident wavefield is
scattered due to structural effects and reflected power at the antenna's
electrical port. Because the latter depends on the load impedance, an antenna
can also be referred to as a loaded scatterer. Its interaction with
electromagnetic waves is defined by means of absorption and scattering
cross-sections (ACS and SCS). When immersed in a diffuse field such as the one
generated within a reverberation chamber (RC), the impact of the load antenna
results from averaged properties over incident angles. One fundamental quantity
is the antenna quality factor (Q-factor) directly related to the averaged ACS.
Current formulations of Q-factor are based on different power budget analysis
which do not enable the consideration of wave interferences between the ingoing
and outgoing fields. Additionally, the structural component is always neglected
in the current formulations. In this paper, we introduce a rigorous formulation
of the antenna Q-factor which takes into account the aforementioned effects.
The antenna is modeled using the scattering-matrix theory which linearly links
the ingoing and outgoing waves in terms of spherical harmonics expansion. The
derived theory is validated using several numerical simulations based on a
Method-of-Moment code. Then, the capability to take advantage of this model to
retrieve antenna properties from multiple Q-factor estimations in an RC is
demonstrated. All results are compared to the existing Q-factor formulations.


  Data depth is a powerful nonparametric tool originally proposed to rank
multivariate data from center outward. In this context, one of the most
archetypical depth notions is Tukey's halfspace depth. In the last few decades
notions of depth have also been proposed for functional data. However, Tukey's
depth cannot be extended to handle functional data because of its degeneracy.
Here, we propose a new halfspace depth for functional data which avoids
degeneracy by regularization. The halfspace projection directions are
constrained to have a small reproducing kernel Hilbert space norm. Desirable
theoretical properties of the proposed depth, such as isometry invariance,
maximality at center, monotonicity relative to a deepest point, upper
semi-continuity, and consistency are established. Moreover, the regularized
halfspace depth can rank functional data with varying emphasis in shape or
magnitude, depending on the regularization. A new outlier detection approach is
also proposed, which is capable of detecting both shape and magnitude outliers.
It is applicable to trajectories in $L^2$, a very general space of functions
that include non-smooth trajectories. Based on extensive numerical studies, our
methods are shown to perform well in terms of detecting outliers of different
types. Three real data examples showcase the proposed depth notion.


  Motivated by the question of existence of global solutions, we obtain
pointwise upper bounds for radially symmetric and monotone solutions to the
homogeneous Landau equation with Coulomb potential. The estimates say that blow
up in the $L^\infty$-norm at a finite time $T$ can occur only if the
$L^{3/2}$-norm of the solution concentrates for times close to $T$. The bounds
are obtained using the comparison principle for the Landau equation and for the
associated mass function.
  This method provides long-time existence results for the isotropic version of
the Landau equation with Coulomb potential, recently introduced by Krieger and
Strain.


  We study cosmological aspects of braneworld models with a warped dimension
and an arbitrary number of compact dimensions. With a stabilized radion, a
number of different cosmological bulk solutions are found in a general case.
Both one and two brane models are considered. The Friedmann equation is
calculated in each case. Particular attention is paid to six dimensional models
where we find that the usual Friedmann equation can typically be recovered
without fine-tuning.


  Based on the Newman-Janis algorithm the Ayon-Beato-Garcia spacetime metric of
the regular spherically symmetric, static and charged black hole has been
converted into rotational form. It is shown that the derived solution for
rotating regular black hole is regular and the critical value of the electric
charge $Q$ for which two horizons merge into one sufficiently decreases in the
presence of nonvanishing angular momentum $a$ of the black hole.


  Elaborating on a paper by Suter, we provide a detailed description of the
automorphism group of the poset of abelian ideals in a Borel subalgebra of a
finite dimensional complex simple Lie algebra.


  Environmental, Social, and Governance (ESG) has been used as a metric to
measure the negative impacts and enhance positive outcomes of companies in
areas such as the environment, society, and governance. Recently, investors
have increasingly recognized the significance of ESG criteria in their
investment choices, leading businesses to integrate ESG principles into their
operations and strategies. The Multi-Lingual ESG Issue Identification (ML-ESG)
shared task encompasses the classification of news documents into 35 distinct
ESG issue labels. In this study, we explored multiple strategies harnessing
BERT language models to achieve accurate classification of news documents
across these labels. Our analysis revealed that the RoBERTa classifier emerged
as one of the most successful approaches, securing the second-place position
for the English test dataset, and sharing the fifth-place position for the
French test dataset. Furthermore, our SVM-based binary model tailored for the
Chinese language exhibited exceptional performance, earning the second-place
rank on the test dataset.


  The application of high-resolution spectropolarimetry has led to major
progress in understanding the magnetism and activity of late-type stars. During
the last decade, magnetic fields have been discovered and mapped for many types
of active cool stars using spectropolarimetric data. However, these
observations and modeling attempts are fundamentally incomplete since they are
based on the interpretation of the circular polarization alone. Taking
advantage of the newly built HARPS polarimeter, we have obtained the first
systematic observations of several cool active stars in all four Stokes
parameters. Here we report the detection of magnetically-induced linear
polarization for the primary component of the very active RS CVn binary HR 1099
and for the moderately active K dwarf epsilon Eri. For both stars the amplitude
of linear polarization signatures is measured to be ~10^{-4} of the unpolarized
continuum, which is approximately a factor of ten lower than for circular
polarization. This is the first detection of the linear polarization in line
profiles of cool active stars. Our observations of the inactive solar-like star
alpha Cen A show neither circular nor linear polarization above the level of
10^{-5}, indicating the absence of a net longitudinal magnetic field stronger
than 0.2 G.


  Optimization of Mixed-Integer Non-Linear Programming (MINLP) supports
important decisions in applications such as Chemical Process Engineering. But
current solvers have limited ability for deductive reasoning or the use of
domain-specific theories, and the management of integrality constraints does
not yet exploit automated reasoning tools such as SMT solvers. This seems to
limit both scalability and reach of such tools in practice. We therefore
present a tool, ManyOpt, for MINLP optimization that enables experimentation
with reduction techniques which transform a MINLP problem to feasibility
checking realized by an SMT solver. ManyOpt is similar to the SAT solver
ManySAT in that it runs a specified number of such reduction techniques in
parallel to get the strongest result on a given MINLP problem. The tool is
implemented in layers, which we may see as features and where reduction
techniques are feature vectors. Some of these features are inspired by known
MINLP techniques whereas others are novel and specific to SMT. Our experimental
results on standard benchmarks demonstrate the benefits of this approach. The
tool supports a variety of SMT solvers and is easily extensible with new
features, courtesy of its layered structure. For example, logical formulas for
deductive reasoning are easily added to constrain further the optimization of a
MINLP problem of interest.


  We introduce the strong CP-violation in the framework of AdS/QCD model and
calculate the electric dipole moments of nucleons as well as the CP-violating
pion-nucleon coupling. Our holographic estimate of the electric dipole moments
gives for the neutron d_n=1.08 X 10^{-16} theta (e cm), which is comparable
with previous estimates. We also predict that the electric dipole moment of the
proton should be precisely the minus of the neutron electric dipole moment,
thus leading to a new sum rule on the electric dipole moments of baryons.


  We investigate the electronic structure of Nickel sulphide (NiS) in the
millerite phase using electron spectroscopic measurements and band structure as
well as model Hamiltonian calculations. While band structure calculations are
found to be relatively more successful in describing the experimental valence
band spectrum of this highly conducting phase compared to the hexagonal phase
of NiS, cluster calculations including electron correlation effects are found
to be necessary for the description of certain features in the experimental
spectra, indicating importance of correlation effects even in a highly metallic
system. The electronic parameter strengths obtained from these calculations
confirm that the millerite NiS is a highly covalent pd-metal. The comparative
study of hexagonal and millerite forms of NiS, provides the information
concerning the evolution of the spectral function in a pd-metal as a function
of covalency.


  A study of top quark production at the future International Linear Collider,
ILC, with a centre-of-mass energy of 500 GeV is presented. The emphasis is put
on determining the sensitivity to physics beyond the Standard Model. The
analysis has been carried out with a full simulation of the ILD detector. Both,
the forward-backward asymmetry and the left-right asymmetry can be determined
to a precision of about 1% to 1.5%. The analysis points out an ambiguity which
arises in case of the production of top-quarks with left-handed helicity.


  The one-loop effects of vacuum polarization induced by untwisted fermions in
QED in a nonsimply connected space-time with topology $S^{1}\times R^{3}$ are
investigated. It is found that photon propagation in this system is
anisotropic, appearing several massive photon modes and a superluminal
transverse mode. For small compactification radius $a$, the superluminal
velocity increases logarithmically with $a$. At low energies the photon masses
lead to an effective confinement of the gauge fields into a (2+1)-dimensional
manifold transverse to the compactified direction. The system shows a
topologically induced directional superconductivity.


  White Dwarfs (WDs) are the final evolutionary product of the vast majority of
stars in the Universe. They are electron-degenerate structures characterized by
no stable thermonuclear activity, and their evolution is generally described as
a pure cooling process. Their cooling rate is adopted as cosmic chronometer to
constrain the age of several Galactic populations, including the disk, globular
and open clusters. By analysing high-resolution photometric data of two twin
Galactic globular clusters (M3 and M13), we find a clear-cut and unexpected
over-abundance of bright WDs in M13. Theoretical models suggest that,
consistently with the horizontal branch morphology, this over-abundance is due
to a slowing down of the cooling process in ~70% of the WDs in M13, caused by
stable thermonuclear burning in their residual hydrogen-rich envelope. This is
the first observational evidence of quiescent thermonuclear activity occurring
in cooling WDs and it brings new attention on the use of the WD cooling rate as
cosmic chronometer for low metallicity environments.


  The Quantum Hall Effect for free electrons in external periodic field is
discussed without using the linear response approximation. We find that the
Hall conductivity is related in a simple way to Floquet energies (associated to
the Schroedinger equation in the co-moving frame). By this relation one can
analyze the dependence of the Hall conductivity from the electric field.
Sub-bands can be introduced by the time average of the expectation value of the
Hamiltonian on the Floquet states. Moreover we prove previous results in form
of sum rules as, for instance: the topological character of the Hall
conductivity (being an integer multiple of e^2/h), the Diofantine equation
which constrains the Hall conductivity by the rational number which measures
the flux of the magnetic field through the periodicity cell. The Schroedinger
equation fixes in a natural way the phase of the wave function over the reduced
Brillouin zone: thus the topological invariant providing the Hall conductivity
can be evaluated numerically without ambiguity.


  We derive two-loop anomalous dimensions for four-Fermi operators in
supersymmetric theories using the effective Kahler potential. We introduce the
general forms in generic gauge theories and apply our results to the
flavor-changing operators in (minimal) supersymmetric standard models.


  We analyze the properties of a single impurity immersed in a Fermi sea. At
positive energy and scattering lengths, we show that the system possesses a
well-defined but metastable excitation, the repulsive polaron, and we calculate
its energy, quasiparticle residue and effective mass. From a thermodynamic
argument we obtain the number of particles in the dressing cloud, illustrating
the repulsive character of the polaron. Identifying the important 2- and 3-body
decay channels, we furthermore calculate the lifetime of the repulsive polaron.
The stability conditions for the formation of fully spin polarized
(ferromagnetic) domains are then examined for a binary mixture of atoms with a
general mass ratio. Our results indicate that mass imbalance lowers the
critical interaction strength for phase-separation, but that very short
quasiparticle decay times will complicate the experimental observation of
itinerant ferromagnetism. Finally, we present the spectral function of the
impurity for various coupling strengths and momenta.


  Linear combinations $D_K$ of the complete polarization-transfer observables,
Dij, in the (p,p') reaction at intermediate energies are demonstrated. A
comparison between systematized measured and calculated values of the
combinations $D_K$ for the $1^+$ (T = 0 and T = 1) levels in $^{12}$C, for the
$4^-$ (T = 0 and T = 1) states in $^{16}$O, and for the $6^-$ (T = 0 and T = 1)
levels in $^{28}$Si are reported. Particularities in angular distributions of
transverse- and longitudinal-spin-transfer probabilities, $D_K$, for the T = 0
and T = 1 unnatural-parity states in the indicated nuclei are discussed. The
spin-observable combinations Dls allowed to differentiate reliably the strength
of the isoscalar and isovector spin-orbit interactions. The comparison of
experimental $D_K$ and calculated $D_K$ with the use of zero-range treatment
(LEA code) and exact finite-range calculations (DWBA-91 program) made it
possible to identify the role of exchange contributions.


  Some clusters of galaxies in addition to thermal bremsstrahlung (TB), emit
diffuse radiation from the intercluster medium (ICM) at radio, EUV and hard
x-ray (HXR) ranges. The radio radiation is due to synchrotron by relativistic
electrons, and the inverse Compton (IC) scattering by the cosmic microwave
background radiation of the same electrons is the most natural source for the
HXR and perhaps the EUV emissions. However, simple estimates give a weaker
magnetic field than that suggested by Faraday rotation measurements.
Consequently, non-thermal bremsstrahlung (NTB) and TB have also been suggested
as sources of these emissions. We show that NTB cannot be the source of the
HXRs and that the difficulty with the low magnetic field in the IC model is
alleviated if we take into account the effects of observational bias,
nonisotropic pitch angle distribution and spectral breaks. We derive a spectrum
for the radiating electrons and discuss acceleration scenarios. We show that
continuous and in situ acceleration in the ICM of the background thermal
electrons requires unreasonably high energy input and acceleration of injected
relativistic electrons gives rise to a much flatter spectrum than desired,
unless a large fraction of electrons escape the ICM, in which case one obtains
EUV and HXR emissions extending well beyond the boundaries of the cluster. A
continuous emission by a cooling spectrum resulting from interaction with ICM
of electrons accelerated elsewhere also suffers from similar shortcomings. The
most likely scenario appears to be an episodic injection-acceleration model,
whereby one obtains a time dependent spectrum that for certain phases of its
evolution satisfies all the requirements.


  The affine ring A of the affine Jacobian variety of a hyperelliptic curve of
genus 3 is studied as a D-module. The conjecture on the minimal D-free
resolution previously proposed is proved in this case. As a by-product a linear
basis of A is explicitly constructed in terms of derivatives of Klein's
hyperelliptic pe functions.


  We present an improvement of the MC event generator Herwiri2, where we recall
the latter MC was a prototype for the inclusion of CEEX resummed EW corrections
in hadron-hadron scattering at high cms energies. In this improvement the new
exact ${\cal O}(\alpha^2L)$ resummed EW generator ${\cal{KK}}$ MC 4.22,
featuring as it does the CEEX realization of resummation in the EW sector, is
put in union with the Herwig parton shower environment. The {\rm LHE} format of
the attendant output event file means that all other conventional parton shower
environments are available to the would-be user of the resulting new MC. For
this reason (and others -- see the text) we henceforth refer to the new
improvement of the Herwiri2 MC as ${\cal{KK}}\text{MC-hh}$. Since this new MC
features exact ${\cal O}(\alpha)$ pure weak corrections from the DIZET EW
library and features the CEEX and the EEX YFS-style resummation of large
multiple photon effects, it provides already the concrete path to 0.05\%
precision on such effects if we focus on the EW effects themselves. We
therefore show predictions for observable distributions and comparisons with
other approaches in the literature. This MC represents an important step in the
realization of the exact amplitude-based $QED\otimes QCD$ resummation paradigm.
Independently of this latter observation, the MC rigorously quantifies
important EW effects in the current LHC experiments.


  Large Language Models (LLMs) have significantly transformed the educational
landscape, offering new tools for students, instructors, and teaching
assistants. This paper investigates the application of LLMs in assisting
teaching assistants (TAs) with viva and code assessments in an advanced
computing class on distributed systems in an Indian University. We develop
TAMIGO, an LLM-based system for TAs to evaluate programming assignments.
  For viva assessment, the TAs generated questions using TAMIGO and circulated
these questions to the students for answering. The TAs then used TAMIGO to
generate feedback on student answers. For code assessment, the TAs selected
specific code blocks from student code submissions and fed it to TAMIGO to
generate feedback for these code blocks. The TAMIGO-generated feedback for
student answers and code blocks was used by the TAs for further evaluation.
  We evaluate the quality of LLM-generated viva questions, model answers,
feedback on viva answers, and feedback on student code submissions. Our results
indicate that LLMs are highly effective at generating viva questions when
provided with sufficient context and background information. However, the
results for LLM-generated feedback on viva answers were mixed; instances of
hallucination occasionally reduced the accuracy of feedback. Despite this, the
feedback was consistent, constructive, comprehensive, balanced, and did not
overwhelm the TAs. Similarly, for code submissions, the LLM-generated feedback
was constructive, comprehensive and balanced, though there was room for
improvement in aligning the feedback with the instructor-provided rubric for
code evaluation. Our findings contribute to understanding the benefits and
limitations of integrating LLMs into educational settings.


  Sparse Identification of Nonlinear Dynamics (SINDy) is a method of system
discovery that has been shown to successfully recover governing dynamical
systems from data (Brunton et al., PNAS, '16; Rudy et al., Sci. Adv. '17).
Recently, several groups have independently discovered that the weak
formulation provides orders of magnitude better robustness to noise. Here we
extend our Weak SINDy (WSINDy) framework introduced in (arXiv:2005.04339) to
the setting of partial differential equations (PDEs). The elimination of
pointwise derivative approximations via the weak form enables effective
machine-precision recovery of model coefficients from noise-free data (i.e.
below the tolerance of the simulation scheme) as well as robust identification
of PDEs in the large noise regime (with signal-to-noise ratio approaching one
in many well-known cases). This is accomplished by discretizing a convolutional
weak form of the PDE and exploiting separability of test functions for
efficient model identification using the Fast Fourier Transform. The resulting
WSINDy algorithm for PDEs has a worst-case computational complexity of
$\mathcal{O}(N^{D+1}\log(N))$ for datasets with $N$ points in each of $D+1$
dimensions (i.e. $\mathcal{O}(\log(N))$ operations per datapoint). Furthermore,
our Fourier-based implementation reveals a connection between robustness to
noise and the spectra of test functions, which we utilize in an \textit{a
priori} selection algorithm for test functions. Finally, we introduce a
learning algorithm for the threshold in sequential-thresholding least-squares
(STLS) that enables model identification from large libraries, and we utilize
scale-invariance at the continuum level to identify PDEs from poorly-scaled
datasets. We demonstrate WSINDy's robustness, speed and accuracy on several
challenging PDEs.


  Ground-state properties of a few attractively interacting ultra-cold atoms of
different mass confined in a one-dimensional harmonic trap are studied in terms
of the correlation noise. Depending on the mass ratio between the components'
atoms, the inter-particle correlations change their properties significantly
from a strong pair-like correlation to an almost uncorrelated phase. This
change is accompanied by the undergoing change in the structure of the
many-body ground state. A crucial role of the quantum statistics is emphasized
by comparing properties of the Fermi-Fermi mixture with a corresponding
Fermi-Bose system.


  Gathering data through measurements is at the basis of every experimental
science. Ideally, measurements should be repeatable and, when extracting only
coarse-grained data, they should allow the experimenter to retrieve the finer
details at a later time. However, in practice most measurements appear to be
noisy. Here we postulate that, despite the imperfections observed in real life
experiments, there exists a fundamental level where all measurements are ideal.
Combined with the requirement that ideal measurements remain so when
coarse-grained or applied in parallel on spacelike separated systems, our
postulate places a powerful constraint on the amount of nonlocality and
contextuality that can be found in an arbitrary physical theory, bringing down
the violation of Bell and Kocher-Specker inequalities near to its quantum
value. In addition, it provides a new compelling motivation for the principles
of Local Orthogonality and Consistent Exclusivity, recently proposed for the
characterization of the quantum set of probability distributions.


  The Twelfth International Workshop on Non-Classical Models of Automata and
Applications (NCMA 2022) was held in Debrecen, Hungary, on August 26 and 27,
2022, organized by the University of Debrecen. The NCMA workshop series was
established in 2009 as an annual event for researchers working on non-classical
and classical models of automata, grammars or related devices. Such models are
investigated both as theoretical models and as formal models for applications
from different points of view.


  We estimate the relative contributions of the supermassive black hole (SMBH)
accretion disk, corona, and obscuring torus to the bolometric luminosity of
Seyfert galaxies, using Spizter mid-infrared (MIR) observations of a complete
sample of 68 nearby active galactic nuclei from the INTEGRAL all-sky hard X-ray
(HX) survey. This is the first HX-selected (above 15 keV) sample of AGNs with
complementary high angular resolution, high signal to noise, MIR data.
Correcting for the host galaxy contribution, we find a correlation between HX
and MIR luminosities: L_MIR L_HX^(0.74+/-0.06). Assuming that the observed MIR
emission is radiation from an accretion disk reprocessed in a surrounding dusty
torus that subtends a solid angle decreasing with increasing luminosity (as
inferred from the declining fraction of obscured AGNs), the intrinsic disk
luminosity, L_D, is approximately proportional to the luminosity of the corona
in the 2-300 keV energy band, L_C, with the L_D/L_C ratio varying by a factor
of 2.1 around a mean value of 1.6. This ratio is a factor of ~2 smaller than
for typical quasars producing the cosmic X-ray background (CXB). Therefore,
over three orders of magnitude in luminosity, HX radiation carries a large, and
roughly comparable, fraction of the bolometric output of AGNs. We estimate the
cumulative bolometric luminosity density of local AGNs at ~(1-3)x10^40
erg/s/Mpc^3. Finally, the Compton temperature ranges between kT_c~2 and ~6 keV
for nearby AGNs, compared to kT_c~2 keV for typical quasars, confirming that
radiative heating of interstellar gas can play an important role in regulating
SMBH growth.


  This paper continues the author's work \cite{PartI}, where a new framework of
the matter-induced physical geometry was built and an intrinsic nonlinearity of
the Dirac equation discovered. Here, the nonlinear Dirac equation is solved and
the localized configurations are found analytically. Of the two possible types
of the potentially stationary localized configurations of the Dirac field, only
one is stable with respect to the action of an external field and it
corresponds to a positive charge. A connection with the global charge asymmetry
of matter in the Universe and with the recently observed excess of the cosmic
positrons is discussed.


  Hessian recovery has been commonly used in mesh adaptation for obtaining the
required magnitude and direction information of the solution error.
Unfortunately, a recovered Hessian from a linear finite element approximation
is nonconvergent in general as the mesh is refined. It has been observed
numerically that adaptive meshes based on such a nonconvergent recovered
Hessian can nevertheless lead to an optimal error in the finite element
approximation. This also explains why Hessian recovery is still widely used
despite its nonconvergence. In this paper we develop an error bound for the
linear finite element solution of a general boundary value problem under a mild
assumption on the closeness of the recovered Hessian to the exact one.
Numerical results show that this closeness assumption is satisfied by the
recovered Hessian obtained with commonly used Hessian recovery methods.
Moreover, it is shown that the finite element error changes gradually with the
closeness of the recovered Hessian. This provides an explanation on how a
nonconvergent recovered Hessian works in mesh adaptation.


  The search for extrasolar Earth-like planets is underway. Over 100 extrasolar
giant planets are known to orbit nearby sun-like stars, including several in
multiple-planet systems. These planetary systems are stepping stones for the
search for Earth-like planets; the technology development, observational
strategies, and science results can all be applied to Earth-like planets. Stars
much less massive than the sun the most common stars in our Galaxy are being
monitored for the gravitational influence of Earth-like planets. Although
Earth-like planets orbiting sun-like stars are much more difficult to detect,
space missions are being built to detect them indirectly due to their effects
on the parent star and to quantify fundamental factors such as terrestrial
planet frequency, size distribution, and mass distribution. Extremely ambitious
space programs are being developed to directly detect Earth-like planets
orbiting sun-like stars, and must tackle the immense technological challenge of
blocking out the light of the parent star, which is brighter than the planet by
six to ten orders of magnitude. Direct detection of radiation from the planet
is necessary for the definitive goal of the search for Earth-like planets: the
study of atmospheric spectral signatures for signs of severe disequilibrium
chemistry that could be indicative of biological activity. In addition to
technological development, a growing flurry of scientific activity has begun
to: understand terrestrial planet formation and terrestrial planet frequency;
model terrestrial-like planet atmospheres and evolution; articulate the
biological signatures of our own Earth; and even to study Earth as an
extrasolar planet by observation and analysis of the spatially unresolved
Earth.


  Hyperbolic deep learning has become a growing research direction in computer
vision for the unique properties afforded by the alternate embedding space. The
negative curvature and exponentially growing distance metric provide a natural
framework for capturing hierarchical relationships between datapoints and
allowing for finer separability between their embeddings. However, these
methods are still computationally expensive and prone to instability,
especially when attempting to learn the negative curvature that best suits the
task and the data. Current Riemannian optimizers do not account for changes in
the manifold which greatly harms performance and forces lower learning rates to
minimize projection errors. Our paper focuses on curvature learning by
introducing an improved schema for popular learning algorithms and providing a
novel normalization approach to constrain embeddings within the variable
representative radius of the manifold. Additionally, we introduce a novel
formulation for Riemannian AdamW, and alternative hybrid encoder techniques and
foundational formulations for current convolutional hyperbolic operations,
greatly reducing the computational penalty of the hyperbolic embedding space.
Our approach demonstrates consistent performance improvements across both
direct classification and hierarchical metric learning tasks while allowing for
larger hyperbolic models.


  We present a new experiment on YBa_2Cu_3O_{7-x} (YBCO) thin films using
spatially resolved heavy ion irradiation. Structures consisting of a periodic
array of strong and weak pinning channels were created with the help of metal
masks. The channels formed an angle of +/-45 Deg with respect to the symmetry
axis of the photolithographically patterned structures. Investigations of the
anisotropic transport properties of these structures were performed. We found
striking resemblance to guided vortex motion as it was observed in YBCO single
crystals containing an array of unidirected twin boundaries. The use of two
additional test bridges allowed to determine in parallel the resistivities of
the irradiated and unirradiated parts as well as the respective current-voltage
characteristics. These measurements provided the input parameters for a
numerical simulation of the potential distribution of the Hall patterning. In
contrast to the unidirected twin boundaries in our experiment both strong and
weak pinning regions are spatially extended. The interfaces between
unirradiated and irradiated regions therefore form a Bose-glass contact. The
experimentally observed magnetic field dependence of the transverse voltage
vanishes faster than expected from the numerical simulation and we interpret
this as a hydrodynamical interaction between a Bose-glass phase and a vortex
liquid.


  SPARQL CONSTRUCT queries allow for the specification of data processing
pipelines that transform given input graphs into new output graphs. It is now
common to constrain graphs through SHACL shapes allowing users to understand
which data they can expect and which not. However, it becomes challenging to
understand what graph data can be expected at the end of a data processing
pipeline without knowing the particular input data: Shape constraints on the
input graph may affect the output graph, but may no longer apply literally, and
new shapes may be imposed by the query template. In this paper, we study the
derivation of shape constraints that hold on all possible output graphs of a
given SPARQL CONSTRUCT query. We assume that the SPARQL CONSTRUCT query is
fixed, e.g., being part of a program, whereas the input graphs adhere to input
shape constraints but may otherwise vary over time and, thus, are mostly
unknown. We study a fragment of SPARQL CONSTRUCT queries (SCCQ) and a fragment
of SHACL (Simple SHACL). We formally define the problem of deriving the most
restrictive set of Simple SHACL shapes that constrain the results from
evaluating a SCCQ over any input graph restricted by a given set of Simple
SHACL shapes. We propose and implement an algorithm that statically analyses
input SHACL shapes and CONSTRUCT queries and prove its soundness and
complexity.


  We discuss shallow resonances in the nonrelativistic scattering of two
particles using an effective field theory (EFT) that includes an auxiliary
field with the quantum numbers of the resonance. We construct the manifestly
renormalized scattering amplitude up to next-to-leading order in a systematic
expansion. For a narrow resonance, the amplitude is perturbative except in the
immediate vicinity of the resonance poles. It naturally has a zero in the
low-energy region, analogous to the Ramsauer-Townsend effect. For a broad
resonance, the leading-order amplitude is nonperturbative almost everywhere in
the regime of validity of the EFT. We regain the results of an EFT without the
auxiliary field, which is equivalent to the effective-range expansion with
large scattering length and effective range. We also consider an additional
fine tuning leading to a low-energy amplitude zero even for a broad resonance.
We show that in all cases the requirement of renormalizability when the
auxiliary field is not a ghost ensures the resonance poles are in the lower
half of the complex momentum plane, as expected by other arguments. The
systematic character of the EFT expansion is exemplified with a toy model
serving as underlying theory.


  The anomaly cancelation method proposed by Wilczek et al. is applied to the
general charged rotating black holes in five-dimensional minimal gauged
supergravity. Thus Hawking temperature and fluxes are found. The Hawking
temperature obtained agrees with the surface gravity formula. The black holes
have charge and two unequal angular momenta and these give rise to appropriate
terms in the effective U(1) gauge field of the reduced (1+1)-dimensional
theory. In particular, it is found that the terms in this U(1) gauge field
correspond exactly to the correct electrostatic potential and the two angular
velocities on the horizon of the black holes, and so the results for the
Hawking fluxes derived here from the anomaly cancelation method are in complete
agreement with the ones obtained from integrating the Planck distribution.


  We present a study of the physical properties of JO201, a unique disk galaxy
with extended tails undergoing extreme ram-pressure stripping as it moves
through the massive cluster Abell 85 at supersonic speeds mostly along the line
of sight. JO201 was observed with MUSE as part of the GASP programme. In a
previous paper (GASP II) we studied the stellar and gas kinematics. In this
paper we present emission-line ratios, gas-phase metallicities and ages of the
stellar populations across the galaxy disk and tails. We find that while the
emission at the core of the galaxy is dominated by an active galactic nucleus
(AGN), the disk is composed of star-forming knots surrounded by excited diffuse
gas. The collection of star-forming knots presents a metallicity gradient
steadily decreasing from the centre of the galaxy outwards, and the ages of the
stars across the galaxy show that the tails formed <10^9 yr ago. This result is
consistent with an estimate of the stripping timescale (1 Gyr), obtained from a
toy orbital model. Overall, our results independently and consistently support
a scenario in which a recent or ongoing event of intense ram-pressure stripping
acting from the outer disk inwards, causes removal and compression of gas, thus
altering the AGN and star-formation activity within and around the galaxy.


  A connected $k$-uniform hypergraph with $n$ vertices and $m$ edges is called
$r$-cyclic if $n=m(k-1)-r+1$. For $r=1$ or $2$, the hypergraph is simply called
unicyclic or bicyclic. In this paper we investigate hypergraphs that attain
larger spectral radii among all simple connected $k$-uniform unicyclic and
bicyclic hypergraphs. Specifically, by using some edge operations, the formula
on power hypergraph eigenvalues, the weighted incidence matrix and a result on
linear unicyclic hypergraphs, we determined the first five hypergraphs with
larger spectral radius among all unicyclic hypergraphs and the first three over
all bicyclic hypergraphs.


  We have investigated properties of superconducting titanium nitride (TiN)
films that were sputtered over a large range of RF-induced DC bias voltage
applied to the substrate. Films grown with the largest bias voltages contained
cubic TiN phases with a large fraction of the (200) crystalline growth
orientation. These films also contained the smallest concentrations of oxygen
impurities, resulting in stoichiometric TiN. Over the range of bias, variations
of the stress from slightly tensile to highly compressive were measured and
correlated to crystallinity of the (200) growth. The films exhibited highly
uniform thickness and resistivity, and show the potential for yielding
reproducible low-temperature devices. Finally, coplanar resonators fabricated
with the films exhibited high kinetic inductance and quality factor, where the
latter was obtained in part from temperature-dependent frequency shifts.


  We present a novel method for inserting objects, specifically humans, into
existing images, such that they blend in a photorealistic manner, while
respecting the semantic context of the scene. Our method involves three
subnetworks: the first generates the semantic map of the new person, given the
pose of the other persons in the scene and an optional bounding box
specification. The second network renders the pixels of the novel person and
its blending mask, based on specifications in the form of multiple appearance
components. A third network refines the generated face in order to match those
of the target person. Our experiments present convincing high-resolution
outputs in this novel and challenging application domain. In addition, the
three networks are evaluated individually, demonstrating for example, state of
the art results in pose transfer benchmarks.


  In this paper, we consider a free boundary problem with volume constraint. We
show that positive minimizer is locally Lipschitz and the free boundary is
analytic away from a singular set with Hausdorff dimension at most $n-8$.


  We report the electronic structure, electric and thermal transport properties
of Ru$_{1-x}$Ir$_{x}$Se$_2$ ($x \leq 0.2$). RuSe$_2$ is a semiconductor that
crystallizes in a cubic pyrite unit cell. The Seebeck coefficient of RuSe$_2$
exceeds -200 $\mu$V/K around 730 K. Ir substitution results in the suppression
of the resistivity and the Seebeck coefficient, suggesting the removal of the
peaks in density of states near the Fermi level. Ru$_{0.8}$Ir$_{0.2}$Se$_{2}$
shows a semiconductor-metal crossover at about 30 K. The magnetic field
restores the semiconducting behavior. Our results indicate the importance of
the electronic correlations in enhanced thermoelectricity of RuSb$_{2}$.


  We present an extensive parameter survey to study the influence of halo mass
profiles on the development of tidal tails in interacting disk galaxies. We
model the galaxies using a fixed exponential disk with a central bulge and vary
the halo potential over a range of parameters using both the Hernquist and NFW
mass distributions, probing the effect of the halo mass, extent and
concentration. We examine the consistency of the results against both
observational and theoretical constraints on halo profiles and comment on the
failures and weaknesses of different models. Galaxies with rising or flat
rotation curves dominated by the halo are inhibited from forming tidal tails
unless the halo is abruptly cut off just beyond the disk edge. Conversely,
models with declining rotation curves -- resulting either from compact, low
mass halos, or from massive disk components in low concentration dark halos --
produce tidal tails very similar to those observed in well-studied interacting
systems. As argued by Springel & White (1998), a unifying, quantitative
relation for all cases is that the ratio of the escape velocity to the circular
velocity at around the solar radius must be v_e/v_c<2.5 for tidal tails to be
produced. The galaxy models which appear to fit most of the observational
constraints are those which have disk-dominated rotation curves and low
concentration halos. We discuss our results in a cosmological context using
recent studies which link halo properties to cosmological models.