  This paper proposes a computationally efficient method to estimate the
time-varying relative pose between two visual-inertial sensor rigs mounted on
the flexible wings of a fixed-wing unmanned aerial vehicle (UAV). The estimated
relative poses are used to generate highly accurate depth maps in real-time and
can be employed for obstacle avoidance in low-altitude flights or landing
maneuvers. The approach is structured as follows: Initially, a wing model is
identified by fitting a probability density function to measured deviations
from the nominal relative baseline transformation. At run-time, the prior
knowledge about the wing model is fused in an Extended Kalman filter~(EKF)
together with relative pose measurements obtained from solving a relative
perspective N-point problem (PNP), and the linear accelerations and angular
velocities measured by the two inertial measurement units (IMU) which are
rigidly attached to the cameras. Results obtained from extensive synthetic
experiments demonstrate that our proposed framework is able to estimate highly
accurate baseline transformations and depth maps.


  Let (g,[p]) be a finite-dimensional restricted Lie algebra, defined over an
algebraically closed field k of characteristic p>0. The scheme of tori of
maximal dimension of g gives rise to a finite group S(g) that coincides with
the Weyl group of g in case g is a Lie algebra of classical type. In this
paper, we compute the group S(g) for Lie algebras of Cartan type and provide
applications concerning weight space decompositions, the existence of generic
tori and polynomial invariants.


  A question whether there exists an interaction between the spins of the
endohedral atom $A$@C$_{60}$ and the properties of the confining shell which
might affect the alignment of, or manipulation by, the spins for building a
register for a quantum computer is discussed. It is argued that an effect,
termed the `C$_{60}$ spin-charging' effect, can occur in endohedral atoms and
would affect the operation of a quantum register. The effect is exemplified by
choosing the $\rm 3d$ (Cr and Mn) and $\rm 4d$ (Mo and Tc) transition metal
atoms as well as a rare-earth Eu atom as the case study. A class of high-spin
atoms which are less suitable for building a quantum register is, thus,
identified.


  In this paper, we prove a Donsker type approximation theorem for the
Rosenblatt process, which is a selfsimilar stochastic process exhibiting long
range dependence. By using numerical results and simulated data, we show that
this approximation performs very well. We use this result to construct a binary
market model driven by this process and we show that the model admits arbitrage
opportunities.


  Segmenting foreground object from a video is a challenging task because of
the large deformations of the objects, occlusions, and background clutter. In
this paper, we propose a frame-by-frame but computationally efficient approach
for video object segmentation by clustering visually similar generic object
segments throughout the video. Our algorithm segments various object instances
appearing in the video and then perform clustering in order to group visually
similar segments into one cluster. Since the object that needs to be segmented
appears in most part of the video, we can retrieve the foreground segments from
the cluster having maximum number of segments, thus filtering out noisy
segments that do not represent any object. We then apply a track and fill
approach in order to localize the objects in the frames where the object
segmentation framework fails to segment any object. Our algorithm performs
comparably to the recent automatic methods for video object segmentation when
benchmarked on DAVIS dataset while being computationally much faster.


  This paper introduces a computationally efficient comparative approach to
classical pricing rules for day-ahead electricity markets, namely Convex Hull
Pricing, IP Pricing and European-like market rules, in a Power Exchange setting
with non-convex demand bids. These demand bids can, for example, be useful to
large industrial consumers, and extend demand block orders in use by European
Power Exchanges. For this purpose, we show that Convex Hull Prices can be
efficiently computed using continuous relaxations for bidding products
involving start-up costs, minimum power output levels and ramp constraints, or
analogous versions on the demand side. Relying on existing efficient
algorithmic approaches to handle European-like market rules for such bidding
products, we provide comparative numerical experiments using realistic data,
which, together with stylized examples, elucidates the relative merits of each
pricing rule from economic and computational perspectives. The motivation for
this work is the prospective need for mid-term evolution of day-ahead markets
in Europe and in the US, as well as the importance of day-ahead price signals,
since these (spot) prices are used as reference prices for many power
derivatives. The datasets, models and algorithms programmed in Julia/JuMP are
provided in an online Git repository.


  The inverse ac Josephson effect involves rf-induced (Shapiro) steps that
cross over the zero-current axis; the phenomenon is of interest in voltage
standard applications. The standard analysis of the step height in current,
which yields the well-known Bessel-function dependence on an effective ac drive
amplitude, is valid only when the drive frequency is large compared with the
junction plasma frequency or when the drive amplitude is large compared with
the zero-voltage Josephson current. Using a first-order Krylov-Bogoliubov
power-balance approach we derive an expression for the threshold value of the
drive amplitude for zero-crossing steps that is not limited to the large
frequency or large amplitude region. Comparison with numerical solutions of the
RSJ differential equation shows excellent agreement for both fundamental and
subharmonic steps. The power-balance value for the threshold converges to the
Bessel-function value in the high- frequency limit.


  Cassini discovered a plethora of neutral and ionised molecules in Titan's
ionosphere including, surprisingly, anions and negatively charged molecules
extending up to 13,800 u/q. In this letter we forward model the Cassini
electron spectrometer response function to this unexpected ionospheric
component to achieve an increased mass resolving capability for negatively
charged species observed at Titan altitudes of 950-1300 km. We report on
detections consistently centered between 25.8-26.0 u/q and between 49.0-50.1
u/q which are identified as belonging to the carbon chain anions,
CN$^-$/C$_3$N$^-$ and/or C$_2$H$^-$/C$_4$H$^-$, in agreement with chemical
model predictions. At higher ionospheric altitudes, detections at 73-74 u/q
could be attributed to the further carbon chain anions C$_5$N$^-$/C$_6$H$^-$
but at lower altitudes and during further encounters, extend over a higher
mass/charge range. This, as well as further intermediary anions detected at
$>$100 u, provide the first evidence for efficient anion chemistry in space
involving structures other than linear chains. Furthermore, at altitudes below
$\sim$1100 km, the low mass anions ($<$150 u/q) were found to deplete at a rate
proportional to the growth of the larger molecules, a correlation that
indicates the anions are tightly coupled to the growth process. This study adds
Titan to an increasing list of astrophysical environments where chain anions
have been observed and shows that anion chemistry plays a role in the formation
of complex organics within a planetary atmosphere as well as in the
interstellar medium.


  We present a low-loss integrated photonics platform in the visible and near
ultraviolet regime. Fully-etched waveguides based on atomic layer deposition
(ALD) of aluminum oxide operate in a single transverse mode with $<$3 dB/cm
propagation loss at a wavelength of 371 nm. Ring resonators with intrinsic
quality factors exceeding 470,000 are demonstrated at 405 nm, and the thermo
optic coefficient of ALD aluminum oxide is estimated to be $2.75\times10^{-5}$
[RIU/$^\circ$C]. Absorption loss is sufficiently low to allow on-resonance
operation with intra-cavity powers up to at least 12.5 mW, limited by available
laser power. Experimental and simulated data indicates the propagation loss is
dominated by sidewall roughness, suggesting lower loss in the blue and UV is
achievable.


  Medication recommendation is a crucial task for intelligent healthcare
systems. Previous studies mainly recommend medications with electronic health
records (EHRs). However, some details of interactions between doctors and
patients may be ignored or omitted in EHRs, which are essential for automatic
medication recommendation. Therefore, we make the first attempt to recommend
medications with the conversations between doctors and patients. In this work,
we construct DIALMED, the first high-quality dataset for medical dialogue-based
medication recommendation task. It contains 11,996 medical dialogues related to
16 common diseases from 3 departments and 70 corresponding common medications.
Furthermore, we propose a Dialogue structure and Disease knowledge aware
Network (DDN), where a QA Dialogue Graph mechanism is designed to model the
dialogue structure and the knowledge graph is used to introduce external
disease knowledge. The extensive experimental results demonstrate that the
proposed method is a promising solution to recommend medications with medical
dialogues. The dataset and code are available at
https://github.com/f-window/DialMed.


  We study the entanglement preservation of two qubits locally interacting with
their reservoirs. We show that the existence of a bound state of the qubit and
its reservoir and the non-Markovian effect are two essential ingredients and
their interplay plays a crucial role in preserving the entanglement in the
steady state. When the non-Markovian effect is neglected, the entanglement
sudden death (ESD) is reproduced. On the other hand, when the non-Markovian is
significantly strong but the bound state is absent, the phenomenon of the ESD
and its revival is recovered. Our formulation presents a unified picture about
the entanglement preservation and provides a clear clue on how to preserve the
entanglement in quantum information processing.


  Sometimes, we do not use a maximum likelihood estimator of a probability but
it's a smoothed estimator in order to cope with the zero frequency problem.
This is often the case when we use the Naive Bayes classifier. Laplace
smoothing is a popular choice with the value of Laplace smoothing estimator
being the expected value of posterior distribution of the probability where we
assume that the prior is uniform distribution. In this paper, we investigate
the confidence intervals of the estimator of Laplace smoothing. We show that
the likelihood function for this confidence interval is the same as the
likelihood of a maximum likelihood estimated value of a probability of
Bernoulli trials. Although the confidence interval of the maximum likelihood
estimator of the Bernoulli trial probability has been studied well, and
although the approximate formulas for the confidence interval are well known,
we cannot use the interval of maximum likelihood estimator since the interval
contains the value 0, which is not suitable for the Naive Bayes classifier. We
are also interested in the accuracy of existing approximation methods since
these approximation methods are frequently used but their accuracy is not well
discussed. Thus, we obtain the confidence interval by numerically integrating
the likelihood function. In this paper, we report the difference between the
confidence interval that we computed and the confidence interval by approximate
formulas. Finally, we include a URL, where all of the intervals that we
computed are available.


  At the classical level, the inverse differential operator for the quadratic
term in the gauge field Lagrangian density fixed in the light front through the
multiplier (nA)^2 yields the standard two term propagator with single
unphysical pole of the type (kn)^-1. Upon canonical quantization on the
light-front, there emerges a third term of the form (kn^(mu)n^(nu))(kn)^-2.
This third term in the propagator has traditionally been dropped on the grounds
that is exactly cancelled by the "instantaneous" term in the interaction
Hamiltonian in the light-front. Our aim in this work is not to discuss which of
the propagators is the correct one, but rather to present at the classical
level, the gauge fixing conditions that can lead to the three-term propagator.


  A pebbling move on a graph removes two pebbles from a vertex and adds one
pebble to an adjacent vertex. A vertex is reachable from a pebble distribution
if it is possible to move a pebble to that vertex using pebbling moves. The
optimal pebbling number $\pi_{opt}$ is the smallest number $m$ needed to
guarantee a pebble distribution of $m$ pebbles from which any vertex is
reachable. A rubbling move is similar to a pebbling move, but it can remove the
two pebbles from two different vertex. The optimal rubbling number $\rho_{opt}$
is defined analogously to the optimal pebbling number.
  In this paper we give lower bounds on both the optimal pebbling and rubbling
numbers by the distance $k$ domination number. With this bound we prove that
for each $k$ there is a graph $G$ with diameter $k$ such that
$\rho_{opt}(G)=\pi_{opt}(G)=2^k$.


  We discuss possible variations of the effective gravitational constant with
length scale, predicted by most of alternative theories of gravity and unified
models of physical interactions. After a brief general exposition, we review in
more detail the predicted corrections to Newton's law of gravity in diverse
brane world models. We consider various configurations in 5 dimensions (flat,
de Sitter and AdS branes in Einstein and Einstein-Gauss-Bonnet theories, with
and without induced gravity and possible incomplete graviton localization), 5D
multi-brane systems and some models in higher dimensions. A common feature of
all models considered is the existence of corrections to Newton's law at small
radii comparable with the bulk characteristic length: at such radii, gravity on
the brane becomes effectively multidimensional. Many models contain superlight
perturbation modes, which modify gravity at large scale and may be important
for astrophysics and cosmology.


  The aim of this paper is to investigate the equivalence conditions for
uniform perfectness of quasi-metric spaces. We also obtain the invariant
property of uniform perfectness under quasim\"obius maps in quasi-metric
spaces. In the end, two applications are given.


  A key challenge in machine learning is to generalize from training data to an
application domain of interest. This work generalizes the recently-proposed
mixture invariant training (MixIT) algorithm to perform unsupervised learning
in the multi-channel setting. We use MixIT to train a model on far-field
microphone array recordings of overlapping reverberant and noisy speech from
the AMI Corpus. The models are trained on both supervised and unsupervised
training data, and are tested on real AMI recordings containing overlapping
speech. To objectively evaluate our models, we also use a synthetic
multi-channel AMI test set. Holding network architectures constant, we find
that a fine-tuned semi-supervised model yields the largest improvement to
SI-SNR and to human listening ratings across synthetic and real datasets,
outperforming supervised models trained on well-matched synthetic data. Our
results demonstrate that unsupervised learning through MixIT enables model
adaptation on both single- and multi-channel real-world speech recordings.


  We present a perturbation theory to find the response of an anisotropic DNA
to the external tension. It is shown that the anisotropy has a nonzero but
small contribution to the force-extension curve of the DNA. Thus an anisotropic
DNA behaves like an isotropic one with an effective bending constant equal to
the harmonic average of its soft and hard bending constants.


  We discuss the basic problem of signal transmission in quantum mechanics in
terms of topological theories. Using the analogy between knot diagrams and
quantum amplitudes we calculate the transmission coefficients of the concept
topological quantum devices that realize the knot topology. We observe that the
problem is in different ways similar to that of transmission on quantum graphs.
The desired transmission or filtering properties can be attained by the
variation of the topology of the device, or an external parameter, which in our
model controls the topological phase. One interesting property of the
transmission coefficients is the existence of "self-averaging" phases, in which
the value of the transmission coefficient is independent from all the
representatives in a chosen family of knots. We briefly discuss physical
realizations of the concept devices.


  We generalize the topological response theory of three-dimensional
topological insulators (TI) to metallic systems-specifically, doped TI with
finite bulk carrier density and a time-reversal symmetry breaking field near
the surface. We show that there is an inhomogeneity-induced Berry phase
contribution to the surface Hall conductivity that is completely determined by
the occupied states and is independent of other details such as band dispersion
and impurities. In the limit of zero bulk carrier density, this intrinsic
surface Hall conductivity reduces to the half-integer quantized surface Hall
conductivity of TI. Based on our theory we predict the behavior of the surface
Hall conductivity for a doped topological insulator with a top gate, which can
be directly compared with experiments.


  We investigate a spectrum of positive self-adjoint operator $\Gk$ (Laplace
operator) acting in the external complexes of some interesting subalgebras
$\Lk$ of Lie algebra $A_1^{(1)}$. We obtain an explicit formula for the action
of $\G_k$. This formula is used to compute the homology of $\Lk$ with trivial
coefficients for $k=-1,0,1,2$. In these cases we show that a spectrum of $\G_k$
is the set of non-negative integers with a finite multiplicity of each
eigenvalue for $k=-1,0$, infinite one for $k=1,2$. We also found the generating
functions for the multiplicities of $\G_k$-eigenvalues (in appropriate sense
for $\G_1$ and $\G_2$).


  The multimessenger event GW170817/GRB 170817A confirmed that binary neutron
star (BNS) mergers can produce short gamma-ray burst (SGRB) jets. This evidence
promoted new investigations on the mechanisms through which a BNS merger
remnant can launch such a powerful relativistic outflow and on the propagation
of the latter across the surrounding post-merger environment. In particular,
great strides have been made in jet propagation models, establishing
connections between the initial jet launching conditions, including the
incipient jet launching time (with respect to merger) and the injection
parameters, and the observable SGRB prompt and afterglow emission. However,
present semi-analytical models and numerical simulations (with one notable
exception) adopt simple hand-made prescriptions to account for the post-merger
environment, lacking a direct association with any specific merging BNS system.
Here, we present the first three-dimensional relativistic hydrodynamics
simulations of incipient SGRB jets propagating through a post-merger
environment that is directly imported from the outcome of a previous general
relativistic BNS merger simulation. Our results show that the evolution and
final properties of the jet can be largely affected by the anisotropies and the
deviations from axisymmetry and homologous expansion characterizing more
realistic BNS merger environments. In addition, we find that the inclusion of
the gravitational pull from the central compact object, often overlooked, can
have a major impact. Finally, we consider different jet launching times
referred to the same BNS merger model and discuss the consequences for the
ultimate jet properties.


  We show that quantum confinement in the valence and conduction bands of
semiconducting single-walled carbon nanotubes can be engineered by means of
artificial defects. This ability holds potential for designing future
nanotube-based quantum devices such as electrically driven room-temperature
single-photon sources emitting at telecom-wavelength. Using Ar$^{+}$ and
N$^{+}$ ion-induced defects, intrananotube quantum dots with sub-10 nm lateral
sizes are created, giving rise to quantized electronic bound states with level
spacings of the order of 100 meV and larger. Using low-temperature scanning
tunneling spectroscopy, we resolve the energy and real space properties of the
quantized states and compare them with theoretical model calculations. By
solving the Schr\"odinger equation over a one-dimensional piecewise constant
potential model, the effects of inhomogeneous defect scattering strength as
well as surface variations in the Au(111) substrate on the quantized states
structure are remarkably well reproduced. Furthermore, using ab-initio
calculations, we demonstrate that defect structures such as vacancies,
di-vacancies and chemisorbed nitrogen ad-atoms constitute strong scattering
centers able to form quantum dots with clear signatures of discrete bound
states as observed experimentally. The ab-initio simulations also allowed to
study the scattering strength profile as a function of energy for different
defect combinations, supporting the potential of highly stable double vacancies
for practical applications at room temperature.


  It is commonly believed that financial crises "lead to" lower growth of a
country during the two-year recession period, which can be reflected by their
post-crisis GDP growth. However, by contrasting a causal model with a standard
prediction model, this paper argues that such a belief is non-causal. To make
causal inferences, we design a two-stage staggered difference-in-differences
model to estimate the average treatment effects. Interpreting the residuals as
the contribution of each crisis to the treatment effects, we astonishingly
conclude that cross-sectional crises are often limited to providing relevant
causal information to policymakers.


  As an alternative to the usual key generation by two-way communication in
schemes for quantum cryptography, we consider codes for key generation by
one-way communication. We study codes that could be applied to the raw key
sequences that are ideally obtained in recently proposed scenarios for quantum
key distribution, which can be regarded as communication through symmetric
four-letter channels.


  The formation of massive stars is currently an unsolved problems in
astrophysics. Understanding the formation of massive stars is essential because
they dominate the luminous, kinematic, and chemical output of stars.
Furthermore, their feedback is likely to play a dominant role in the evolution
of molecular clouds and any subsequent star formation therein. Although
significant progress has been made observationally and theoretically, we still
do not have a consensus as to how massive stars form. There are two contending
models to explain the formation of massive stars, Core Accretion and
Competitive Accretion. They differ primarily in how and when the mass that
ultimately makes up the massive star is gathered. In the core accretion model,
the mass is gathered in a prestellar stage due to the overlying pressure of a
stellar cluster or a massive pre-cluster cloud clump. In contrast, competitive
accretion envisions that the mass is gathered during the star formation process
itself, being funneled to the centre of a stellar cluster by the gravitational
potential of the stellar cluster. Although these differences may not appear
overly significant, they involve significant differences in terms of the
physical processes involved. Furthermore, the differences also have important
implications in terms of the evolutionary phases of massive star formation, and
ultimately that of stellar clusters and star formation on larger scales. Here
we review the dominant models, and discuss prospects for developing a better
understanding of massive star formation in the future.


  Langevin diffusion is a commonly used tool for sampling from a given
distribution. In this work, we establish that when the target density $p^*$ is
such that $\log p^*$ is $L$ smooth and $m$ strongly convex, discrete Langevin
diffusion produces a distribution $p$ with $KL(p||p^*)\leq \epsilon$ in
$\tilde{O}(\frac{d}{\epsilon})$ steps, where $d$ is the dimension of the sample
space. We also study the convergence rate when the strong-convexity assumption
is absent. By considering the Langevin diffusion as a gradient flow in the
space of probability distributions, we obtain an elegant analysis that applies
to the stronger property of convergence in KL-divergence and gives a
conceptually simpler proof of the best-known convergence results in weaker
metrics.


  Current state-of-the-art approaches to skeleton-based action recognition are
mostly based on recurrent neural networks (RNN). In this paper, we propose a
novel convolutional neural networks (CNN) based framework for both action
classification and detection. Raw skeleton coordinates as well as skeleton
motion are fed directly into CNN for label prediction. A novel skeleton
transformer module is designed to rearrange and select important skeleton
joints automatically. With a simple 7-layer network, we obtain 89.3% accuracy
on validation set of the NTU RGB+D dataset. For action detection in untrimmed
videos, we develop a window proposal network to extract temporal segment
proposals, which are further classified within the same network. On the recent
PKU-MMD dataset, we achieve 93.7% mAP, surpassing the baseline by a large
margin.


  The transition from petascale to exascale computers is characterized by
substantial changes in the computer architectures and technologies. The
research community relying on computational simulations is being forced to
revisit the algorithms for data generation and analysis due to various
concerns, such as higher degrees of concurrency, deeper memory hierarchies,
substantial I/O and communication constraints. Simulations today typically save
all data to analyze later. Simulations at the exascale will require us to
analyze data as it is generated and save only what is really needed for
analysis, which must be performed predominately in-situ, i.e., executed
sufficiently fast locally, limiting memory and disk usage, and avoiding the
need to move large data across nodes.
  In this paper, we present a distributed method that enables in-situ data
analysis for large protein folding trajectory datasets. Traditional trajectory
analysis methods currently follow a centralized approach that moves the
trajectory datasets to a centralized node and processes the data only after
simulations have been completed. Our method, on the other hand, captures
conformational information in-situ using local data only while reducing the
storage space needed for the part of the trajectory under consideration. This
method processes the input trajectory data in one pass, breaks from the
centralized approach of traditional analysis, avoids the movement of trajectory
data, and still builds the global knowledge on the formation of individual
$\alpha$-helices or $\beta$-strands as trajectory frames are generated.


  We compare the dark matter halos' structural parameters derived for four
Milky Way dwarf spheroidal galaxies to those of subhalos found in cosmological
$N$-body simulations. We confirm that estimates of the mass at a single fixed
radius are fully consistent with the observations. However, when a second
structural parameter such as the logarithmic slope of the dark halo density
profile measured close to the half-light radius is included in the comparison,
we find little to no overlap between the satellites and the subhalos. Typically
the right mass subhalos have steeper profiles at these radii than measurements
of the dSph suggest. Using energy arguments we explore if it is possible to
solve this discrepancy by invoking baryonic effects. Assuming that feedback
from supernovae can lead to a reshaping of the halos, we compute the required
efficiency and find entirely plausible values for a significant fraction of the
subhalos and even as low as 0.1%. This implies that care must be taken not to
exaggerate the effect of supernovae feedback as this could make the halos too
shallow. These results could be used to calibrate and possibly constrain
feedback recipes in hydrodynamical simulations.


  To benefit from utility-driven and rule-based approaches to self-adaptation,
we propose combining both by defining and linking the utility function and the
adaptation rules in a pattern-based way at the architectural level.


  A finite group $G$ is said to be admissible over a field $F$ if there exists
a division algebra $D$ central over $F$ with a maximal subfield $L$ such that
$L/F$ is Galois with group $G$. In this paper we give a complete
characterization of admissible groups over function fields of curves over
equicharacteristic complete discretely valued fields with algebraically closed
residue fields, such as the field $\overline{\mathbb{F}_P}((t))(x)$.


  We construct and analyze an ultraviolet extension of a model in which
electroweak symmetry breaking is due to both technifermion and top-quark
condensates. The model includes dynamical mechanisms for all of the various
gauge symmetry breakings. We discuss certain aspects in which it requires
additional ingredients to be more realistic.


  We consider the production of neutrinos in active galactic nuclei (AGN)
through hadronic cascades. The initial, high energy nucleons are accelerated in
a source above the accretion disk around the central black hole. From the
source, the particles diffuse back to the disk and initiate hadronic cascades.
The observable output from the cascade are electromagnetic radiation and
neutrinos. We use the observed diffuse background X-ray luminosity, which
presumably results {}from this process, to predict the diffuse neutrino flux
close to existing limits from the Frejus experiment. The resulting neutrino
spectrum is $E^{-2}$ down to the $\GeV$ region. We discuss modifications of
this scenario which reduce the predicted neutrino flux.


  Active galaxies and gamma ray bursts are the sources of the highest energy
photons detected by astronomical telescopes. We speculate that they may be the
sources of the highest energy cosmic rays. This makes them true proton
accelerators, where the highest energy photons are the decay products of
neutral pions photoproduced when the proton beams interacts with ambient
radiation. Neutrinos from the decay of charged pions represent an
incontrovertible signature for proton acceleration. A main theme of this talk
is that their fluxes can be estimated from the measured gamma ray luminosity by
model-independent methods, based on dimensional analysis and textbook particle
physics.


  An exhaustive list of four-dimensional $\Lambda$-vacuum spacetimes admitting
a Killing vector whose self-dual Killing two-form ${\cal F}$ is null is
obtained assuming that the self-dual Weyl tensor is proportional to the tensor
product of ${\cal F}$ by itself. Our analysis complements previous results
concerning the case with non-null ${\cal F}$. We analyze both cases with
$\Lambda$ vanishing or not. In the latter case we prove that $\Lambda< 0$ must
hold necessarily, and we find a characterization of the Einstein spacetimes
conformal to pp-waves. In the former case we obtain spacetime characterizations
of vacuum plane waves and of the stationary vacuum Brinkmann spacetimes. At the
light of the full set of results, old and new, we reformulate the case with
non-null ${\cal F}$ and $\Lambda= 0$. We finally present a table collecting the
results for both null, and non-null, ${\cal F}$.


  We study the hadron production at finite values of temperature and baryon
density by means of an effective relativistic mean-field model with the
inclusion of the full octet of baryons, the Delta-isobar degrees of freedom and
the lightest pseudoscalar and vector mesons. These last particles are
considered in the so-called one-body contribution, taking into account of an
effective chemical potential and mass depending on the self-consistent
interaction between baryons. The analysis is performed by requiring the Gibbs
conditions on the global conservation of baryon number, electric charge
fraction and zero net strangeness. In this context, we study the behavior of
different particle-antiparticle ratios and strangeness production.


  Error correction plays a major role in the reconciliation of continuous
variable quantum key distribution (CV-QKD) and greatly affects the performance
of the system. CV-QKD requires error correction codes of extremely low rates
and high reconciliation efficiencies. There are only very few code designs
available in this ultra low rate regime. In this paper, we introduce a method
for designing protograph-based ultra low rate LDPC codes using differential
evolution. By proposing type-based protographs, a new way of representing low
rate protograph-based LDPC codes, we drastically reduce the complexity of the
protograph optimization, which enables us to quickly design codes over a wide
range of rates. We show that the codes resulting from our optimization
outperform the codes from the literature both in regards to the threshold and
in finite-length performance, validated by Monte-Carlo simulations, showing
gains in the regime relevant for CV-QKD.


  We report the crystal structures and physical properties of trilayer
nickelates Nd$_4$Ni$_3$O$_{10}$ and Nd$_4$Ni$_3$O$_8$. Measurements of
magnetization and electrical resistivity display contrasting behaviors in the
two compounds. Nd$_4$Ni$_3$O$_{10}$ shows a paramagnetic metallic behavior with
a metal to metal phase transition($T^{\ast}$) at about 162 K, as revealed by
both magnetic susceptibility and resistivity. Further magnetoresistance and
Hall coefficient results show a negative magnetoresistance at low temperatures
and the carrier type of Nd$_4$Ni$_3$O$_{10}$ is dominated by hole-type charge
carriers. The significant enhancement of Hall coefficient and resistivity below
$T^{\ast}$ suggest that effective charge carrier density decreases when cooling
through the transition temperature. In contrast, Nd$_4$Ni$_3$O$_8$ shows an
insulating behavior despite small value of resistivity at room temperature. The
compound shows paramagnetic behavior, with the similar magnetic moments as in
Nd$_4$Ni$_3$O$_{10}$ derived from the Curie-Weiss fitting. This may suggest
that the magnetic moments in both systems are contributed by the Nd ions. By
applying pressures up to about 49 GPa, the insulating behavior is still present
and becomes even stronger. Our results suggest that the different Ni
configurations ($Ni^{1+/2+}$ or $Ni^{2+/3+}$) and competition between localized
and itinerant electrons may account for the contrasting behaviors in trilayer
nickelates Nd$_4$Ni$_3$O$_{10}$ and Nd$_4$Ni$_3$O$_8$.


  The giant impact phase of terrestrial planet formation establishes
connections between super-Earths' orbital properties (semimajor axis spacings,
eccentricities, mutual inclinations) and interior compositions (the presence or
absence of gaseous envelopes). Using N-body simulations and analytic arguments,
we show that spacings derive not only from eccentricities, but also from
inclinations. Flatter systems attain tighter spacings, a consequence of an
eccentricity equilibrium between gravitational scatterings, which increase
eccentricities, and mergers, which damp them. Dynamical friction by residual
disk gas plays a critical role in regulating mergers and in damping
inclinations and eccentricities. Systems with moderate gas damping and high
solid surface density spawn gas-enveloped super-Earths with tight spacings,
small eccentricities, and small inclinations. Systems in which super-Earths
coagulate without as much ambient gas, in disks with low solid surface density,
produce rocky planets with wider spacings, larger eccentricities, and larger
mutual inclinations. A combination of both populations can reproduce the
observed distributions of spacings, period ratios, transiting planet
multiplicities, and transit duration ratios exhibited by Kepler super-Earths.
The two populations, both formed in situ, also help to explain observed trends
of eccentricity vs. planet size, and bulk density vs. method of mass
measurement (radial velocities vs. transit timing variations). Simplifications
made in this study --- including the limited timespan of the simulations, and
the approximate treatments of gas dynamical friction and gas depletion history
--- should be improved upon in future work to enable a detailed quantitative
comparison to the observations.


  Urban Air Mobility (UAM) offers a solution to current traffic congestion by
providing on-demand air mobility in urban areas. Effective traffic management
is crucial for efficient operation of UAM systems, especially for high-demand
scenarios. In this paper, we present a centralized traffic management framework
for on-demand UAM systems. Specifically, we provide a scheduling policy, called
VertiSync, which schedules the aircraft for either servicing trip requests or
rebalancing in the system subject to aircraft safety margins and energy
requirements. We characterize the system-level throughput of VertiSync, which
determines the demand threshold at which passenger waiting times transition
from being stabilized to being increasing over time. We show that the proposed
policy is able to maximize throughput for sufficiently large fleet sizes. We
demonstrate the performance of VertiSync through a case study for the city of
Los Angeles, and show that it significantly reduces passenger waiting times
compared to a first-come first-serve scheduling policy.


  The level densities and $\gamma$-strength functions of the weakly deformed
$^{148}$Sm and $^{149}$Sm nuclei have been extracted. The temperature versus
excitation energy curve, derived within the framework of the micro canonical
ensemble, shows structures, which we associate with the break up of Cooper
pairs. The nuclear heat capacity is deduced within the framework of both the
micro canonical and the canonical ensemble. We observe negative heat capacity
in the micro canonical ensemble whereas the canonical heat capacity exhibits an
S-shape as function of temperature, both signals of a phase transition. The
structures in the $\gamma$-strength functions are discussed in terms of the
pygmy resonance and the scissors mode built on exited states. The samarium
results are compared with data for the well deformed $^{161,162}$Dy,
$^{166,167}$Er and $^{171,172}$Yb isotopes and with data from
(n,$\gamma$)-experiments and giant dipole resonance studies.


  Sizing and fitting of Personal Protective Equipment (PPE) is a critical part
of the product creation process; however, traditional methods to do this type
of work can be labor intensive and based on limited or non-representative
anthropomorphic data. In the case of PPE, a poor fit can jeopardize an
individual's health and safety. In this paper we present an unsupervised
machine learning algorithm that can identify a representative set of exemplars,
individuals that can be utilized by designers as idealized sizing models. The
algorithm is based around a Variational Autoencoder (VAE) with a Point-Net
inspired encoder and decoder architecture trained on Human point-cloud data
obtained from the CEASAR dataset. The learned latent space is then clustered to
identify a specified number of sizing groups. We demonstrate this technique on
scans of human faces to provide designers of masks and facial coverings a
reference set of individuals to test existing mask styles.


  Solar energy is one of important renewable energy sources and simulation of
solar irradiance can be used as input for simulation of photovoltaic (PV)
generation. This paper proposes a simulation algorithm of multi-station solar
irradiance data considering temporal correlations. First of all, we group all
the days of the observed data to k clusters for each station based on their
daily features of solar irradiance and the daily states constitute Markov chain
of days. Then, we reduce state permutations of different stations before
getting Markov Transition Probability Matrix (MTPM). In terms of the observed
data and MTPM, the simulation approach is proposed. Finally, we test our
approach by applying to solar irradiance data of three stations and show that
the properties of simulated data match those of the observed data.


  This review discusses the complementary relationship between radio and hard
X-ray observations of the Sun using primarily results from the era of the
Reuven Ramaty High Energy Solar Spectroscopic Imager satellite. A primary focus
of joint radio and hard X-ray studies of solar flares uses observations of
nonthermal gyrosynchrotron emission at radio wavelengths and bremsstrahlung
hard X-rays to study the properties of electrons accelerated in the main flare
site, since it is well established that these two emissions show very similar
temporal behavior. A quantitative prescription is given for comparing the
electron energy distributions derived separately from the two wavelength
ranges: this is an important application with the potential for measuring the
magnetic field strength in the flaring region, and reveals significant
differences between the electrons in different energy ranges. Examples of the
use of simultaneous data from the two wavelength ranges to derive physical
conditions are then discussed, including the case of microflares, and the
comparison of images at radio and hard X-ray wavelengths is presented. There
have been puzzling results obtained from observations of solar flares at
millimeter and submillimeter wavelengths, and the comparison of these results
with corresponding hard X-ray data is presented. Finally, the review discusses
the association of hard X-ray releases with radio emission at decimeter and
meter wavelengths, which is dominated by plasma emission (at lower frequencies)
and electron cyclotron maser emission (at higher frequencies), both coherent
emission mechanisms that require small numbers of energetic electrons. These
comparisons show broad general associations but detailed correspondence remains
more elusive.


  We construct the most general Ricci-flat metrics in (D+n) dimensions that
preserve the R^{1,n-1}\times SO(D) isometry. The equations of motion are
governed by the system of a GL(n,\R)/SO(1,n-1) scalar coset coupled to
D-dimensional gravity. Among the solutions, we find a large class of smooth
Lorentzian wormholes that connect two asymptotic flat spacetimes. In addition,
we obtain new vacuum tachyonic wave solutions in D\ge 4 dimensions, which fit
the general definition of pp-waves in that there exists a covariantly constant
null vector. The momenta of the tachyon waves are larger than their ADM masses.
The world-volume of the tachyon wave is R^{1,2}, instead of R^{1,1} for the
usual vacuum pp-wave. We show that the tachyon wave solutions admit no Killing
spinors, except in D=4, in which case it preserves half of the supersymmetry.
We also obtain a general class of p-brane wormhole and tachyon wave solutions
where the R^{1,n-1} part of the spacetime lies in the the world-volume of the
p-branes. These include examples of M-branes and D3-brane. Furthermore, we
obtain AdS tachyon waves in D\ge 4 dimensions.


  Thanks to their versatility, nitrogen-vacancy (NV) centers in nanodiamonds
have been widely adopted as nanoscale sensors. However, their sensitivities are
limited by their short coherence times relative to NVs in bulk diamond. A more
complete understanding of the origins of decoherence in nanodiamonds is
critical to improving their performance. Here we present measurements of fast
spin relaxation on qutrit transitions between the energy eigenstates composed
of the $m_s = \pm1$ states of the NV$^-$ electronic ground state in $\sim40$-nm
nanodiamonds under ambient conditions. For frequency splittings between these
states of $\sim20~$MHz or less the maximum theoretically achievable coherence
time of the NV spin is $\sim2~$orders of magnitude shorter than would be
expected if the NV spin is treated as a qubit. We attribute this fast
relaxation to electric field noise. We observe a strong falloff of the qutrit
relaxation rate with the splitting between the states, suggesting that,
whenever possible, measurements with NVs in nanodiamonds should be performed at
moderate axial magnetic fields ($>60$ G). We also observe that the qutrit
relaxation rate changes with time. These findings indicate that surface
electric field noise is a major source of decoherence for NVs in nanodiamonds.


  We present numerical simulations of giant planet migration in our solar
system and examine how the speed of planetary migration affects inclinations in
the resulting population of small bodies (test particles) scattered outward and
subsequently captured into Neptune's 3:2 mean motion resonance (the Plutinos)
as well as the hot classical Kuiper belt population. We do not find a
consistent relationship between the degree of test particle inclination
excitation and e-folding planet migration timescales in the range 5-50 Myr. Our
results present a counter-example to Nesvorny 2015's finding that the Plutino
and hot classical inclinations showed a marked increase with increasing
e-folding timescales for Neptune's migration. We argue that these differing
results are likely due to differing secular architectures of the giant planets
during and after migration. Small changes in the planets' initial conditions
and differences in the numerical implementation of planet migration can result
in different amplitudes of the planets' inclination secular modes, and this can
lead to different final inclination distributions for test particles in the
simulations. We conclude that the observed large inclination dispersion of
Kuiper belt objects does not require Neptune's migration to be slow; planetary
migration with e-folding timescales of 5, 10, 30, and 50 Myr can all yield
inclination dispersions similar to the observed Plutino and hot classical
populations, with no correlation between the degree of inclination excitation
and migration speed.


  Let $\Gamma$ be a geometrically-finite Fuchsian group acting on the upper
half plane $\hh.$ Let $\E$ denote the set of elliptic fixed points of $\Gamma$
in $\hh.$ We give a lower bound on the minimal hyperbolic distance between
points in $\E.$ Our bound depends on a universal constant and the length of the
smallest closed geodesic on $\Gamma \backslash \hh.$


  We present decompositions of the rotation curves of three spiral galaxies at
redshifts z~0.7 and 1 into contributions by their bulges, disks, and dark
halos, respectively. In order to set constraints on the degeneracy of the
decompositions we interpret the morphology of the spiral structures
quantitatively in the framework of density wave theory. Galaxy models
constrained in such a way show that the distant galaxies, which are much
younger than nearby galaxies, have very likely 'maximum disks', i.e. are
dominated in their inner parts by baryonic matter. We argue that current
theories of the cosmogony of galaxies must allow for these types of galaxies.


  By adding gauge fields to the D-string classical solution, which have
non-zero contribution to commutators in continuum limit (extreme large $N$), we
introduced $(m,n)$-strings in IIB matrix model. It is found that the size of
matrices depends on the value of the electric field. The tension of these
strings appears in $SL(2,Z)$ invariant form. The interaction for parallel and
angled strings are found in agreement with the string theory for small electric
fields.


  The gradual patterns that model the complex co-variations of attributes of
the form "The more/less X, The more/less Y" play a crucial role in many real
world applications where the amount of numerical data to manage is important,
this is the biological data. Recently, these types of patterns have caught the
attention of the data mining community, where several methods have been defined
to automatically extract and manage these patterns from different data models.
However, these methods are often faced the problem of managing the quantity of
mined patterns, and in many practical applications, the calculation of all
these patterns can prove to be intractable for the user-defined frequency
threshold and the lack of focus leads to generating huge collections of
patterns. Moreover another problem with the traditional approaches is that the
concept of gradualness is defined just as an increase or a decrease. Indeed, a
gradualness is considered as soon as the values of the attribute on both
objects are different. As a result, numerous quantities of patterns extracted
by traditional algorithms can be presented to the user although their
gradualness is only a noise effect in the data. To address this issue, this
paper suggests to introduce the gradualness thresholds from which to consider
an increase or a decrease. In contrast to literature approaches, the proposed
approach takes into account the distribution of attribute values, as well as
the user's preferences on the gradualness threshold and makes it possible to
extract gradual patterns on certain databases where literature approaches fail
due to too large search space. Moreover, results from an experimental
evaluation on real databases show that the proposed algorithm is scalable,
efficient, and can eliminate numerous patterns that do not verify specific
gradualness requirements to show a small set of patterns to the user.


  Let $G$ be a semisimple, simply connected algebraic group over an
algebraically closed field of characteristic zero. We prove that the
$\infty$-category of D-modules on the loop group of $G$ is equivalent to the
monoidal colimit of the $\infty$-categories of D-modules on the standard
parahoric subgroups. This also follows from arXiv:2009.10998, but the present
paper gives a simpler proof. The idea is to develop a combinatorial model for
the path space of a simplicial complex, in which 'paths' are sequences of
adjacent simplices, and to use a generalized version of hyperdescent for
D-modules. We also give two more applications of this hyperdescent theorem:
triviality of D-modules on the 'schematic Bruhat-Tits building,' which was
first established by Varshavsky using a different method, and triviality of
D-modules on the `simplicial affine Springer resolution.'


  Using standard methods for studying singularities of projections and of
contacts, we classify the stable singularities of affine $\lambda$-equidistants
of $n$-dimensional closed submanifolds of $\mathbb R^q$, for $q\leq 2n$,
whenever $(2n,q)$ is a pair of nice dimensions.


  By using the Ringel-Hall algebra approach, we investigate the structure of
the Lie algebra $L(\Lambda)$ generated by indecomposable constructible sets in
the varieties of modules for any finite dimensional $\mathbb{C}$-algebra
$\Lambda.$ We obtain a geometric realization of the universal enveloping
algebra $R(\Lambda)$ of $L(\Lambda).$ This generalizes the main result of
Riedtmann in \cite{R}. We also obtain Green's theorem in \cite{G} in a
geometric form for any finite dimensional $\mathbb{C}$-algebra $\Lambda$ and
use it to give the comultiplication formula in $R(\Lambda).$


  The magnetic field of the classical T Tauri star V2129 Oph can be modeled
approximately by superposing slightly tilted dipole and octupole moments, with
polar magnetic field strengths of 0.35kG and 1.2kG respectively (Donati et al.
2007). Here we construct a numerical model of V2129 Oph incorporating this
result and simulate accretion onto the star. Simulations show that the disk is
truncated by the dipole component and matter flows towards the star in two
funnel streams. Closer to the star, the flow is redirected by the octupolar
component, with some of the matter flowing towards the high-latitude poles, and
the rest into the octupolar belts. The shape and position of the spots differ
from those in a pure dipole case, where crescent-shaped spots are observed at
the intermediate latitudes. Simulations show that if the disk is truncated at
the distance of 6.2 R_* which is comparable with the co-rotation radius, 6.8
R_*, then the high-latitude polar spots dominate, but the accretion rate
obtained from the simulations is about an order of magnitude lower than the
observed one. The accretion rate matches the observed one if the disk is
disrupted much closer to the star, at 3.4 R_*. However, the octupolar belt
spots strongly dominate. Better match has been obtained in experiments with a
dipole field twice as strong. The torque on the star from the
disk-magnetosphere interaction is small, and the time-scale of spin evolution,
2 x10^7-10^9 years is longer than the 2x10^6 years age of V2129 Oph. The
external magnetic flux of the star is strongly influenced by the disk: the
field lines connecting the disk and the star inflate and form magnetic towers
above and below the disk. The potential (vacuum) approximation is still valid
inside the Alfv\'en (magnetospheric) surface where the magnetic stress
dominates over the matter stress.


  Real-world large-scale datasets usually contain noisy labels and are
imbalanced. Therefore, we propose derivative manipulation (DM), a novel and
general example weighting approach for training robust deep models under these
adverse conditions.
  DM has two main merits. First, loss function and example weighting are common
techniques in the literature. DM reveals their connection (a loss function does
example weighting) and is a replacement of both. Second, despite that a loss
defines an example weighting scheme by its derivative, in the loss design, we
need to consider whether it is differentiable. Instead, DM is more flexible by
directly modifying the derivative so that a loss can be a non-elementary format
too. Technically, DM defines an emphasis density function by a derivative
magnitude function. DM is generic in that diverse weighting schemes can be
derived.
  Extensive experiments on both vision and language tasks prove DM's
effectiveness.


  A proposal is made for the quantum state of the universe that has an initial
state that is macroscopically time symmetric about a homogeneous, isotropic
bounce of extremal volume and that at that bounce is microscopically in the
ground state for inhomogeneous and/or anisotropic perturbation modes. The
coarse-grained entropy is minimum at the bounce and then grows during inflation
as the modes become excited away from the bounce and interact (assuming the
presence of an inflaton, and in the part of the quantum state in which the
inflaton is initially large enough to drive inflation). The part of this pure
quantum state that dominates for observations is well approximated by quantum
processes occurring within a Lorentzian expanding macroscopic universe. Because
this part of the quantum state has no negative Euclidean action, one can avoid
the early-time Boltzmann brains and Boltzmann solar systems that appear to
dominate observations in the Hartle-Hawking no-boundary wavefunction.


  We propose a microscopic stochastic approach to improve description of
nuclear dynamics beyond the mean-field approximation at low energies. It is
shown that, for small amplitude fluctuations, the proposed model gives a result
for the dispersion of a one-body observable that is identical to the result
obtained previously through a variational approach. Furthermore, by projecting
the proposed stochastic mean-field evolution on a collective path, a
generalized Langevin equation is derived for collective variable, which
incorporate one-body dissipation and one-body fluctuation mechanism in
accordance with quantal fluctuation-dissipation relation.


  It has been conjectured that the (weakly coupled) Randall-Sundrum (RS) model
with gauge fields in the bulk is dual to a (strongly coupled) 4D conformal
field theory (CFT) with an UV cut-off and in which global symmetries of the CFT
are gauged. We elucidate features of this dual CFT which are crucial for a
complete understanding of the proposed duality. We argue that the limit of no
(or small) brane-localized kinetic term for bulk gauge field on the RS side
(often studied in the literature) is dual to no bare kinetic term for the gauge
field which is coupled to the CFT global current. In this limit, the kinetic
term for this gauge field in the dual CFT is ``induced'' by CFT loops. Then,
this CFT loop contribution to the gauge field 1PI two-point function is dual
(on the RS side) to the full gauge propagator (i.e., including the contribution
of Kaluza-Klein and zero-modes) with both external points on the Planck brane.
We also emphasize that loop corrections to the gauge coupling on the RS side
are dual to sub-leading effects in a large-N expansion on the CFT side; these
sub-leading corrections to the gauge coupling in the dual CFT are (in general)
sensitive to the strong dynamics of the CFT.


  There are a countless number of fonts with various shapes and styles. In
addition, there are many fonts that only have subtle differences in features.
Due to this, font identification is a difficult task. In this paper, we propose
a method of determining if any two characters are from the same font or not.
This is difficult due to the difference between fonts typically being smaller
than the difference between alphabet classes. Additionally, the proposed method
can be used with fonts regardless of whether they exist in the training or not.
In order to accomplish this, we use a Convolutional Neural Network (CNN)
trained with various font image pairs. In the experiment, the network is
trained on image pairs of various fonts. We then evaluate the model on a
different set of fonts that are unseen by the network. The evaluation is
performed with an accuracy of 92.27%. Moreover, we analyzed the relationship
between character classes and font identification accuracy.


  Let k be a global field and let k_v be the completion of k with respect to v,
a non-archimedean place of k. Let \mathbf{G} be a connected, simply-connected
algebraic group over k, which is absolutely almost simple of k_v-rank 1. Let
G=\mathbf{G}(k_v). Let \Gamma be an arithmetic lattice in G and let C=C(\Gamma)
be its congruence kernel. Lubotzky has shown that C is infinite, confirming an
earlier conjecture of Serre. Here we provide complete solution of the
congruence subgroup problem for \Gamm$ by determining the structure of C. It is
shown that C is a free profinite product, one of whose factors is
\hat{F}_{\omega}, the free profinite group on countably many generators. The
most surprising conclusion from our results is that the structure of C depends
only on the characteristic of k. The structure of C is already known for a
number of special cases. Perhaps the most important of these is the
(non-uniform) example \Gamma=SL_2(\mathcal{O}(S)), where \mathcal{O}(S) is the
ring of S-integers in k, with S=\{v\}, which plays a central role in the theory
of Drinfeld modules. The proof makes use of a decomposition theorem of
Lubotzky, arising from the action of \Gamma on the Bruhat-Tits tree associated
with G.


  The fate of the single particle immersed in and interacting with a bath of
other particles localized in a tilted lattice is investigated. For tilt values
comparable to the tunneling rate a slow-down of the dynamics is observed
without, however, a clear localization of the impurity. For large tilt and
strong interactions the motion of the impurity resembles that in the
Kronig-Penney potential. The dynamics depends on the initial distribution of
tilted bosons. It shows delocalized dynamics for a regular, density wave like
distribution and a localization if tilted bosons are randomly distributed.


  We study perfect $2$-coloring of the Johnson graphs $J(n,3)$ associated with
the third largest eigenvalue and symmetric quotient matrix, which exists only
when $n \in \{6, 10\}$. We survey the known constructions in the case $n=6$,
give a new construction for the two known perfect $2$-colorings in the case
$n=10$, and prove that these are the only possible ones.


  We summarize some theoretical issues, which have been considered of special
importance in the discussions of the above working group session.


  From the analysis of more than 92 ks of data obtained with the laxpc
instrument on board Astrosat we have detected a clear high-frequency QPO whose
frequency varies between 67.4 and 72.3 Hz. In the classification of variability
classes of GRS 1915+105, at the start of the observation period the source was
in class omega and at the end the variability was that of class mu: both
classes are characterized by the absence of hard intervals and correspond to
disk-dominated spectra. After normalization to take into account time
variations of the spectral properties as measured by X-ray hardness, the QPO
centroid frequency is observed to vary along the hardness-intensity diagram,
increasing with hardness. We also measure phase lags that indicate that HFQPO
variability at high energies lags that at lower energies and detect systematic
variations with the position on the hardness-intensity diagram. This is the
first time that (small) variations of the HFQPO frequency and lags are observed
to correlate with other properties of the source. We discuss the results in the
framework of existing models, although the small (7%) variability observed is
too small to draw firm conclusions.


  The explosive growth of fake news along with destructive effects on politics,
economy, and public safety has increased the demand for fake news detection.
Fake news on social media does not exist independently in the form of an
article. Many other entities, such as news creators, news subjects, and so on,
exist on social media and have relationships with news articles. Different
entities and relationships can be modeled as a heterogeneous information
network (HIN). In this paper, we attempt to solve the fake news detection
problem with the support of a news-oriented HIN. We propose a novel fake news
detection framework, namely Adversarial Active Learning-based Heterogeneous
Graph Neural Network (AA-HGNN) which employs a novel hierarchical attention
mechanism to perform node representation learning in the HIN. AA-HGNN utilizes
an active learning framework to enhance learning performance, especially when
facing the paucity of labeled data. An adversarial selector will be trained to
query high-value candidates for the active learning framework. When the
adversarial active learning is completed, AA-HGNN detects fake news by
classifying news article nodes. Experiments with two real-world fake news
datasets show that our model can outperform text-based models and other
graph-based models when using less labeled data benefiting from the adversarial
active learning. As a model with generalizability, AA-HGNN also has the ability
to be widely used in other node classification-related applications on
heterogeneous graphs.


  The structure-property relation of nanostructured Al-doped ZnO thin films has
been investigated in detail through a systematic variation of structure and
morphology, with particular emphasis on how they affect optical and electrical
properties. A variety of structures, ranging from compact polycristalline films
to mesoporous, hierarchically organized cluster assemblies, are grown by Pulsed
Laser Deposition at room temperature at different oxygen pressures. We
investigate the dependence of functional properties on structure and morphology
and show how the correlation between electrical and optical properties can be
studied to evaluate energy gap, conduction band effective mass and transport
mechanisms. Understanding these properties opens the way for specific
applications in photovoltaic devices, where optimized combinations of
conductivity, transparency and light scattering are required.


  In this paper we construct the q-analogue of Barnes' Bernoulli numbers and
plynomials of degree 2, which is an answer to a part of Schlosser's question.
Finally, we treat the q-analogue of the sums of powers of consecutive integrs.


  We report the first evidence of a hot corino in a Bok globule. This is based
on the ALMA observations in the 1.2 mm band toward the low-mass Class 0
protostar IRAS 19347+0727 in B335. Saturated complex organic molecules (COMs),
CH$_3$CHO, HCOOCH$_3$, and NH$_2$CHO, are detected in a compact region within a
few 10 au around the protostar. Additionally, CH$_3$OCH$_3$, C$_2$H$_5$OH,
C$_2$H$_5$CN, and CH$_3$COCH$_3$ are tentatively detected. Carbon-chain related
molecules, CCH and c-C$_3$H$_2$, are also found in this source, whose
distributions are extended over a few 100 au scale. On the other hand,
sulfur-bearing molecules CS, SO, and SO$_2$, have both compact and extended
components. Fractional abundances of the COMs relative to H$_2$ are found to be
comparable to those in known hot-corino sources. Though the COMs lines are as
broad as 5-8 km s$^{-1}$, they do not show obvious rotation motion in the
present observation. Thus, the COMs mainly exist in a structure whose
distribution is much smaller than the synthesized beam (0."58 x 0."52).


  Despite the clear performance benefits of data augmentations, little is known
about why they are so effective. In this paper, we disentangle several key
mechanisms through which data augmentations operate. Establishing an exchange
rate between augmented and additional real data, we find that in
out-of-distribution testing scenarios, augmentations which yield samples that
are diverse, but inconsistent with the data distribution can be even more
valuable than additional training data. Moreover, we find that data
augmentations which encourage invariances can be more valuable than invariance
alone, especially on small and medium sized training sets. Following this
observation, we show that augmentations induce additional stochasticity during
training, effectively flattening the loss landscape.


  Galaxies are not in a dynamical steady state. They continually undergo
perturbations, e.g., from infalling dwarf galaxies and dark-matter
substructure. After a dynamical perturbation, stars phase mix towards a new
steady state; in so doing they generally form spiral structures, such as spiral
density waves in galaxy disks and the Gaia Snail observed in the vertical
phase-space density in the solar neighborhood. Structures in phase-space
density can be hard to measure accurately, because spatially varying selection
effects imprint their own patterns on the density. However, stellar labels such
as metallicity, or other element abundances, or stellar masses and ages, can be
measured even in the face of complex or unknown spatial selection functions. We
show that if the equilibrium galaxy has phase-space gradients in these labels,
any perturbation that could raise a spiral wave in the phase-space density will
raise a spiral wave in the distribution of labels as well. We work out the
relationship between the spiral patterns in the density and in the labels. As
an example, we analyze the Gaia Snail and show that its amplitude and dynamical
age as derived from elemental abundances (mainly [Mg/Fe]) follow similar
patterns to those derived from the phase-space density. Our best model dates
the Snail's perturbation to about 400 Myr ago although we find significant
variations with angular momentum in the best-fit age. Conceptually, the ideas
presented here are related to Orbital Torus Imaging, chemical tagging, and
other methods that use stellar labels to trace dynamics.


  In the general classical picture of pebble-based core growth, planetary cores
grow by accretion of single pebble species. The growing planet may reach the
so-called pebble isolation mass, at which it induces a pressure bump that
blocks inward drifting pebbles exterior to its orbit, thereby stalling core
growth by pebble accretion. In recent hydrodynamic simulations, pebble
filtration by the pressure bump depends on several parameters including core
mass, disc structure, turbulent viscosity and pebble size. We investigated how
accretion of multiple, instead of single, pebble species affects core growth
rates, and how the dependence of pebble isolation mass on turbulent viscosity
and pebble size sets the final core masses. We performed numerical simulations
in viscous 1D disc, where maximal grain sizes were regulated by grain growth,
fragmentation and drift limits. We confirm that core growth rates and final
core masses are sensitive to three key parameters: threshold velocity at which
pebbles fragment on collision, turbulent viscosity and distribution of pebble
species, which yield a diversity of planetary cores. With accretion of multiple
pebble species, planetary cores can grow pretty fast, reaching over 30 -- 40
$M_{\rm{E}}$ in mass. Potential cores of cold gas giants were able to form from
embryos initially implanted as far as 50 AU. Our results suggest that accretion
of multi-species pebbles could explain: the estimated 25 -- 45 $M_{\rm{E}}$
heavy elements abundance inside Jupiter's core; massive cores of extrasolar
planets; disc rings and gaps at wider orbits; early and rapid formation of
planetary bodies.


  In this paper, we propose a novel heart segmentation pipeline Combining
Faster R-CNN and U-net Network (CFUN). Due to Faster R-CNN's precise
localization ability and U-net's powerful segmentation ability, CFUN needs only
one-step detection and segmentation inference to get the whole heart
segmentation result, obtaining good results with significantly reduced
computational cost. Besides, CFUN adopts a new loss function based on edge
information named 3D Edge-loss as an auxiliary loss to accelerate the
convergence of training and improve the segmentation results. Extensive
experiments on the public dataset show that CFUN exhibits competitive
segmentation performance in a sharply reduced inference time. Our source code
and the model are publicly available at https://github.com/Wuziyi616/CFUN.


  We discuss the Kondo effect in a spinless two-orbital conduction electron
system coupled with anharmonic Jahn-Teller vibration by employing a numerical
renormalization group technique. When a temperature $T$ is decreased, we
encounter a plateau of $\log 3$ entropy due to quasi-triple degeneracy of local
low-energy states, composed of vibronic ground states and the first excited
state with an excitation energy of $\Delta E$. Around at $T$$\approx$$\Delta
E$, we observe an entropy change from $\log 3$ to $\log 2$. This $\log 2$
entropy originates from the rotational degree of freedom of the vibronic state
and it is eventually released due to the screening by orbital moments of
conduction electrons, leading to the Kondo effect of a Jahn-Teller ion. The
Kondo temperature is explained by the effective $s$-$d$ model with anisotropic
exchange interactions.


  We derive an exact representation of the exchange-correlation energy within
density functional theory (DFT) which spawns a class of approximations leading
to correct long-range asymptotic behavior. In what amounts to be the simplest
approximation, we obtain an electronic structure theory that combines a new
local correlation en-ergy (based on Monte-Carlo calculations applied to the
homogeneous electron gas (HEG)) and a combination of local and explicit
long-ranged exchange. The theory is applied to several 1st row atoms and
diatomic molecules where encouraging results are obtained: a good description
of the chemical bond at the same time allowing for bound anions, reasonably
accurate affinity energies and correct polarizability of an elongated hydrogen
chain. Further stringent tests of DFT are passed: the ratio of ionization
potential and highest orbital energy is close to unity and the atomic charge of
two distant hydrogen atoms under large bias is quantized (integer).


  We present the results of a systematic study of the rest-frame UV
spectroscopic properties of Lyman Break Galaxies (LBGs). The database of almost
1000 LBG spectra proves useful for constructing high S/N composite spectra. The
composite spectrum of the entire sample reveals a wealth of features
attributable to hot stars, HII regions, dust, and outflowing neutral and
ionized gas. By grouping the database according to galaxy parameters such as
Lyman-alpha equivalent width, UV spectral slope, and interstellar kinematics,
we isolate some of the major trends in LBG spectra which are least compromised
by selection effects. We find that LBGs with stronger Lyman-alpha emission have
bluer UV continua, weaker low-ionization interstellar absorption lines, smaller
kinematic offsets between Lyman-alpha and the interstellar absorption lines,
and lower star-formation rates. There is a decoupling between the dependence of
low- and high-ionization outflow features on other spectral properties. Most of
the above trends can be explained in terms of the properties of the large-scale
outflows seen in LBGs. According to this scenario, the appearance of LBG
spectra is determined by a combination of the covering fraction of outflowing
neutral gas which contains dust, and the range of velocities over which this
gas is absorbing. Higher sensitivity and spectral resolution observations are
still required for a full understanding of the covering fraction and velocity
dispersion of the outflowing neutral gas in LBGs, and its relationship to the
escape fraction of Lyman continuum radiation in galaxies at z~3.


  Many countries have passed their first COVID-19 epidemic peak. Traditional
epidemiological models describe this as a result of non-pharmaceutical
interventions that pushed the growth rate below the recovery rate. In this new
phase of the pandemic many countries show an almost linear growth of confirmed
cases for extended time-periods. This new containment regime is hard to explain
by traditional models where infection numbers either grow explosively until
herd immunity is reached, or the epidemic is completely suppressed (zero new
cases). Here we offer an explanation of this puzzling observation based on the
structure of contact networks. We show that for any given transmission rate
there exists a critical number of social contacts, $D_c$, below which linear
growth and low infection prevalence must occur. Above $D_c$ traditional
epidemiological dynamics takes place, as e.g. in SIR-type models. When
calibrating our corresponding model to empirical estimates of the transmission
rate and the number of days being contagious, we find $D_c\sim 7.2$. Assuming
realistic contact networks with a degree of about 5, and assuming that lockdown
measures would reduce that to household-size (about 2.5), we reproduce actual
infection curves with a remarkable precision, without fitting or fine-tuning of
parameters. In particular we compare the US and Austria, as examples for one
country that initially did not impose measures and one that responded with a
severe lockdown early on. Our findings question the applicability of standard
compartmental models to describe the COVID-19 containment phase. The
probability to observe linear growth in these is practically zero.


  A $\Gamma$-magic rectangle set $MRS_{\Gamma}(a, b; c)$ of order $abc$ is a
collection of $c$ arrays $(a\times b)$ whose entries are elements of group
$\Gamma$, each appearing once, with all row sums in every rectangle equal to a
constant $\omega\in \Gamma$ and all column sums in every rectangle equal to a
constant $\delta \in \Gamma$.
  In this paper we prove that for $\{a,b\}\neq\{2^{\alpha},2k+1\}$ where
$\alpha$ and $k$ are some natural numbers, a $\Gamma$-magic rectangle set
MRS$_{\Gamma}(a, b;c)$ exists if and only if $a$ and $b$ are both even or and
$|\Gamma|$ is odd or $\Gamma$ has more than one involution. Moreover we obtain
sufficient and necessary conditions for existence a $\Gamma$-magic rectangle
MRS$_{\Gamma}(a, b)$=MRS$_{\Gamma}(a, b;1)$.


  A lattice Delaunay polytope P is called perfect if its Delaunay sphere is the
only ellipsoid circumscribed about P. We present a new algorithm for finding
perfect Delaunay polytopes. Our method overcomes the major shortcomings of the
previously used method. We have implemented and used our algorithm for finding
perfect Delaunay polytopes in dimensions 6, 7, 8. Our findings lead to a new
conjecture that sheds light on the structure of lattice Delaunay tilings.


  The paper presents the nowdays definition of the phenomenon of cosmic gamma
ray bursts, refers to the main alternative models of their origin and proposes
three promising domains of new observations in the incoming decade.


  The large-scale integration of intermittent renewable energy resources
introduces increased uncertainty and volatility to the supply side of power
systems, thereby complicating system operation and control. Recently,
data-driven approaches, particularly reinforcement learning (RL), have shown
significant promise in addressing complex control challenges in power systems,
because RL can learn from interactive feedback without needing prior knowledge
of the system model. However, the training process of model-free RL methods
relies heavily on random decisions for exploration, which may result in ``bad"
decisions that violate critical safety constraints and lead to catastrophic
control outcomes. Due to the inability of RL methods to theoretically ensure
decision safety in power systems, directly deploying traditional RL algorithms
in the real world is deemed unacceptable. Consequently, the safety issue in RL
applications, known as safe RL, has garnered considerable attention in recent
years, leading to numerous important developments. This paper provides a
comprehensive review of the state-of-the-art safe RL techniques and discusses
how these techniques can be applied to power system control problems such as
frequency regulation, voltage control, and energy management. We then present
discussions on key challenges and future research directions, related to
convergence and optimality, training efficiency, universality, and real-world
deployment.


  This paper studies one-loop effective potential and
spontaneous-symmetry-breaking pattern for SU(5) gauge theory in de Sitter
space-time. Curvature effects modify the flat-space effective potential by
means of a very complicated special function previously derived in the
literature. An algebraic technique already developed by the first author to
study spontaneous symmetry breaking of SU(n) for renormalizable polynomial
potentials is here generalized, for SU(5), to the much harder case of a de
Sitter background. A detailed algebraic and numerical analysis provides a
better derivation of the stability of the extrema in the maximal subgroups
SU(4) x U(1), SU(3) x SU(2) x U(1), SU(3) x U(1) x U(1) x R(311), SU(2) x SU(2)
x U(1) x U(1) x R(2211), where R(311) and R(2211) discrete symmetries select
particular directions in the corresponding two-dimensional strata. One thus
obtains a deeper understanding of the result, previously found with a different
numerical analysis, predicting the slide of the inflationary universe into
either the SU(3) x SU(2) x U(1) or SU(4) x U(1) extremum. Interestingly, using
this approach, one can easily generalize all previous results to a more
complete SU(5) tree-level potential also containing cubic terms.


  In this short Note we would like to bring into the attention of people
working in General Relativity a Schwarzschild like metric found by Professor
Cleopatra Mociu\c{t}chi in sixties. It was obtained by the A. Sommerfeld
reasoning from his treatise "Elektrodynamik" but using instead of the energy
conserving law from the classical Physics, the relativistic energy conserving
law.


  I present here the main results of recent realistic, 3D, hydrodynamical
simulations of convection at the surface of metal-poor red giant stars. I
discuss the application of these convection simulations as time-dependent, 3D,
hydrodynamical model atmospheres to spectral line formation calculations and
abundance analyses. The impact of 3D models on derived elemental abundances is
investigated by means of a differential comparison of the line strengths
predicted in 3D under the assumption of local thermodynamic equilibrium (LTE)
with the results of analogous line formation calculations performed with
classical, 1D, hydrostatic model atmospheres. The low surface temperatures
encountered in the upper photospheric layers of 3D model atmospheres of very
metal-poor stars cause spectral lines of neutral metals and molecules to appear
stronger in 3D than in 1D calculations. Hence, 3D elemental abundances derived
from such lines are significantly lower than estimated by analyses with 1D
models. In particular, differential 3D$-$1D LTE abundances for C, N, and O
derived from CH, NH, and OH lines are found to be in the range -0.5 to -1 dex.
Large negative differential 3D-1D corrections to the Fe abundance are also
computed for weak low-excitation neutral Fe lines. The application of
metal-poor 3D models to the spectroscopic analysis of extremely iron-poor halo
stars is discussed.


  The nature of boundedness of orbits of a particle moving in a central force
field is investigated. General conditions for circular orbits and their
stability are discussed. In a bounded central field orbit, a particle moves
clockwise or anticlockwise, depending on its angular momentum, and at the same
time oscillates between a minimum and a maximum radial distance, defining an
inner and an outer annulus. There are generic orbits suggested in popular texts
displaying the general features of a central orbit. In this work it is
demonstrated that some of these orbits, seemingly possible at the first glance,
are not compatible with a central force field. For power law forces, the
general nature of boundedness and geometric shape of orbits are investigated.


  We present an expansion of FLEET, a machine learning algorithm optimized to
select transients that are most likely to be tidal disruption events (TDEs).
FLEET is based on a random forest algorithm trained on the light curves and
host galaxy information of 4,779 spectroscopically classified transients. For
transients with a probability of being a TDE, \ptde$>0.5$, we can successfully
recover TDEs with a $\approx40$\% completeness and a $\approx30$\% purity when
using the first 20 days of photometry, or a similar completeness and
$\approx50$\% purity when including 40 days of photometry. We find that the
most relevant features for differentiating TDEs from other transients are the
normalized host separation, and the light curve $(g-r)$ color during peak.
Additionally, we use FLEET to produce a list of the 39 most likely TDE
candidates discovered by the Zwicky Transient Facility that remain currently
unclassified. We explore the use of FLEET for the Legacy Survey of Space and
Time on the Vera C. Rubin Observatory (\textit{Rubin}) and the \textit{Nancy
Grace Roman Space Telescope} (\textit{Roman}). We simulate the \textit{Rubin}
and \textit{Roman} survey strategies and estimate that $\sim 10^4$ TDEs could
be discovered every year by \textit{Rubin}, and $\sim200$ TDEs per year by
\textit{Roman}. Finally, we run FLEET on the TDEs in our \textit{Rubin} survey
simulation and find that we can recover $\sim 30$\% of those at a redshift $z
<0.5$ with \ptde$>0.5$. This translates to $\sim3,000$ TDEs per year that FLEET
could uncover from \textit{Rubin}. FLEET is provided as a open source package
on GitHub https://github.com/gmzsebastian/FLEET


  We study the photo-excitation dynamics of correlated band insulators, using
non-equilibrium dynamical mean-field theory for the ionic Hubbard model. We
find two distinct behaviors, depending on the ratio of the on-site interaction
$U$ and the bare band gap $\Delta$. For small interactions, the relaxation is
characterized by intra-band carrier scattering in relatively rigid bands,
leading to a non-thermal intermediate state with separate thermal distributions
of electrons and holes. This behavior can be viewed as typical for a band
insulator with weak interactions. For larger interaction, on the other hand, we
observe a strong modification of the electronic spectrum and a filling-in of
the gap after photo-excitation, along with a rapid thermalization of the
system. The two behaviors therefore provide a dynamical distinction of a
correlated band insulator and a band-insulator, which can differ even when the
spectra of the two systems are similar in equilibrium. The crossover happens
when the interaction $U$ is comparable to $\Delta$.


  In this paper the internal structure of a neutron star is shown to be
inferrable from its gravitational-wave spectrum. Iteratively applying the
inverse scheme of the scaled coordinate logarithmic perturbation method for
neutron stars proposed by Tsui and Leung [Astrophys. J. {\bf 631}, 495 (2005)],
we are able to determine the mass, the radius and the mass distribution of a
star from its quasi-normal mode frequencies of stellar pulsation. In addition,
accurate equation of state of nuclear matter can be obtained from such
inversion scheme. Explicit formulas for the case of axial $w$-mode oscillation
are derived here and numerical results for neutron stars characterized by
different equations of state are shown.


  This paper discusses the synthesis, characterization, and comprehensive study
of Ba-122 single crystals with various substitutions and various $T_c$. The
paper uses five complementary techniques to obtain a self-consistent set of
data on the superconducting properties of Ba-122. A major conclusion of the
authors work is the coexistence of two superconducting condensates differing in
the electron-boson coupling strength. The two gaps that develop in distinct
Fermi surface sheets are nodeless in the $k_xk_y$-plane and exhibit s-wave
symmetry, the two-band model represents a sufficient data description tool. A
moderate interband coupling and a considerable Coulomb repulsion in the
description of the two-gap superconducting state of barium pnictides favor the
$s^{++}$-model.


  The classical matrix-tree theorem discovered by G.Kirchhoff in 1847 relates
the principal minor of the nxn Laplace matrix to a particular sum of monomials
of matrix elements indexed by directed trees with n vertices and a single sink.
In this paper we consider a generalization of this statement: for any k \ge n
we define a degree k polynomial det_{n,k} of matrix elements and prove that
this polynomial applied to the Laplace matrix gives a sum of monomials indexed
by acyclic graphs with n vertices and k edges.


  A supremum-of-quadratics representation for convex barrier-type constraints
is developed and applied within the context of a class of continuous time state
constrained linear regulator problems. Using this representation, it is shown
that a linear regulator problem subjected to such a convex barrier-type
constraint can be equivalently formulated as an unconstrained two-player linear
quadratic game. By demonstrating equivalence of the upper and lower values of
this game, state feedback characterizations for the optimal policies of both
players are developed. These characterizations are subsequently illustrated by
example.


  OPERA (\emph{O}scillation \emph{P}roject with \emph{E}mulsion t\emph{R}acking
\emph{A}pparatus) is a long-baseline neutrino experiment, designed to provide
the first direct proof of $\nu_\mu \to \nu_\tau$ oscillation in the atmospheric
sector using the \emph{C}ERN \emph{N}eutrinos to \emph{G}ran \emph{S}asso
(CNGS) $\nu_\mu$ beam. The detector, consisting of a modular target made of
lead - nuclear emulsion units complemented by electronic trackers and muon
spectrometers, has been conceived to select $\rm{\nu_\tau}$ charged current
interactions, among all neutrino flavour events, through the observation of the
outcoming tau leptons and subsequent decays. In this paper, the detector, the
event analysis chain and the preliminary results from the first OPERA physics
run are reported.


  We study existence and structure of $P-$area minimizing surfaces in the
Heisenberg group under Dirichlet and Neumann boundary conditions. We show that
there exists an underlying vector field $N$ that characterized existence and
structure of $P$-area minimizing surfaces. This vector field exists even if
there is no $P$-area minimizing surface satisfying the prescribed boundary
conditions. We prove that if $\partial \Omega$ satisfies a so called Barrier
condition, it is sufficient to guarantee existence of such surfaces. Our
approach is completely different from previous methods in the literature and
makes major progress in understanding existence of $P$-area minimizing
surfaces.


  Precise and, if possible, accurate characterization of exoplanets cannot be
dissociated from the characterization of their host stars. In this chapter we
discuss different methods and techniques used to derive fundamental properties
and atmospheric parameters of exoplanet-host stars. The main limitations,
advantages and disadvantages, as well as corresponding typical measurement
uncertainties of each method are presented.


  Recent studies found that many channels are affected by additive noise that
is impulsive in nature and is best explained by heavy-tailed symmetric
alpha-stable distributions. Dealing with impulsive noise environments comes
with an added complexity with respect to the standard Gaussian environment: the
alpha-stable probability density functions have an infinite second moment and
the "nice" Hilbert space structure of the space of random variables having a
finite second moment is lost along with its tools and methodologies. This is
indeed the case in estimation theory where classical tools to quantify
performance of an estimator are tightly related to the assumption of finite
variance variables. In alpha-stable environments, expressions such as the mean
square error and the Cramer-Rao bound are hence problematic. In this work, we
tackle the parameter estimation problem in impulsive noise environments and
develop novel tools that are tailored to the alpha-stable and heavy-tailed
noise environments, tools that coincide with the standard ones adopted in the
Gaussian setup, namely a generalized "power" measure and a generalized Fisher
information. We generalize known information inequalities commonly used in the
Gaussian context: the de Bruijn's identity, the data processing inequality, the
Fisher information inequality, the isoperimetric inequality for entropies and
the Cramer-Rao bound. Additionally, we derive upper bounds on the differential
entropy of independent sums having a stable component. Finally, the new "power"
measure is used to shed some light on the additive alpha-stable noise channel
capacity in a setup that generalizes the linear average power constrained AWGN
channel. Our theoretical findings are paralleled with numerical evaluations of
various quantities and bounds using developed {\em Matlab} packages.


  We examine charge transport through a system of three sites connected in
series in the situation when an oscillating charged piston modulates the energy
of the middle site. We show that with an appropriate set of parameters, charge
can be transferred against an applied voltage. In this scenario, when the
oscillating piston shifts away from the middle site, the energy of the site
decreases and it is populated by a charge transferred from the lower energy
site. On the other hand, when the piston returns to close proximity, the energy
of the middle site increases and it is depopulated by the higher energy site.
Thus through this process, the charge is pumped against the potential gradient.
Our results can explain the process of proton pumping in one of the
mitochondrial enzymes, Complex I. Moreover, this mechanism can be used for
electron pumping in semiconductor nanostructures.


  Incremental learning represents a crucial task in aerial image processing,
especially given the limited availability of large-scale annotated datasets. A
major issue concerning current deep neural architectures is known as
catastrophic forgetting, namely the inability to faithfully maintain past
knowledge once a new set of data is provided for retraining. Over the years,
several techniques have been proposed to mitigate this problem for image
classification and object detection. However, only recently the focus has
shifted towards more complex downstream tasks such as instance or semantic
segmentation. Starting from incremental-class learning for semantic
segmentation tasks, our goal is to adapt this strategy to the aerial domain,
exploiting a peculiar feature that differentiates it from natural images,
namely the orientation. In addition to the standard knowledge distillation
approach, we propose a contrastive regularization, where any given input is
compared with its augmented version (i.e. flipping and rotations) in order to
minimize the difference between the segmentation features produced by both
inputs. We show the effectiveness of our solution on the Potsdam dataset,
outperforming the incremental baseline in every test. Code available at:
https://github.com/edornd/contrastive-distillation.


  The influence of periodic shear deformation on nonaffine atomic displacements
in an amorphous solid is examined via molecular dynamics simulations. We study
the three-dimensional Kob-Andersen binary mixture model at a finite
temperature. It is found that when the material is periodically strained, most
of the atoms undergo repetitive nonaffine displacements with amplitudes that
are broadly distributed. We show that particles with large amplitudes of
nonaffine displacements are organized into compact clusters. With increasing
strain amplitude, spatial correlations of nonaffine displacements become
increasingly long-ranged, although they remain present even in a quiescent
system due to thermal fluctuations.


  Three-dimensional (3D) image cytometers may significantly improve the cell
analysis accuracy to facilitate biological discoveries and clinical diagnosis,
but their development is curbed by the low imaging throughput. Here we report
SIngle-frame LAbel-free Cell Tomography (SILACT) with diffraction-limited
resolution and unprecedented imaging speed of over 10,000 volumes/second.
SILACT is built on a unique interferometric microscope with angle-multiplexing
illumination and a pre-trained physics-incorporating Deep Neural Network for
efficient 3D Refractive Index (RI) reconstruction, from which 3D morphological
and biophysical parameters of cells are extracted. With microfluidics and a
high-speed camera, SILACT is capable of imaging over 20,000 cells/second and
distinguishing different cell species during rapid measurements of large cell
quantities, as well as visualizing shear-induced 3D transient deformation of
red blood cells on a sub-millisecond scale.


  We perform model independent and model dependent analyses of solar neutrino
data including the neutral current event rate from SNO. The inclusion of the
first SNO NC data in the model independent analysis determines the allowed
ranges of $^{8}{B}$ flux normalisation and the $\nu_e$ survival probability
more precisely than what was possible from the SK and SNO CC combination. We
perform global $\nu_e-\nu_{active}$ oscillation analyses of solar neutrino data
using the NC rate instead of the SSM prediction for the $^{8}{B}$ flux, in view
of the large uncertainty in the latter. The LMA gives the best solution, while
the LOW solution is allowed only at the $3\sigma$ level.


  We prove the convergence of an implicit time discretization for the one-phase
Mullins-Sekerka equation, possibly with additional non-local repulsion,
proposed in [F. Otto, Arch. Rational Mech. Anal. 141 (1998) 63--103]. Our
simple argument shows that the limit satisfies the equation in a distributional
sense as well as an optimal energy-dissipation relation. The proof combines
arguments from optimal transport, gradient flows & minimizing movements, and
basic geometric measure theory.


  Deep Q-Learning has been successfully applied to a wide variety of tasks in
the past several years. However, the architecture of the vanilla Deep Q-Network
is not suited to deal with partially observable environments such as 3D video
games. For this, recurrent layers have been added to the Deep Q-Network in
order to allow it to handle past dependencies. We here use Minecraft for its
customization advantages and design two very simple missions that can be frames
as Partially Observable Markov Decision Process. We compare on these missions
the Deep Q-Network and the Deep Recurrent Q-Network in order to see if the
latter, which is trickier and longer to train, is always the best architecture
when the agent has to deal with partial observability.


  There are two important, and potentially interconnecting, avenues to the
realisation of large-scale quantum algorithms: improvement of the hardware, and
reduction of resource requirements demanded by algorithm components. In
focusing on the latter, one crucial subroutine to many sought-after
applications is the quantum adder. A variety of different implementations exist
with idiosyncratic pros and cons. One of these, the Draper quantum Fourier
adder, offers the lowest qubit count of any adder, but requires a substantial
number of gates as well as extremely fine rotations. In this work, we present a
modification of the Draper adder which eliminates small-angle rotations to
highly coarse levels, matched with some strategic corrections. This reduces
hardware requirements without sacrificing the qubit saving. We show that the
inherited loss of fidelity is directly given by the rate of carry and borrow
bits in the computation. We derive formulae to predict this, complemented by
complete gate-level matrix product state simulations of the circuit. Moreover,
we analytically describe the effects of possible stochastic control error. We
present an in-depth analysis of this approach in the context of Shor's
algorithm, focusing on the factoring of RSA-2048. Surprisingly, we find that
each of the $7\times 10^7$ quantum Fourier transforms may be truncated down to
$\pi/64$, with additive rotations left only slightly finer. This result is much
more efficient than previously realised. We quantify savings both in terms of
logical resources and raw magic states, demonstrating that phase adders can be
competitive with Toffoli-based constructions.