  The coronavirus disease 2019 (COVID-19) continues to have a negative impact
on healthcare systems around the world, though the vaccines have been developed
and national vaccination coverage rate is steadily increasing. At the current
stage, automatically segmenting the lung infection area from CT images is
essential for the diagnosis and treatment of COVID-19. Thanks to the
development of deep learning technology, some deep learning solutions for lung
infection segmentation have been proposed. However, due to the scattered
distribution, complex background interference and blurred boundaries, the
accuracy and completeness of the existing models are still unsatisfactory. To
this end, we propose a boundary guided semantic learning network (BSNet) in
this paper. On the one hand, the dual-branch semantic enhancement module that
combines the top-level semantic preservation and progressive semantic
integration is designed to model the complementary relationship between
different high-level features, thereby promoting the generation of more
complete segmentation results. On the other hand, the mirror-symmetric boundary
guidance module is proposed to accurately detect the boundaries of the lesion
regions in a mirror-symmetric way. Experiments on the publicly available
dataset demonstrate that our BSNet outperforms the existing state-of-the-art
competitors and achieves a real-time inference speed of 44 FPS.


  Squeezing of quantum fluctuations by means of entanglement is a well
recognized goal in the field of quantum information science and precision
measurements. In particular, squeezing the fluctuations via entanglement
between two-level atoms can improve the precision of sensing, clocks,
metrology, and spectroscopy. Here, we demonstrate 3.4 dB of metrologically
relevant squeezing and entanglement for ~ 10^5 cold cesium atoms via a quantum
nondemolition (QND) measurement on the atom clock levels. We show that there is
an optimal degree of decoherence induced by the quantum measurement which
maximizes the generated entanglement. A two-color QND scheme used in this paper
is shown to have a number of advantages for entanglement generation as compared
to a single color QND measurement.


  Quantum Error Mitigation (EM) is a collection of strategies to reduce errors
on noisy intermediate scale quantum (NISQ) devices on which proper quantum
error correction is not feasible. One of such strategies aimed at mitigating
noise effects of a known environment is to realise the inverse map of the noise
using a set of completely positive maps weighted by a quasi-probability
distribution, i.e. a probability distribution with positive and negative
values. This quasi-probability distribution is realised using classical
post-processing after final measurements of the desired observables have been
made. Here we make a connection with quasi-probability EM and recent results
from quantum trajectory theory for open quantum systems. We show that the
inverse of noise maps can be realised by performing classical post-processing
on the quantum trajectories generated by an additional reservoir with a
quasi-probability measure called the influence martingale. We demonstrate our
result on a model relevant for current NISQ devices. Finally, we show the
quantum trajectories required for error correction can themselves be simulated
by coupling an ancillary qubit to the system. In this way, we can avoid the
introduction of the engineered reservoir.


  We report the results of a study of X-ray point sources coincident with the
High Velocity System (HVS) projected in front of NGC 1275. A very deep X-ray
image of the core of the Perseus cluster made with the Chandra Observatory has
been used. We find a population of Ultra-Luminous X-ray sources (ULX; 7 sources
with LX [0.5-7 keV] > 7x10^39 erg/s). As with the ULX populations in the
Antennae and Cartwheel galaxies, those in the HVS are associated with a region
of very active star formation. Several sources have possible optical
counterparts found on HST images, although the X-ray brightest one does not.
Absorbed power-law models fit the X-ray spectra, with most having a photon
index between 2 and 3.


  A large body of theoretical and computational work shows that jets - modelled
as magnetized disk winds - exert an external torque on their underlying disks
that can efficiently remove angular momentum and act as major drivers of disk
accretion. These predictions have recently been confirmed in direct HST
measurements of the jet rotation and angular momentum transport in low mass
protostellar systems. We review the theory of disc winds and show that their
physics is universal and scales to jets from both low and high mass star
forming regions. This explains the observed properties of outflows in massive
star forming regions, before the central massive star generates an ultracompact
HII region. We also discuss the recent numerical studies on the formation of
massive accretion disks and outflows through gravitational collapse, including
our own work on 3D Adaptive Mesh simulations (using the FLASH code) of the
hydromagnetic collapse of an initial rotating, and cooling Bonner-Ebert sphere.
Magnetized collapse gives rise to outflows. Our own simulations show that both
a jet-like disk wind on sub AU scales, and a larger scale molecular outflow
occur (Banerjee and Pudritz 2005).


  An integral representation of solutions of the wave equation as a
superposition of other solutions of this equation is built. The solutions from
a wide class can be used as building blocks for the representation.
Considerations are based on mathematical techniques of continuous wavelet
analysis. The formulas obtained are justified from the point of view of
distribution theory. A comparison of the results with those by G. Kaiser is
carried out. Methods of obtaining physical wavelets are discussed.


  Using Monte-Carlo simulations of X-ray flare distributions across the
accretion disk of active galactic nuclei (AGN), we obtain modeling results for
the energy-dependent fractional variability amplitude. Referring to previous
results of this model, we illustrate the relation between the shape of the
point-to-point fractional variability spectrum, F_pp, and the time-integrated
spectral energy distribution, F_E. The results confirm that the spectral shape
and variability of the iron Kalpha line are dominated by the flares closest to
the disk center.


  Motivated by the recent observations of nodeless superconductivity in the
monolayer CuO$_{2}$ grown on the Bi$_{2}$Sr$_{2}$CaCu$_{2}$O$_{8+\delta }$
substrates, we study the two-dimensional superconducting (SC) phases described
by the two-dimensional $t$-$J$ model in proximity to an antiferromagnetic (AF)
insulator. We found that (i) the nodal d-wave SC state can be driven via a
continuous transition into a nodeless d-wave pairing state by the proximity
induced AF field. (ii) The energetically favorable pairing states in the strong
field regime have extended s-wave symmetry and can be nodal or nodeless. (iii)
Between the pure d-wave and s-wave paired phases, there emerge two
topologically distinct SC phases with ($s+$i$d$) symmetry, i.e., the weak and
strong pairing phases, and the weak pairing phase is found to be a $Z_{2}$
topological superconductor protected by valley symmetry, exhibiting robust
gapless non-chiral edge modes. These findings strongly suggest that the
high-$T_{c}$ superconductors in proximity to antiferromagnets can realize fully
gapped symmetry protected topological SC.


  How does the submm galaxy population detected by SCUBA fit into galaxy
evolution? How do these rare starbursting systems, which contribute
significantly to high redshift star-formation, relate to other galaxy
populations? Deep radio observations have been most useful for studying these
systems, but still leave a significant fraction of the population unidentified.
Now with the deep IRAC and MIPS images from the GOODS Spitzer Legacy program
and a re-analysis of the deep radio data, we are able to identify counterparts
for a large fraction of SCUBA galaxies in GOODS-N. All of these counterparts
are detected by Spitzer. Given the vast multi-wavelength data in this field, we
can study the spectral energy distributions (SEDs) of these systems and
determine what is fueling their intense infrared luminosities. A rest-frame
composite optical-to-radio SED for all spectroscopically identified submm
sources shows that the average SCUBA galaxy is consistent with models of
ultraluminous starburst galaxies, although cooler than those observed locally.
Because of this, the submm flux alone consistently overestimates IR when using
spectral templates which obey the local ULIRG temperature-luminosity relation.
The wide range of 24/850 micron flux ratios as a function of redshift indicates
the presence of strong mid-IR features, to be confirmed with deep IRS
spectroscopy. The IRAC colours of the submm systems provide useful redshift
constraints, since, at these redshifts, IRAC samples the stellar bump. The
Spitzer photometry of this large sample of submm galaxies has allowed us to put
constraints on many of the outstanding issues in submm astronomy.


  A prominent tool in many problems involving metric spaces is a notion of
randomized low-diameter decomposition. Loosely speaking, $\beta$-decomposition
refers to a probability distribution over partitions of the metric into sets of
low diameter, such that nearby points (parameterized by $\beta>0$) are likely
to be "clustered" together. Applying this notion to the shortest-path metric in
edge-weighted graphs, it is known that $n$-vertex graphs admit an $O(\ln
n)$-padded decomposition (Bartal, 1996), and that excluded-minor graphs admit
$O(1)$-padded decomposition (Klein, Plotkin and Rao 1993, Fakcharoenphol and
Talwar 2003, Abraham et al. 2014).
  We design decompositions to the family of $p$-path-separable graphs, which
was defined by Abraham and Gavoille (2006). and refers to graphs that admit
vertex-separators consisting of at most $p$ shortest paths in the graph.
  Our main result is that every $p$-path-separable $n$-vertex graph admits an
$O(\ln (p \ln n))$-decomposition, which refines the $O(\ln n)$ bound for
general graphs, and provides new bounds for families like bounded-treewidth
graphs. Technically, our clustering process differs from previous ones by
working in (the shortest-path metric of) carefully chosen subgraphs.


  We introduce a simple model to describe the interplay between specific and
non-specific interactions. We study the influence of various physical factors
on the static and dynamic properties of the specific interactions of our model
and show that contrary to intuitive expectations, non-specific interactions can
assist in the formation of specific complexes and increase their stability. We
then discuss the relevance of these results for biological systems.


  We study finite but growing principal square submatrices $A_n$ of the one- or
two-sided infinite Fibonacci Hamiltonian $A$. Our results show that such a
sequence $(A_n)$, no matter how the points of truncation are chosen, is always
stable -- implying that $A_n$ is invertible for sufficiently large $n$ and
$A_n^{-1}\to A^{-1}$ pointwise.


  In this paper we extend the boundary string field theory action for a non-BPS
D-brane to the one including the target space fermions and the nonlinear
supersymmetry with 32 supercharges up to some order. This is based on the idea
that the vacuum with a non-BPS D-brane belongs to the spontaneously broken
phase of the supersymmetry. As a result, we find that the action is almost
uniquely determined up to the field redefinition ambiguities.


  We give bounds on the distribution and fragmentation functions that appear at
leading order in deep inelastic 1-particle inclusive leptoproduction or in
Drell-Yan processes. These bounds simply follow from positivity of the defining
matrix elements and are an important guidance in estimating the magnitude of
the azimuthal and spin asymmetries in these processes.


  Using the logarithmic superfluid model of physical vacuum, one can formulate
a quantum theory, which successfully recovers Einstein's theory of relativity
in low-momenta limit, but otherwise has different foundations and predictions.
We present an analytical example of the dispersion relation and argue that it
should have a Landau "roton" form which ensures the suppression of dissipative
fluctuations. We show that at small momenta, a dispersion relation becomes
relativistic with small deformations, such that a photon acquires effective
mass, but a much more complex picture arises at large momenta.


  Signals are a classical tool used in cellular automata constructions that
proved to be useful for language recognition or firing-squad synchronisation.
Particles and collisions formalize this idea one step further, describing
regular nets of colliding signals. In the present paper, we investigate the use
of particles and collisions for constructions involving an infinite number of
interacting particles. We obtain a high-level construction for a new smallest
intrinsically universal cellular automaton with 4 states.


  We demonstrate the broadband operation of a switchable terahertz quarter-wave
plate achieved with an active metasurface employing vanadium dioxide. For this
purpose, we utilize anisotropically deformed checkerboard structures, which
present broadband characteristics compatible with deep modulation. Moreover,
the metasurface is integrated with a current injection circuit to achieve state
switching; this injection circuit can also be employed to monitor the electric
state of vanadium dioxide. We estimate the Stokes parameters derived from the
experimental transmission spectra of the fabricated metasurface and confirm the
helicity switching of circularly polarized waves near a designed frequency of
0.66THz. The relative bandwidth is evaluated as 0.52, which is 4.2 times
broader than that in a previous study.


  We prove that for $C^1$ generic diffeomorphisms, every expansive homoclinic
class is hyperbolic.


  This paper develops a generalized scalar auxiliary variable (SAV) method for
the time-dependent Ginzburg-Landau equations. The backward Euler is used for
discretizing the temporal derivative of the time-dependent Ginzburg-Landau
equations. In this method, the system is decoupled and linearized to avoid
solving the non-linear equation at each step. The theoretical analysis proves
that the generalized SAV method can preserve the maximum bound principle and
energy stability, which is confirmed by the numerical results. It shows that
the numerical algorithm is stable.


  We present deep radio images at 1.4 GHz of a large and complete sample of BL
Lacertae objects (BL Lacs) selected from the Deep X-ray Radio Blazar Survey
(DXRBS). We have observed 24 northern sources with the Very Large Array (VLA)
in both its A and C configurations and 15 southern sources with the Australia
Telescope Compact Array (ATCA) in its largest configuration. We find that in
the DXRBS, as in the 1-Jy survey, which has a radio flux limit roughly ten
times higher than the DXRBS, a considerable number (about a third) of BL Lacs
can be identified with the relativistically beamed counterparts of
Fanaroff-Riley type II (FR II) radio galaxies. We attribute the existence of FR
II-BL Lacs, which is not accounted for by current unified schemes, to an
inconsistency in our classification scheme for radio-loud active galactic
nuclei (AGN). Taking the extended radio power as a suitable measure of
intrinsic jet power, we find similar average values for low- (LBL) and
high-energy peaked BL Lacs (HBL), contrary to the predictions of the blazar
sequence.


  Self-Supervised Learning (SSL) methods such as VICReg, Barlow Twins or W-MSE
avoid collapse of their joint embedding architectures by constraining or
regularizing the covariance matrix of their projector's output. This study
highlights important properties of such strategy, which we coin
Variance-Covariance regularization (VCReg). More precisely, we show that {\em
VCReg combined to a MLP projector enforces pairwise independence between the
features of the learned representation}. This result emerges by bridging VCReg
applied on the projector's output to kernel independence criteria applied on
the projector's input. We empirically validate our findings where (i) we put in
evidence which projector's characteristics favor pairwise independence, (ii) we
demonstrate pairwise independence to be beneficial for out-of-domain
generalization, (iii) we demonstrate that the scope of VCReg goes beyond SSL by
using it to solve Independent Component Analysis. This provides the first
theoretical motivation and explanation of MLP projectors in SSL.


  Despite the recent success of automatic metrics for assessing translation
quality, their application in evaluating the quality of machine-translated
chats has been limited. Unlike more structured texts like news, chat
conversations are often unstructured, short, and heavily reliant on contextual
information. This poses questions about the reliability of existing
sentence-level metrics in this domain as well as the role of context in
assessing the translation quality. Motivated by this, we conduct a
meta-evaluation of existing sentence-level automatic metrics, primarily
designed for structured domains such as news, to assess the quality of
machine-translated chats. We find that reference-free metrics lag behind
reference-based ones, especially when evaluating translation quality in
out-of-English settings. We then investigate how incorporating conversational
contextual information in these metrics affects their performance. Our findings
show that augmenting neural learned metrics with contextual information helps
improve correlation with human judgments in the reference-free scenario and
when evaluating translations in out-of-English settings. Finally, we propose a
new evaluation metric, Context-MQM, that utilizes bilingual context with a
large language model (LLM) and further validate that adding context helps even
for LLM-based evaluation metrics.


  In the paper "Geometry of polynomial mapping at infinity via intersection
homology" the second and third authors associated to a given polynomial mapping
$F : \C^2 \to \C^2$ with nonvanishing jacobian a variety whose homology or
intersection homology describes the geometry of singularities at infinity of
the mapping. We generalize this result.


  We study the dilaton action induced by RG flows between holographic CFT fixed
points. For this purpose we introduce a general bulk effective theory for the
goldstone boson of the broken spacetime symmetry, providing an AdS analog of
the EFT of Inflation. In two dimensions, we use the effective theory to compute
the dilaton action, as well as the UV and IR conformal anomalies, without
further assumptions. In higher dimensions we take a `slow-flow' limit analogous
to the assumption of slow-roll in Inflation, and in this context we obtain the
dilaton action, focusing on terms proportional to the difference of the A-type
anomalies. We include Gauss-Bonnet terms in the gravitational action in order
to verify that our method correctly differentiates between A-type and other
anomalies.


  It has recently been suggested that exchange spring media offer a way to
increase media density without causing thermal instability
(superparamagnetism), by using a hard and a soft layer coupled by exchange.
Victora has suggested a figure of merit xi = 2 E_b/mu_0 m_s H_sw, the ratio of
the energy barrier to that of a Stoner-Wohlfarth system with the same switching
field, which is 1 for a Stoner-Wohlfarth (coherently switching) particle and 2
for an optimal two-layer composite medium. A number of theoretical approaches
have been used for this problem (e.g., various numbers of coupled
Stoner-Wohlfarth layers and continuum micromagnetics). In this paper we show
that many of these approaches can be regarded as special cases or
approximations to a variational formulation of the problem, in which the energy
is minimized for fixed magnetization. The results can be easily visualized in
terms of a plot of the energy as a function of magnetic moment m_z, in which
both the switching field [the maximum slope of E(m_z)] and the stability
(determined by the energy barrier E_b) are geometrically visible. In this
formulation we can prove a rigorous limit on the figure of merit xi, which can
be no higher than 4. We also show that a quadratic anistropy suggested by Suess
et al comes very close to this limit.


  Following ideas of Kedlaya-Liu, we are going to consider extending our
previous work to the context of more general adic spaces, which will be
corresponding deformation of the relative $p$-adic Hodge structure over more
general adic spaces. This means that the deformation could be also realized by
an adic spaces (perfectoid, preperfectoid, relatively perfectoid and so on).
Parts of the whole project here actually are inspired by the corresponding
Drinfeld's lemma for diamonds after Scholze, as well as the work from
Carter-Kedlaya-Z\'abr\'adi which is aimed at studying the representation theory
of products of \'etale fundamental groups. Moreover, we gain motivations from
noncommutative analytic geometries and noncommutative Tamagawa number
conjectures.


  In this work we propose the design principles behind the development of a
smart application utilized by mobile devices in order to control the spread of
SARS-CoV-2 coronavirus disease that caused the COVID-19 pandemic. Through the
deployment of this application utilizing their Bluetooth enabled devices,
individuals may keep track of their close contacts, and if nearby contacts
using the same application are reported later as infected the proximate
individual is informed in order to be quarantined for a short of time,
preventing hence the spread of the virus. Through the latest year, there have
been developed several applications in the Google Play Store that can be
deployed by smart devices utilizing their Bluetooth connectivity for the nearby
device tracking. However, in this work we propose an open architecture for the
development of such applications, that also incorporates a more elaborated
graph-theoretic and algorithmic background regarding the contact tracing. The
proposed contact tracing algorithm, that can be embedded in the deployment of
the application, provides a more immediate tracking of the contacts of an
infected individuals, providing a wider extent in the tracing of the contacts,
leading hence to a more immediate mitigation of the epidemic.


  We present the calculation of the decay width of the Z-boson into three jets
including complete quark mass effects to second order in the strong coupling
constant. The study is done for different jet clustering algorithms such as EM,
JADE, E and DURHAM. Because three-jet observables are very sensitive to the
quark mass we consider the possibility of extracting the bottom quark mass from
LEP data.


  Using data from the WISE mission, we have measured near infra-red (NIR)
photometry of a diverse sample of dust-free stellar systems (globular clusters,
dwarf and giant early-type galaxies) which have metallicities that span the
range -2.2 < [Fe/H] (dex) < 0.3. This dramatically increases the sample size
and broadens the metallicity regime over which the 3.4 (W1) and 4.6 micron (W2)
photometry of stellar populations have been examined.
  We find that the W1 - W2 colors of intermediate and old (> 2 Gyr) stellar
populations are insensitive to the age of the stellar population, but that the
W1 - W2 colors become bluer with increasing metallicity, a trend not well
reproduced by most stellar population synthesis (SPS) models. In common with
previous studies, we attribute this behavior to the increasing strength of the
CO absorption feature located in the 4.6 micron bandpass with metallicity.
  Having used our sample to validate the efficacy of some of the SPS models, we
use these models to derive stellar mass-to-light ratios in the W1 and W2 bands.
Utilizing observational data from the SAURON and ATLAS3D surveys, we
demonstrate that these bands provide extremely simple, yet robust stellar mass
tracers for dust free older stellar populations that are freed from many of the
uncertainties common among optical estimators.


  Kepler photometry has revealed two unusual transiting companions orbiting an
early A-star and a late B-star. In both cases the occultation of the companion
is deeper than the transit. The occultation and transit with follow-up optical
spectroscopy reveal a 9400 K early A-star, KOI-74 (KIC 6889235), with a
companion in a 5.2 day orbit with a radius of 0.08 Rsun and a 10000 K late
B-star KOI-81 (KIC 8823868) that has a companion in a 24 day orbit with a
radius of 0.2 Rsun. We infer a temperature of 12250 K for KOI-74b and 13500 K
for KOI-81b.
  We present 43 days of high duty cycle, 30 minute cadence photometry, with
models demonstrating the intriguing properties of these object, and speculate
on their nature.


  Reinforcement learning has a rich history in neuroscience, from early work on
dopamine as a reward prediction error signal for temporal difference learning
(Schultz et al., 1997) to recent work suggesting that dopamine could implement
a form of 'distributional reinforcement learning' popularized in deep learning
(Dabney et al., 2020). Throughout this literature, there has been a tight link
between theoretical advances in reinforcement learning and neuroscientific
experiments and findings. As a result, the theories describing our experimental
data have become increasingly complex and difficult to navigate. In this
review, we cover the basic theory underlying classical work in reinforcement
learning and build up to an introductory overview of methods in modern deep
reinforcement learning that have found applications in systems neuroscience. We
start with an overview of the reinforcement learning problem and classical
temporal difference algorithms, followed by a discussion of 'model-free' and
'model-based' reinforcement learning together with methods such as DYNA and
successor representations that fall in between these two extremes. Throughout
these sections, we highlight the close parallels between such machine learning
methods and related work in both experimental and theoretical neuroscience. We
then provide an introduction to deep reinforcement learning with examples of
how these methods have been used to model different learning phenomena in
systems neuroscience, such as meta-reinforcement learning (Wang et al., 2018)
and distributional reinforcement learning (Dabney et al., 2020). Code that
implements the methods discussed in this work and generates the figures is also
provided.


  The classifying diagram was defined by Rezk and is a generalization of the
nerve of a category; in contrast to the nerve, the classifying diagram of two
categories is equivalent if and only if the categories are equivalent. In this
paper we prove that the classifying diagram of any category is characterized in
terms of classifying spaces of stabilizers of groups. We also prove explicit
decompositions of the classifying diagrams for the categories of finite ordered
sets, finite dimensional vector spaces, and finite sets in terms of classifying
spaces of groups.


  Early Exit Neural Networks (EENNs) present a solution to enhance the
efficiency of neural network deployments. However, creating EENNs is
challenging and requires specialized domain knowledge, due to the large amount
of additional design choices. To address this issue, we propose an automated
augmentation flow that focuses on converting an existing model into an EENN. It
performs all required design decisions for the deployment to heterogeneous or
distributed hardware targets: Our framework constructs the EENN architecture,
maps its subgraphs to the hardware targets, and configures its decision
mechanism. To the best of our knowledge, it is the first framework that is able
to perform all of these steps.
  We evaluated our approach on a collection of Internet-of-Things and standard
image classification use cases. For a speech command detection task, our
solution was able to reduce the mean operations per inference by 59.67%. For an
ECG classification task, it was able to terminate all samples early, reducing
the mean inference energy by 74.9% and computations by 78.3%. On CIFAR-10, our
solution was able to achieve up to a 58.75% reduction in computations.
  The search on a ResNet-152 base model for CIFAR-10 took less than nine hours
on a laptop CPU. Our proposed approach enables the creation of EENN optimized
for IoT environments and can reduce the inference cost of Deep Learning
applications on embedded and fog platforms, while also significantly reducing
the search cost - making it more accessible for scientists and engineers in
industry and research. The low search cost improves the accessibility of EENNs,
with the potential to improve the efficiency of neural networks in a wide range
of practical applications.


  A significant fraction of massive stars are moving supersonically through the
interstellar medium (ISM), either due to disruption of a binary system or
ejection from their parent star cluster. The interaction of their wind with the
ISM produces a bow shock. In late evolutionary stages these stars may undergo
rapid transitions from red to blue and vice versa on the Hertzsprung-Russell
diagram, with accompanying rapid changes to their stellar winds and bow shocks.
Recent 3D simulations of the bow shock produced by the nearby runaway red
supergiant (RSG) Betelgeuse, under the assumption of a constant wind, indicate
that the bow shock is very young (<30000 years old), hence Betelgeuse may have
only recently become a RSG. To test this possibility, we have calculated
stellar evolution models for single stars which match the observed properties
of Betelgeuse in the RSG phase. The resulting evolving stellar wind is
incorporated into 2D hydrodynamic simulations in which we model a runaway blue
supergiant (BSG) as it undergoes the transition to a RSG near the end of its
life. We find that the collapsing BSG wind bubble induces a bow shock-shaped
inner shell around the RSG wind that resembles Betelgeuse's bow shock, and has
a similar mass. Surrounding this is the larger-scale retreating bow shock
generated by the now defunct BSG wind's interaction with the ISM. We suggest
that this outer shell could explain the bar feature located (at least in
projection) just in front of Betelgeuse's bow shock.


  In this paper, we provide a theoretical analysis of closed-loop properties of
a simple data-driven model predictive control (MPC) scheme. The formulation
does not involve any terminal ingredients, thus allowing for a simple
implementation without (potential) feasibility issues. The proposed approach
relies on an implicit description of linear time-invariant systems based on
behavioral systems theory, which only requires one input-output trajectory of
an unknown system. For the nominal case with noise-free data, we prove that the
data-driven MPC scheme ensures exponential stability for the closed loop if the
prediction horizon is sufficiently long. Moreover, we analyze the robust
data-driven MPC scheme for noisy output measurements for which we prove
closed-loop practical exponential stability. The advantages of the presented
approach are illustrated with a numerical example.


  Ultra-relativistic motion and efficient conversion of kinetic energy to
radiation are required by gamma-ray burst (GRB) observations, yet they are
difficult to simultaneously achieve. Three leading mechanisms have been
proposed to explain the observed emission emanating from GRB outflows:
radiation from either relativistic internal or external shocks, or thermal
emission from a photosphere. Previous works were dedicated to independently
treating these three mechanisms and arguing for a sole, unique origin of the
prompt emission of gamma-ray bursts. In contrast, herein, we first explain why
all three models are valid mechanisms and that a contribution from each of them
is expected in the prompt phase. Additionally, we show that a single parameter,
the dimensionless entropy of the GRB outflow, determines which mechanism
contributes the most to the emission. More specifically, internal shocks
dominate for low values of the dimensionless entropy, external shocks for
intermediate values and finally, photospheric emission for large values. We
present a unified framework for the emission mechanisms of GRBs with easily
testable predictions for each process.


  Radiative processes such as synchrotron radiation and Compton scattering play
an important role in astrophysics. Radiative processes are fundamentally
stochastic in nature, and the best tools currently used for resolving these
processes computationally are Monte Carlo (MC) methods. These methods typically
draw a large number of samples from a complex distribution such as the
differential cross section for electron-photon scattering, and then use these
samples to compute the radiation properties such as angular distribution,
spectrum, and polarization. In this work we propose a machine learning (ML)
technique for efficient sampling from arbitrary known probability distributions
that can be used to accelerate Monte Carlo calculation of radiative processes
in astrophysical scenarios. In particular, we apply our technique to inverse
Compton radiation and find that our ML method can be up to an order of
magnitude faster than traditional methods currently in use.


  Suppression measurements for neutral pions ($\pi^0$) are used to investigate
the predicted path length ($L$) and transverse momentum ($p_T$) dependent jet
quenching patterns of the hot QCD medium produced in Au+Au collisions at
$\sqrt{s_{NN}}=200$ GeV. The observed scaling patterns show the predicted
trends for jet-medium interactions dominated by radiative energy loss. They
also allow simple estimates of the transport coefficient $\hat{q}$ and the
ratio of viscosity to entropy density $\eta/s$. These estimates indicate that
the short mean free path ($\lambda$) in the QCD medium leading to
hydrodynamic-like flow with a small value of $\eta/s$, is also responsible for
the strong suppression observed.


  How would randomly shuffling feature vectors among nodes from the same class
affect graph neural networks (GNNs)? The feature shuffle, intuitively, perturbs
the dependence between graph topology and features (A-X dependence) for GNNs to
learn from. Surprisingly, we observe a consistent and significant improvement
in GNN performance following the feature shuffle. Having overlooked the impact
of A-X dependence on GNNs, the prior literature does not provide a satisfactory
understanding of the phenomenon. Thus, we raise two research questions. First,
how should A-X dependence be measured, while controlling for potential
confounds? Second, how does A-X dependence affect GNNs? In response, we (i)
propose a principled measure for A-X dependence, (ii) design a random graph
model that controls A-X dependence, (iii) establish a theory on how A-X
dependence relates to graph convolution, and (iv) present empirical analysis on
real-world graphs that align with the theory. We conclude that A-X dependence
mediates the effect of graph convolution, such that smaller dependence improves
GNN-based node classification.


  Quantum systems must be prepared, controlled, and measured with high fidelity
in order to perform complex quantum algorithms. Control fidelities have greatly
improved in silicon spin qubits, but state preparation and readout fidelities
have generally been poor. By operating with low electron temperatures and
employing high-bandwidth cryogenic amplifiers, we demonstrate single qubit
readout visibilities >99%, exceeding the threshold for quantum error
correction. In the same device, we achieve average single qubit control
fidelities >99.95%. Our results show that silicon spin qubits can be operated
with high overall operation fidelity.


  Low-rank adaption (LoRA) is a prominent method that adds a small number of
learnable parameters to the frozen pre-trained weights for parameter-efficient
fine-tuning. Prompted by the question, ``Can we make its representation enough
with LoRA weights solely at the final phase of finetuning without the
pre-trained weights?'' In this work, we introduce Progressive Compression
LoRA~(PC-LoRA), which utilizes low-rank adaptation (LoRA) to simultaneously
perform model compression and fine-tuning. The PC-LoRA method gradually removes
the pre-trained weights during the training process, eventually leaving only
the low-rank adapters in the end. Thus, these low-rank adapters replace the
whole pre-trained weights, achieving the goals of compression and fine-tuning
at the same time. Empirical analysis across various models demonstrates that
PC-LoRA achieves parameter and FLOPs compression rates of 94.36%/89.1% for
vision models, e.g., ViT-B, and 93.42%/84.2% parameters and FLOPs compressions
for language models, e.g., BERT.


  Recently new reactor antineutrino spectra have been provided for 235U, 239Pu,
241Pu and 238U, increasing the mean flux by about 3 percent. To good
approximation, this reevaluation applies to all reactor neutrino experiments.
The synthesis of published experiments at reactor-detector distances <100 m
leads to a ratio of observed event rate to predicted rate of 0.976(0.024). With
our new flux evaluation, this ratio shifts to 0.943(0.023), leading to a
deviation from unity at 98.6% C.L. which we call the reactor antineutrino
anomaly. The compatibility of our results with the existence of a fourth
non-standard neutrino state driving neutrino oscillations at short distances is
discussed. The combined analysis of reactor data, gallium solar neutrino
calibration experiments, and MiniBooNE-neutrino data disfavors the
no-oscillation hypothesis at 99.8% C.L. The oscillation parameters are such
that |Delta m_{new}^2|>1.5 eV^2 (95%) and sin^2(2\theta_{new})=0.14(0.08)
(95%). Constraints on the theta13 neutrino mixing angle are revised.


  The XMM Large Scale Structure Survey (XMM-LSS) is a major project to map the
large scale structure of the universe out to cosmological distances. An 8
degree by 8 degree region will be surveyed by XMM with planned optical
follow-up to produce a three-dimensional map of many hundreds of clusters out
to a redshift of z = 1. To explore the relation of the large scale structure to
the location and properties of extragalactic radio sources, the XMM-LSS project
also includes a low frequency radio survey of this region. This combination
will provide unprecedented insight into how the radio source formation and
evolution are affected by the local environment. Here, we present preliminary
results from our 325 MHz and 74 MHz surveys in this region. At 325 MHz, we have
a flux limit of 4 mJy/beam, a resolution of 6.3", and a total of 256 source
detections over 5.6 square degrees. At 74 MHz, we have a flux limit of 275
mJy/beam, a resolution of 30", and a total of 211 source detections over 110
square degrees. We describe these results and explore what they tell us about
the population of extra-galactic low frequency radio sources. The 74 MHz survey
represents the first presentation of a deep, sub-arcminute resolution survey at
such a low frequency. This was made possible by recent advances in both
hardware and data reduction algorithms which we describe in detail.


  We present a weak gravitational lensing analysis of supergroup SG1120$-$1202,
consisting of four distinct X-ray-luminous groups, that will merge to form a
cluster comparable in mass to Coma at $z=0$. These groups lie within a
projected separation of 1 to 4 Mpc and within $\Delta v=550$ km s$^{-1}$ and
form a unique protocluster to study the matter distribution in a coalescing
system.
  Using high-resolution {\em HST}/ACS imaging, combined with an extensive
spectroscopic and imaging data set, we study the weak gravitational distortion
of background galaxy images by the matter distribution in the supergroup. We
compare the reconstructed projected density field with the distribution of
galaxies and hot X-ray emitting gas in the system and derive halo parameters
for the individual density peaks.
  We show that the projected mass distribution closely follows the locations of
the X-ray peaks and associated brightest group galaxies. One of the groups that
lies at slightly lower redshift ($z\approx 0.35$) than the other three groups
($z\approx 0.37$) is X-ray luminous, but is barely detected in the
gravitational lensing signal. The other three groups show a significant
detection (up to $5 \sigma$ in mass), with velocity dispersions between
$355^{+55}_{-70}$ and $530^{+45}_{-55}$ km s$^{-1}$ and masses between
$0.8^{+0.4}_{-0.3} \times 10^{14}$ and $1.6^{+0.5}_{-0.4}\times 10^{14} h^{-1}
M_{\odot}$, consistent with independent measurements. These groups are
associated with peaks in the galaxy and gas density in a relatively
straightforward manner. Since the groups show no visible signs of interaction,
this supports the picture that we are catching the groups before they merge
into a cluster.


  We study topological open string amplitudes on orientifolds without fixed
planes. We determine the contributions of the untwisted and twisted sectors as
well as the BPS structure of the amplitudes. We illustrate our general results
in various examples involving D-branes in toric orientifolds. We perform the
computations by using both the topological vertex and unoriented localization.
We also present an application of our results to the BPS structure of the
coloured Kauffman polynomial of knots.


  We search for mirror and cavity-like features of a linear chain of atoms in
which one of the atoms is specially chosen as a probe atom that is initially
prepared in its excited state or is continuously driven by a laser field. Short
chains are considered, composed of only three and five atoms. The analysis
demonstrate the importance of the inter atomic dipole-dipole interaction which
may lead to a collective ordering of the emission along some specific
directions. We examine the conditions under which the radiative modes available
for the emission are only those contained inside a cone centered about the
inter atomic axis. Particular interest is in achieving the one-way emission
along the inter atomic axis, either into left (backward) or right (forward)
direction, which is referred to as a mirror-like behavior of the atomic chain.
A direction dependent quantity called the directivity function, which
determines how effective the system is in concentrating the radiation into a
given direction, is introduced. We show that the function depends crucially on
the distance between the atoms and find that there is a threshold for the inter
atomic distances above which a strongly directional emission can be achieved.
The one-sided emission as a manifestation of the mirror-like behavior and a
highly focused emission along the inter atomic axis as a characteristic of a
single-mode cavity are demonstrated to occur in the stationary field. Below the
threshold the directivity function is spherically symmetric. However, we find
that the population can be trapped in one of the atoms, and sometimes in all
atoms indicating that at these small distances the system decays to a state for
which there are no radiative modes available for emission.


  We study a general version of the adversarial online learning problem. We are
given a decision set $\mathcal{X}$ in a reflexive Banach space $X$ and a
sequence of reward vectors in the dual space of $X$. At each iteration, we
choose an action from $\mathcal{X}$, based on the observed sequence of previous
rewards. Our goal is to minimize regret, defined as the gap between the
realized reward and the reward of the best fixed action in hindsight. Using
results from infinite dimensional convex analysis, we generalize the method of
Dual Averaging (or Follow the Regularized Leader) to our setting and obtain
general upper bounds on the worst-case regret that subsume a wide range of
results from the literature. Under the assumption of uniformly continuous
rewards, we obtain explicit anytime regret bounds in a setting where the
decision set is the set of probability distributions on a compact metric space
$S$ whose Radon-Nikodym derivatives are elements of $L^p(S)$ for some $p > 1$.
Importantly, we make no convexity assumptions on either the set $S$ or the
reward functions. We also prove a general lower bound on the worst-case regret
for any online algorithm. We then apply these results to the problem of
learning in repeated continuous two-player zero-sum games, in which players'
strategy sets are compact metric spaces. In doing so, we first prove that if
both players play a Hannan-consistent strategy, then with probability 1 the
empirical distributions of play weakly converge to the set of Nash equilibria
of the game. We then show that, under mild assumptions, Dual Averaging on the
(infinite-dimensional) space of probability distributions indeed achieves
Hannan-consistency. Finally, we illustrate our results through numerical
examples.


  We discuss the standard Lane-Emden formalism as well as the one related to
the slowly rotating objects. It is preceded by a brief introduction of
different forms of the polytropic equation of state. This allows to study a
wide class of astrophysical objects in the framework of a given theory of
gravity, as demonstrated in a few examples. We will discuss light elements
burning processes and cooling models in stars and substellar objects with the
use of the Lane-Emden formalism.


  Genome and metagenome comparisons based on large amounts of next-generation
sequencing (NGS) data pose significant challenges for alignment-based
approaches due to the huge data size and the relatively short length of the
reads. Alignment-free approaches based on the counts of word patterns in NGS
data do not depend on the complete genome and are generally computationally
efficient. Thus, they contribute significantly to genome and metagenome
comparison. Recently, novel statistical approaches have been developed for the
comparison of both long and shotgun sequences. These approaches have been
applied to many problems including the comparison of gene regulatory regions,
genome sequences, metagenomes, binning contigs in metagenomic data,
identification of virus-host interactions, and detection of horizontal gene
transfers. We provide an updated review of these applications and other related
developments of word-count based approaches for alignment-free sequence
analysis.


  In order to derive tensorial exchange interactions and local magnetic
anisotropies in itinerant magnetic systems, an approach combining the
Spin-Cluster Expansion with the Relativistic Disordered Local Moment scheme is
introduced. The theoretical background and computational aspects of the method
are described in detail. The exchange interactions and site resolved anisotropy
contributions for the IrMn3/Co(111) interface, a prototype for an exchange bias
system, are calculated including a large number of magnetic sites from both the
antiferromagnet and ferromagnet. Our calculations reveal that the coupling
between the two subsystems is fairly limited to the vicinity of the interface.
The magnetic anisotropy of the interface system is discussed, including effects
of the Dzyaloshinskii-Moriya interactions that appear due to symmetry breaking
at the interface.


  Virtual globes have progressed from little-known technology to broadly
popular software in a mere few years. We investigated this phenomenon through a
survey and discovered that, while virtual globes are en vogue, their use is
restricted to a small set of tasks so simple that they do not involve any
spatial thinking. Spatial thinking requires that users ask "what is where" and
"why"; the most common virtual globe tasks only include the "what". Based on
the results of this survey, we have developed a multi-touch virtual globe
derived from an adapted virtual globe paradigm designed to widen the potential
uses of the technology by helping its users to inquire about both the "what is
where" and "why" of spatial distribution. We do not seek to provide users with
full GIS (geographic information system) functionality, but rather we aim to
facilitate the asking and answering of simple "why" questions about general
topics that appeal to a wide virtual globe user base.


  Electric vehicles (EVs) are key to alleviate our dependency on fossil fuels.
The future smart grid is expected to be populated by millions of EVs equipped
with high-demand batteries. To avoid an overload of the (current) electricity
grid, expensive upgrades are required. Some of the upgrades can be averted if
users of EVs participate to energy balancing mechanisms, for example through
bidirectional EV charging. As the proliferation of consumer Internet-connected
devices increases, including EV smart charging stations, their security against
cyber-attacks and the protection of private data become a growing concern. We
need to properly adapt and develop our current technology that must tackle the
security challenges in the EV charging infrastructure, which go beyond the
traditional technical applications in the domain of energy and transport
networks. Security must balance with other desirable qualities such as
interoperability, crypto-agility and energy efficiency. Evidence suggests a gap
in the current awareness of cyber security in EV charging infrastructures. This
paper fills this gap by providing the most comprehensive to date overview of
privacy and security challenges To do so, we review communication protocols
used in its ecosystem and provide a suggestion of security tools that might be
used for future research.


  We consider here a full study of stellar dynamics from the brane-world point
of view in the case of constant density and of a polytropic fluid. We start our
study cataloguing the minimal requirements to obtain a compact object with a
Schwarszchild exterior, highlighting the low and high energy limit, the
boundary conditions, and the appropriate behavior of Weyl contributions inside
and outside of the star. Under the previous requirements we show an extensive
study of stellar behavior, starting with stars of constant density and its
extended cases with the presence of nonlocal contributions. Finally, we focus
our attention to more realistic stars with a polytropic equation of state,
specially in the case of white dwarfs, and study their static configurations
numerically. One of the main results is that the inclusion of the Weyl
functions from braneworld models allow the existence of more compact
configurations than within General Relativity.


  SN 2015bn is a nearby hydrogen-poor superluminous supernova (SLSN-I) that has
been intensively observed in X-rays with the goal to detect the spin-down
powered emission from a magnetar engine. The early-time UV/optical/infrared
(UVOIR) data fit well to the magnetar model, but require leakage of energy at
late times of $\lesssim 10^{43}$ erg s$^{-1}$, which is expected to be
partially emitted in X-rays. Deep X-ray limits until $\sim$300 days after
explosion revealed no X-ray emission. Here, we present the latest deep 0.3--10
keV X-ray limit at 805 days obtained with \textit{XMM-Newton}. We find $L_X <
10^{41}$ erg s$^{-1}$, with no direct evidence for central-engine powered
emission. While the late-time optical data still follow the prediction of the
magnetar model, the best-fit model to the bolometric light curve predicts that
$\sim$97\% of the total input luminosity of the magnetar is escaping outside of
the UVOIR bandpass at the time of observation. Our X-ray upper limit is
$<$1.5\% of the input luminosity, strongly constraining the high-energy
leakage, unless non-radiative losses are important. These deep X-ray
observations identify a missing energy problem in SLSNe-I and we suggest future
observations in hard X-rays and $\gamma$-rays for better constraints. Also,
independent of the optical data, we constrain the parameter spaces of various
X-ray emission scenarios, including ionization breakout by magnetar spin-down,
shock interaction between the ejecta and external circumstellar medium,
off-axis $\gamma$-ray burst afterglow, and black hole fallback accretion.


  We review the last two decades of using photon beams to measure the
production of mesons, and in particular the information that can be obtained on
the spectrum of light, non-strange baryons. This is a compendium of
experimental results, which should be used as a complement to theoretical
reviews of the subject. Lists of data sets are given, together with a
comprehensive set of references. An indication of the impact of the data is
presented with a summary of the results.


  We record photoreflectance from Ge/GeSi modulation doped quantum wells
possessing $10^4$ V/cm perpendicular electric fields. Qualitatively very
different spectra are obtained from samples of well-width 100 \AA and 250 \AA.
Comparing the wavefunctions calculated from an $8 \times 8$ \textbf{k.p}
theory, we find that while they remain confined in the narrower 100 \AA QW, the
electric field causes them to tunnel into the forbidden gap in the 250 \AA\
well. This implies that the samples should show a transition from the quantum
confined Franz-Keldysh effect to the bulk-like Franz-Keldysh effect. Close to
the band-edge where Franz-Keldysh effects are important, simulated
photoreflectance spectra reproduce the essential features of the experiment,
without any adjustable parameters.


  We investigate the gluon Wigner distributions for unpolarized, longitudinally
polarized and transversely polarized target state. Instead of a nucleon, we
take the target state to be a quark dressed with a gluon at one loop and
investigate the gluon Wigner distributions at leading twist. Better numerical
convergence is obtained compared to an earlier study, that removes the
regulator dependence of the results. We present a first calculation of the
Wigner distribution for the transversely polarized target and linearly
polarized gluon. We study the spin densities in momentum and impact parameter
space. We also investigate the quark and gluon helicity and orbital angular
momentum distributions at small-$x$.


  Context. Star clusters constitute a significant part of the stellar
population in our Galaxy. The feedback processes they exert on the interstellar
medium impact multiple physical processes from the chemical to the dynamical
evolution of the Galaxy. In addition, young and massive stellar clusters might
act as efficient particle accelerators and contribute to the production of
cosmic rays. Aims. We aim at evaluating the wind luminosity driven by the young
(< 30 Myr) Galactic open stellar clusters observed by the Gaia space mission.
This is crucial for determining the energy channeled into accelerated
particles. Methods. To do this, we developed a method relying on the number,
magnitude, and line-of-sight extinction of the stars observed per cluster.
Assuming that the stellar mass function follows a Kroupa mass distribution and
accounting for the maximum stellar mass allowed by the age and mass of the
parent cluster, we conservatively estimated the mass and wind luminosity of 387
local clusters within the second data release of Gaia. Results. We compared the
results of our computation with recent estimates of young cluster masses. With
respect to these, our sample is three times more abundant, particularly above a
few thousand solar masses. This is of the utmost relevance for predicting the
gamma-ray emission resulting from the interaction of accelerated particles. The
cluster wind luminosity distribution we obtained extends up to 3x10^38 erg/s.
This is a promising feature in terms of potential particle acceleration
scenarios.


  A theoretical model is presented that for the first time matches experimental
measurements of the pedestal width-height Diallo scaling in the
low-aspect-ratio high-$\beta$ tokamak NSTX. Combining linear gyrokinetics with
self-consistent pedestal equilibrium variation, kinetic-ballooning, rather than
ideal-ballooning plasma instability, is shown to limit achievable confinement
in spherical tokamak pedestals. Simulations are used to find the novel
Gyrokinetic Critical Pedestal constraint, which determines the steepest
pressure profile a pedestal can sustain subject to gyrokinetic instability.
Gyrokinetic width-height scaling expressions for NSTX pedestals with varying
density and temperature profiles are obtained. These scalings for spherical
tokamaks depart significantly from that of conventional aspect ratio tokamaks.


  Recent work on the dynamical evolution of galactic nuclei containing
supermassive black holes is reviewed. Topics include galaxy structural
properties; collisionless and collisional equilibria; loss-cone dynamics; and
dynamics of binary and multiple supermassive black holes.


  Recently, it was shown that there is a phase transition in the community
detection problem. This transition was first computed using the cavity method,
and has been proved rigorously in the case of $q=2$ groups. However, analytic
calculations using the cavity method are challenging since they require us to
understand probability distributions of messages. We study analogous
transitions in so-called "zero-temperature inference" model, where this
distribution is supported only on the most-likely messages. Furthermore,
whenever several messages are equally likely, we break the tie by choosing
among them with equal probability. While the resulting analysis does not give
the correct values of the thresholds, it does reproduce some of the qualitative
features of the system. It predicts a first-order detectability transition
whenever $q > 2$, while the finite-temperature cavity method shows that this is
the case only when $q > 4$. It also has a regime analogous to the "hard but
detectable" phase, where the community structure can be partially recovered,
but only when the initial messages are sufficiently accurate. Finally, we study
a semisupervised setting where we are given the correct labels for a fraction
$\rho$ of the nodes. For $q > 2$, we find a regime where the accuracy jumps
discontinuously at a critical value of $\rho$.


  (abbreviated) We study quantized solutions of WdW equation describing a
closed FRW universe with a $\Lambda $ term and a set of massless scalar fields.
We show that when $\Lambda \ll 1$ in the natural units and the standard
$in$-vacuum state is considered, either wavefunction of the universe, $\Psi$,
or its derivative with respect to the scale factor, $a$, behave as random
quasi-classical fields at sufficiently large values of $a$, when $1 \ll a \ll
e^{{2\over 3\Lambda}}$ or $a \gg e^{{2\over 3\Lambda}}$, respectively.
Statistical r.m.s value of the wavefunction is proportional to the
Hartle-Hawking wavefunction for a closed universe with a $\Lambda $ term.
Alternatively, the behaviour of our system at large values of $a$ can be
described in terms of a density matrix corresponding to a mixed state, which is
directly determined by statistical properties of $\Psi$. It gives a non-trivial
probability distribution over field velocities. We suppose that a similar
behaviour of $\Psi$ can be found in all models exhibiting copious production of
excitations with respect to $out$-vacuum state associated with classical
trajectories at large values of $a$. Thus, the third quantization procedure may
provide a 'boundary condition' for classical solutions of WdW equation.


  We address Fano-like interference effects in scanning tunneling microscopy
(STM) measurements of nanoscale systems, e.g. two-level systems. Common for
these systems is that second order tunneling contributions give rise to
interference effects that cause suppressed transmission through the system for
certain energies. The suppressed transmission is measurable either in the
differential conductance or in the bias voltage derivative thereof.


  We show that the image of a nonconstant conformal harmonic map $\mathbb C\to
\mathbb R^3$, not necessarily proper and possibly with branch points,
intersects every properly embedded nonflat minimal surface of bounded curvature
in $\mathbb R^3$. The same holds if $\mathbb C$ is replaced by any open
conformal surface without nonconstant bounded subharmonic functions.


  Deep Learning has led to a dramatic leap in Super-Resolution (SR) performance
in the past few years. However, being supervised, these SR methods are
restricted to specific training data, where the acquisition of the
low-resolution (LR) images from their high-resolution (HR) counterparts is
predetermined (e.g., bicubic downscaling), without any distracting artifacts
(e.g., sensor noise, image compression, non-ideal PSF, etc). Real LR images,
however, rarely obey these restrictions, resulting in poor SR results by SotA
(State of the Art) methods. In this paper we introduce "Zero-Shot" SR, which
exploits the power of Deep Learning, but does not rely on prior training. We
exploit the internal recurrence of information inside a single image, and train
a small image-specific CNN at test time, on examples extracted solely from the
input image itself. As such, it can adapt itself to different settings per
image. This allows to perform SR of real old photos, noisy images, biological
data, and other images where the acquisition process is unknown or non-ideal.
On such images, our method outperforms SotA CNN-based SR methods, as well as
previous unsupervised SR methods. To the best of our knowledge, this is the
first unsupervised CNN-based SR method.


  We characterize the dynamical instability responsible for the breakdown of
regular rows and necklaces of quantized vortices that appear at the interface
between two superfluids in relative motion. Making use of a generalized
point-vortex model, we identify several mechanisms leading to the suppression
of this instability. They include a non-zero mass of the vortex cores,
dissipative processes resulting from the interaction between the vortices and
the excitations of the superfluid, and the proximity of the vortex array to the
sample boundaries. We show that massive vortex cores not only have a mitigating
effect on the dynamical instability, but also change the associated scaling law
and affect the direction along which it develops. The predictions of our
massive and dissipative point-vortex model are eventually compared against
recent experimental measurements of the maximum instability growth rate
relevant to vortex necklaces in a cold-atom platform.


  With the recent prevalence of Reinforcement Learning (RL), there have been
tremendous interests in developing RL-based recommender systems. In practical
recommendation sessions, users will sequentially access multiple scenarios,
such as the entrance pages and the item detail pages, and each scenario has its
specific characteristics. However, the majority of existing RL-based
recommender systems focus on optimizing one strategy for all scenarios or
separately optimizing each strategy, which could lead to sub-optimal overall
performance. In this paper, we study the recommendation problem with multiple
(consecutive) scenarios, i.e., whole-chain recommendations. We propose a
multi-agent RL-based approach (DeepChain), which can capture the sequential
correlation among different scenarios and jointly optimize multiple
recommendation strategies. To be specific, all recommender agents (RAs) share
the same memory of users' historical behaviors, and they work collaboratively
to maximize the overall reward of a session. Note that optimizing multiple
recommendation strategies jointly faces two challenges in the existing
model-free RL model - (i) it requires huge amounts of user behavior data, and
(ii) the distribution of reward (users' feedback) are extremely unbalanced. In
this paper, we introduce model-based RL techniques to reduce the training data
requirement and execute more accurate strategy updates. The experimental
results based on a real e-commerce platform demonstrate the effectiveness of
the proposed framework.


  Security especially in the fields of IoT, industrial automation and critical
infrastructure is paramount nowadays and a hot research topic. In order to
ensure confidence in research results they need to be reproducible. In the past
we reported [18] that in many publications important information such as
details about the equipment used are missing. In this paper we report on our
own experiments that we run to verify the parameters reported in the datasheets
that came along with our experimental equipment. Our results show that there
are significant discrepancies between the datasheets and the real world data.
These deviations concern accuracy of positions, movements, duration of laser
shots etc. In order to improve reproducibility of results we therefore argue on
the one hand that research groups verify the data given in datasheets of
equipment they use and on the other hand that they provide measurement set-up
parameters in globally accepted units such as cm, seconds, etc.


  A multi-object spectroscopy follow-up survey of galaxy clusters selected from
the Red-sequence Cluster Survey (RCS) is being completed. About forty clusters
were chosen with redshifts from 0.15 to 0.6, and in a wide range of richnesses.
One of the main science drivers of this survey is a study of internal dynamics
of clusters. We present some preliminary results for a subset of the clusters,
including the correlation of optical richness with mass, and the mass-to-light
ratio as a function of cluster mass.


  We obtained thorough photometric observations of two binary near-Earth
asteroids (66391) Moshup = 1999 KW4 and (88710) 2001 SL9 taken from 2000 to
2019 and derived physical and dynamical properties of the binary systems. We
found that the data for 1999 KW4 are inconsistent with a constant orbital
period and we obtained unique solution with a quadratic drift of the mean
anomaly of the satellite of -0.65 +/- 0.16 deg/yr2 (all quoted uncertainties
are 3sigma). This means that the semimajor axis of the mutual orbit of the
components of this binary system increases in time with a mean rate of 1.2 +/-
0.3 cm/yr.
  The data for 2001 SL9 are also inconsistent with a constant orbital period
and we obtained two solutions for the quadratic drift of the mean anomaly: 2.8
+/- 0.2 and 5.2 +/- 0.2 deg/yr2, implying that the semimajor axis of the mutual
orbit of the components decreases in time with a mean rate of -2.8 +/- 0.2 or
-5.1 +/- 0.2 cm/yr for the two solutions, respectively.
  The expanding orbit of 1999 KW4 may be explained by mutual tides interplaying
with binary YORP (BYORP) effect (McMahon and Scheeres, 2010). However, a
modeling of the BYORP drift using radar-derived shapes of the binary components
predicted a much higher value of the orbital drift than the observed one. It
suggests that either the radar-derived shape model of the secondary is
inadequate for computing the BYORP effect, or the present theory of BYORP
overestimates it. It is possible that the BYORP coefficient has instead an
opposite sign than predicted; in that case, the system may be moving into an
equilibrium between the BYORP and the tides.
  In the case of 2001 SL9, the BYORP effect is the only known physical
mechanism that can cause the inward drift of its mutual orbit.


  Post-processing typically takes the outputs of a Numerical Weather Prediction
(NWP) model and applies linear statistical techniques to produce improve
localized forecasts, by including additional observations, or determining
systematic errors at a finer scale. In this pilot study, we investigate the
benefits and challenges of using non-linear neural network (NN) based methods
to post-process multiple weather features -- temperature, moisture, wind,
geopotential height, precipitable water -- at 30 vertical levels, globally and
at lead times up to 7 days. We show that we can achieve accuracy improvements
of up to 12% (RMSE) in a field such as temperature at 850hPa for a 7 day
forecast. However, we recognize the need to strengthen foundational work on
objectively measuring a sharp and correct forecast. We discuss the challenges
of using standard metrics such as root mean squared error (RMSE) or anomaly
correlation coefficient (ACC) as we move from linear statistical models to more
complex non-linear machine learning approaches for post-processing global
weather forecasts.


  Cross-Domain Recommendation (CDR) is an effective way to alleviate the
cold-start problem. However, previous work severely ignores fairness and bias
when learning the mapping function, which is used to obtain the representations
for fresh users in the target domain. To study this problem, in this paper, we
propose a Fairness-aware Cross-Domain Recommendation model, called FairCDR. Our
method achieves user-oriented group fairness by learning the fairness-aware
mapping function. Since the overlapping data are quite limited and
distributionally biased, FairCDR leverages abundant non-overlapping users and
interactions to help alleviate these problems. Considering that each individual
has different influence on model fairness, we propose a new reweighing method
based on Influence Function (IF) to reduce unfairness while maintaining
recommendation accuracy. Extensive experiments are conducted to demonstrate the
effectiveness of our model.


  We propose a system to deliver dynamic guidance in drawing, sketching and
handwriting tasks via an electromagnet moving underneath a high refresh rate
pressure sensitive tablet. The system allows the user to move the pen at their
own pace and style and does not take away control. The system continously and
iteratively measures the pen motion and adjusts magnet position and power
according to the user input in real-time via a receding horizon optimal control
formulation. The optimization is based on a novel approximate electromagnet
model that is fast enough for use in real-time methods, yet provides very good
fit to experimental data. Using a closed-loop time-free approach allows for
error-correcting behavior, gently pulling the user back to the desired
trajectory rather than pushing or pulling the pen to a continuously advancing
setpoint. Our experimental results show that the system can control the pen
position with a very low dispersion of 2.8mm (+/-0.8mm). An initial user study
indicates that it significantly increases accuracy of users drawing a variety
of shapes and that this improvement increases with complexity of the shape.


  Audio signals are often stored and transmitted in compressed formats. Among
the many available audio compression schemes, MPEG-1 Audio Layer III (MP3) is
very popular and widely used. Since MP3 is lossy it leaves characteristic
traces in the compressed audio which can be used forensically to expose the
past history of an audio file. In this paper, we consider the scenario of audio
signal manipulation done by temporal splicing of compressed and uncompressed
audio signals. We propose a method to find the temporal location of the splices
based on transformer networks. Our method identifies which temporal portions of
a audio signal have undergone single or multiple compression at the temporal
frame level, which is the smallest temporal unit of MP3 compression. We tested
our method on a dataset of 486,743 MP3 audio clips. Our method achieved higher
performance and demonstrated robustness with respect to different MP3 data when
compared with existing methods.


  The cosmic ultraviolet background (UVB) heats the intergalactic medium (IGM),
as a result the gas in dark matter halos below a certain mass is too hot to
cool within a Hubble time. The UVB effectively suppresses the formation of
dwarf galaxies. Using high resolution cosmological hydrodynamical simulations
we show that photo heating leads to small baryon fractions in halos below ~
6x10^9 h^{-1}M_sun, independent of the cosmic environment. The simulations are
carried out assuming a homogeneous UVB with flux densities as given by Haardt &
Madau (1996). A halo may stop to condense gas significantly after the universe
is reionised, namely when its mass falls below the characteristic mass scale
set by the photo heating. Assuming a spherical halo model we derive this
characteristic mass analytically and identify the main mechanisms that prevent
the gas from cooling in small halos. The theoretically derived characteristic
mass is smaller than the one obtained from observations. Increasing the energy
per ionising photon by a factor between four and eight would be sufficient to
reconcile both. This is equivalent to an average temperature of the IGM of ~
10^4 K. In this sense the faint end of the luminosity function may serve as a
calorimeter for the IGM.


  The split main sequences found in the colour-magnitude diagrams of star
clusters younger than ~600 Myr are suggested to be caused by the dichotomy of
stellar rotation rates of upper main-sequence stars. Tidal interactions have
been suggested as a possible explanation of the dichotomy of the stellar
rotation rates. This hypothesis proposes that the slow rotation rates of stars
along the split main sequences are caused by tidal interactions in binaries. To
test this scenario, we measured the variations in the radial velocities of
slowly rotating stars along the split main sequence of the young Galactic
cluster NGC 2422 (~90 Myr) using spectra obtained at multiple epochs with the
Canada-France-Hawai'i Telescope. Our results show that most slowly rotating
stars are not radial-velocity variables. Using the theory of dynamical tides,
we find that the binary separations necessary to fully or partially synchronise
our spectroscopic targets, on time-scales shorter than the cluster age, predict
much larger radial velocity variations across multiple-epoch observations, or a
much larger radial velocity dispersion at a single epoch, than the observed
values. This indicates that tidal interactions are not the dominant mechanism
to form slowly rotating stars along the split main sequences. As the
observations of the rotation velocity distribution among B- and A-type stars in
binaries of larger separations hint at a much stronger effect of braking with
age, we discuss the consequences of relaxing the constraints of the dynamical
tides theory.


  We model the early stages of planet formation in the Solar System, including
continual planetesimal formation, and planetesimal and pebble accretion onto
planetary embryos in an evolving disk driven by a disk wind. The aim is to
constrain aspects of planet formation that have large uncertainties by matching
key characteristics of the Solar System. The model produces a good fit to these
characteristics for a narrow range of parameter space. Planetary growth beyond
the ice line is dominated by pebble accretion. Planetesimal accretion is more
important inside the ice line. Pebble accretion inside the ice line is slowed
by higher temperatures, partial removal of inflowing pebbles by planetesimal
formation and pebble accretion further out in the disk, and increased radial
velocities due to gas advection. The terrestrial planets are prevented from
accreting much water ice because embryos beyond the ice line reach the pebble
isolation mass before the ice line enters the terrestrial-planet region. When
only pebble accretion is considered, embryos typically remain near their
initial mass or grow to the pebble-isolation mass. Adding planetesimal
accretion allows Mars-sized objects to form inside the ice line, and allows
giant-planet cores to form over a wider region beyond the ice line. In the
region occupied by Mercury, pebble Stokes numbers are small. This delays the
formation of embryos and stunts their growth, so that only low-mass planets can
form here.


  Several recently devised machine learning (ML) algorithms have shown improved
accuracy for various predictive problems. Model searches, which explore to find
an optimal ML algorithm and hyperparameter values for the target problem, play
a critical role in such improvements. During a model search, data scientists
typically use multiple ML implementations to construct several predictive
models; however, it takes significant time and effort to employ multiple ML
implementations due to the need to learn how to use them, prepare input data in
several different formats, and compare their outputs. Our proposed framework
addresses these issues by providing simple and unified coding method. It has
been designed with the following two attractive features: i) new machine
learning implementations can be added easily via common interfaces between the
framework and ML implementations and ii) it can be scaled to handle large model
configuration search spaces via profile-based scheduling. The results of our
evaluation indicate that, with our framework, implementers need only write
55-144 lines of code to add a new ML implementation. They also show that ours
was the fastest framework for the HIGGS dataset, and the second-fastest for the
SECOM dataset.


  The $\gamma Z$-box diagram for parity violating elastic $e$-$p$ scattering
has recently undergone a thorough analysis by several research groups. Though
all now agree on the analytic form of the diagram, the numerical results differ
due to the treatment of the structure functions, $F_{1,2,3}^{\gamma Z}(x,Q^2)$.
Currently, $F_{1,2,3}^{\gamma Z}(x,Q^2)$ at low $Q^2$ and $W^2$ must be
approximated through the modification of existing fits to electromagnetic
structure function data. We motivate and describe the modification used to
obtain $F_{1,2}^{\gamma Z}(x,Q^2)$ in our previous work. We also describe an
alternative modification and compare the result to our original calculation.
Finally, we present a new modification procedure to acquire $F_3^{\gamma
Z}(x,Q^2)$ in the resonance region and calculate the axial contribution to the
$\gamma Z$-box diagram. Details of these modifications will illuminate where
discrepancies between the groups arise and where future improvements can be
made.


  We study the equation $\dot{u}=\log\det (u_{\alpha\bar{\beta}})-Au+f(z,t)$ in
domains of $\mathbb{C}^n$. This equation has a close connection with the
K\"ahler-Ricci flow. In this paper, we consider the case where the boundary
condition is smooth and the initial condition is irregular.


  There exist an infinite number of exact small momentum fraction-$x$ boundary
conditions on light-cone wavefunctions of bound states in gauge theory. They
are necessary for finite expectation values of the invariant mass operator and
relate components of the wavefunction from different Fock sectors. We
illustrate their consequences by analyzing the small-$x$ quark Regge behavior
of a heavy large-$N$ meson, finding power-law rise of unpolarized
distributions. The polarized distribution changes sign and then vanishes with
minus the unpolarized Regge intercept.


  The method of reconstruction of an attractor from a set of short time series
({\it clusters}) is proposed and discussed. This method is most useful for
correlation dimension estimation of experimental data.


  Fighting fish were very recently introduced by the authors as combinatorial
structures made of square tiles that form two dimensional branching surfaces. A
main feature of these fighting fish is that the area of uniform random fish of
size $n$ scales like $n^{5/4}$ as opposed to the typical $n^{3/2}$ area
behavior of the staircase or direct convex polyominoes that they generalize. In
this extended abstract we concentrate on enumerative properties of fighting
fish: in particular we provide a new decomposition and we show that the number
of fighting fish with $i$ left lower free edges and $j$ right lower free edges
is equal to
  \begin{equation*}
  \frac{(2i+j-2)!(2j+i-2)!}{i!j!(2i-1)!(2j-1)!}.
  \end{equation*} These numbers are known to count rooted planar non-separable
maps with $i+1$ vertices and $j+1$ faces, or two-stack-sortable permutations
with respect to ascending and descending runs, or left ternary trees with
respect to vertices with even and odd abscissa. However we have been unable
until now to provide any explicit bijection between our fish and such
structures. Instead we provide new refined generating series for left ternary
trees to prove further equidistribution results.


  In this paper the space of images is considered as a Riemannian manifold
using the metamorphosis approach, where the underlying Riemannian metric
simultaneously measures the cost of image transport and intensity variation. A
robust and effective variational time discretization of geodesics paths is
proposed. This requires to minimize a discrete path energy consisting of a sum
of consecutive image matching functionals over a set of image intensity maps
and pairwise matching deformations. For square-integrable input images the
existence of discrete, connecting geodesic paths defined as minimizers of this
variational problem is shown. Furthermore, $\Gamma$-convergence of the
underlying discrete path energy to the continuous path energy is proved. This
includes a diffeomorphism property for the induced transport and the existence
of a square-integrable weak material derivative in space and time. A spatial
discretization via finite elements combined with an alternating descent scheme
in the set of image intensity maps and the set of matching deformations is
presented to approximate discrete geodesic paths numerically. Computational
results underline the efficiency of the proposed approach and demonstrate
important qualitative properties.


  The FUGIN CO survey with the Nobeyama 45-m Telescope revealed the 3D
structure of a galactic shock wave in the tangential direction of the 4-kpc
molecular arm. The shock front is located at G30.5+00.0+95 km/s on the
up-stream (lower longitude) side of the star-forming complex W43 (G30.8-0.03),
and composes a molecular bow shock (MBS) concave to W43, exhibiting an
arc-shaped molecular ridge perpendicular to the galactic plane with width $\sim
0^\circ.1$ (10 pc) and vertical length $\sim 1^\circ \ (100\ {\rm pc})$. The
MBS is coincident with the radio continuum bow of thermal origin, indicating
association of ionized gas and similarity to a cometary bright-rimmed cloud.
The up-stream edge of the bow is sharp with a growth width of $\sim 0.5$ pc
indicative of shock front property. The velocity width is $\sim 10$ km/s, and
the center velocity decreases by $\sim 15$ \kms from bottom to top of the bow.
The total mass of molecular gas in MBS is estimated to be $\sim 1.2\times 10^6
<_\odot$ and ionized gas $\sim 2\times 10^4 M_\odot$. The vertical disk
thickness increases step like at the MBS by $\sim 2$ times from lower to upper
longitude, which indicates hydraulic-jump in the gaseous disk. We argue that
the MBS was formed by the galactic shock compression of an accelerated flow in
the spiral-arm potential encountering the W43 molecular complex. A bow-shock
theory can well reproduce the bow morphology. We argue that molecular bows are
common in galactic shock waves not only in the Galaxy but also in galaxies,
where MBS are associated with giant cometary HII regions. We also analyzed the
HI data in the same region to obtain a map of HI optical depth and molecular
fraction. We found a firm evidence of HI-to-H$_{2}$ transition in the galactic
shock as revealed by a sharp molecular front at the MBS front.


  We present C18O observations of the pre-stellar core L1689B, in the (J=3-2)
and (J=2-1) rotational transitions, taken at the James Clerk Maxwell Telescope
in Hawaii. We use a lambda-iteration radiative transfer code to model the data.
We adopt a similar form of radial density profile to that which we have found
in all pre-stellar cores, with a `flat' inner profile, steepening towards the
edge, but we make the gradient of the `flat' region a free parameter. We find
that the core is close to virial equilibrium, but there is tentative evidence
for core contraction. We allow the temperature to vary with a power-law form
and find we can consistently fit all of the CO data with an inverse temperature
gradient that is warmer at the edge than the centre. However, when we combine
the CO data with the previously published millimetre data we fail to find a
simultaneous fit to both data-sets without additionally allowing the CO
abundance to decrease towards the centre. This effect has been observed
qualitatively many times before, as the CO freezes out onto the dust grains at
high densities, but we quantify the effect. Hence we show that the combination
of mm/submm continuum and spectral line data is a very powerful method of
constraining the physical parameters of cores on the verge of forming stars.


  Charge transfer through nanoscale junctions connecting metallic leads with
quantum dots or single molecules is often described within an open system
formulation in terms of Redfield theory. Under non-equilibrium conditions, the
usually invoked rotating wave approximation is not justified which may lead to
unphysical steady state solutions with e.g. negative populations. In this work
we explore subtleties and constraints of the approach and thus clarify its
applicability in numerical calculations. General findings are illustrated for
an analytically solvable case of a molecule with two electronic states.


  Social media sites are now becoming very important platforms for product
promotion or marketing campaigns. Therefore, there is broad interest in
determining ways to guide a site to react more positively to a product with a
limited budget. However, the practical significance of the existing studies on
this subject is limited for two reasons. First, most studies have investigated
the issue in oversimplified networks in which several important network
characteristics are ignored. Second, the opinions of individuals are modeled as
bipartite states(e.g., support or not) in numerous studies, however, this
setting is too strict for many real scenarios. In this study, we focus on
social trust networks(STNs), which have the significant characteristics ignored
in the previous studies. We generalized a famed continuous-valued opinion
dynamics model for STNs, which is more consistent with real scenarios. We
subsequently formalized two novel problems for solving the issue in STNs.
Moreover, we developed two matrix-based methods for these two problems and
experiments on real-world datasets to demonstrate the practical utility of our
methods.


  This paper proposes a qualitative analysis to the simple harmonic motion for
students who are not mathematically well-prepared. It uses the variation in
speed and acceleration to sketch the velocity-time curve. The curve appears to
be sinusoidal, whose shape is largely determined by the fact that the gradient
of a velocity-time graph is acceleration. This approach cannot determine the
exact value of period and claim the curve to be sinusoidal, however, it
complements rigorous mathematical analysis in that it is full of physical
reasoning that the mathematical approaches lack of.


  We study the topologically twisted index of $\mathcal{N}=6$ supersymmetric
Chern-Simons matter theory with $U(N)_k \times U(N)_{-k}$ gauge group in the 't
Hooft limit, that is, for $N, k \, \to \infty$ with $\lambda=N/k$ fixed. In the
regime where $\lambda$ is fixed and large we find an analytical expression for
the leading order term of the index. The leading term of the index matches
precisely the Bekenstein-Hawking entropy of the dual asymptotically AdS$_4$
magnetically charged black holes embedded in IIA supergrvity on AdS$_4\times
\mathbb{CP}^3$, after a standard Legendre transformation. We numerically
explore the genus expansion of the topologically twisteed index beyond the
leading order, focusing on the genus one contribution, that is, $N^0$. We find
qualitative agreement with the topological expansion of the free energy on
$S^3$ at genus one. Our logarithmic in $\lambda$ term constitutes a prediction
for the one-loop effective action on the IIA supergravity side.


  In this paper we discuss the natural candidate for the one dimensional free
Poincar\'e inequality. Two main strong points sustain this candidacy. One is
the random matrix heuristic and the other the relations with the other free
functional inequalities, namely, the free transportation and Log-Sobolev
inequalities. As in the classical case the Poincar\'e is implied by the others.
This investigation is driven by a nice lemma of Haagerup which relates
logarithmic potentials and Chebyshev polynomials. The Poincar\'e inequality
revolves around the counting number operator for the Chebyshev polynomials of
first kind with respect to the arcsine law on $[-2,2]$. This counting number
operator appears naturally in a representation of the minimum of the
logarithmic potential with external fields as well as in the perturbation of
logarithmic energy with external fields, which is the essential connection
between all these inequalities.


  The area under receiver operating characteristics (AUC) is the standard
measure for comparison of anomaly detectors. Its advantage is in providing a
scalar number that allows a natural ordering and is independent on a threshold,
which allows to postpone the choice. In this work, we question whether AUC is a
good metric for anomaly detection, or if it gives a false sense of comfort, due
to relying on assumptions which are unlikely to hold in practice. Our
investigation shows that variations of AUC emphasizing accuracy at low false
positive rate seem to be better correlated with the needs of practitioners, but
also that we can compare anomaly detectors only in the case when we have
representative examples of anomalous samples. This last result is disturbing,
as it suggests that in many cases, we should do active or few-show learning
instead of pure anomaly detection.


  In this paper the celebrated arcsine aging scheme of G. Ben Arous and J.
Cern\'y is taken up. Using a brand new approach based on point processes and
weak convergence techniques, this scheme is implemented in a wide class of
Markov processes that can best be described as Glauber dynamics of discrete
disordered systems. More specifically, conditions are given for the underlying
clock process (a partial sum process that measures the total time elapsed along
paths of a given length) to converge to a subordinator, and this subordinator
is constructed explicitly. This approach is illustrated on Bouchaud's
asymmetric trap model on the complete graph for which aging is for the first
time proved, and the full, optimal picture, obtained.


  Given a sequence of regular finite coverings of complete Riemannian
manifolds, we consider the covering solenoid associated with the sequence. We
study the leaf-wise Laplacian on the covering solenoid. The main result is that
the spectrum of the Laplacian on the covering solenoid equals the closure of
the union of the spectra of the manifolds in the sequence. We offer an
equivalent statement of Selberg's 1/4 conjecture.


  In this work, the study of thermal conductivity before and after in-situ
ring-opening polymerization of cyclic butylene terephthalate into poly
(butylene terephthalate) in presence of graphene-related materials (GRM) is
addressed, to gain insight in the modification of nanocomposites morphology
upon polymerization. Five types of GRM were used: one type of graphite
nanoplatelets, two different grades of reduced graphene oxide (rGO) and the
same rGO grades after thermal annealing for 1 hour at 1700{\deg}C under vacuum
to reduce their defectiveness. Polymerization of CBT into pCBT, morphology and
nanoparticle organization were investigated by means of differential scanning
calorimetry, electron microscopy and rheology. Electrical and thermal
properties were investigated by means of volumetric resistivity and bulk
thermal conductivity measurement. In particular, the reduction of nanoflake
aspect ratio during ring-opening polymerization was found to have a detrimental
effect on both electrical and thermal conductivities in nanocomposites.


  The intervening large--scale structure distorts cosmic microwave background
(CMB) anisotropies via gravitational lensing. The same large--scale structure,
traced by dusty star--forming galaxies, also induces anisotropies in the
far--infrared background (FIRB). We investigate the resulting inter--dependence
of the FIRB and CMB with a halo model for the FIRB. In particular, we calculate
the cross--correlation between the lensing potential and the FIRB. The lensing
potential can be quadratically estimated from CMB temperature and/or
polarization maps. We show that the cross--correlation can be measured with
high signal--to--noise with data from the Planck Surveyor. We discuss how such
a measurement can be used to understand the nature of FIRB sources and their
relation to the distribution of dark matter.


  This article is concerned with three heteroclinic cycles forming a
heteroclinic network in ${\mathbb R}^6$. The stability of the cycles and of the
network are studied. The cycles are of a type that has not been studied before,
and provide an illustration for the difficulties arising in dealing with cycles
and networks in high dimension. In order to obtain information on the stability
for the present network and cycles, in addition to the information on
eigenvalues and transition matrices, it is necessary to perform a detailed
geometric analysis of return maps. Some general results and tools for this type
of analysis are also developed here.


  We report the discovery of a further line of sight allowing detection of HeII
Ly alpha absorption by the intergalactic medium. A HST/STIS survey of 32 bright
z ~ 3 quasars selected from the Hamburg Quasar Surveys yielded one detection
toward QSO 1157+3143 (z ~ 3, B ~ 17). A 10 orbit follow-up spectrum reveals a
UV spectrum significantly supressed by two intervening Lyman limit systems at
z=2.77 and 2.94, but with the continuum flux recovering sufficiently shortward
of ~ 1700 A to allow study of the HeII absorption spectrum in the redshift
range 2.75 < z < 2.97. The absorption is characterized by alternating voids and
dense filament structures seen in both HeII and HI. Attempts to model the HeII
opacity in terms of HI Ly alpha forest absorption are not successful in the
voids, suggesting that HeII reionization is not complete between z=2.77 and
2.97 or that an optically thin Lyman limit system with z ~ 0.3 is responsible
for the additional opacity.


  We study an atomic Bose-Fermi mixture in an optical lattice which is confined
using an optical trap. We obtain the Mott ground states of such a system in the
limit of deep optical lattice and discuss the effect of quantum fluctuations on
these states. We also study the superfluid-insulator transitions of bosons and
metal-insulator transition of fermions in such a mixture within a slave-rotor
mean-field approximation, and obtain the corresponding phase diagram. We
discuss experimental implications of our results.


  A covariant simultaneous action for branes in an arbitrary curved background
spacetime is considered. The action depends on a pair of independent field
variables, the brane embedding functions, through the canonical momentum of a
reparametrization invariant geometric model for the brane, and an auxiliary
vector field. The form of the action is analogous to a symplectic potential.
Extremization of the simultaneous action produces at once the equations of
motion and the Jacobi equations for the brane geometric model, and it also
provides a convenient shortcut towards its second variation. In this note, we
consider geometric models depending only on the intrinsic geometry of the brane
worldvolume, and discuss briefly the generalization to extrinsic geometry
dependent models. The approach is illustrated for Dirac-NambuGoto [DNG] branes.
For a relativistic particle, a simultaneous action was introduced by Bazanski,
that served as an inspiration for the present work.


  In common sense, postselected weak amplification must be related to
destructive interference effect of the meter system, and a single photon exerts
no effect on thermal field via cross-phasemodulation (XPM) interaction. In this
Letter we present, for the first time, a thermal light cross-Kerr effect.
Through analysis, we reveal two unexpected results: i) postselection and weak
amplification can be explained at a classical level without destructive
interference, and ii) weak amplification and weak value are not one thing.
After postselection a new mixed light can be generated which is nonclassical.
This scheme can be realized via electromagnetically-induced transparency.


  Ratio-dependent predator-prey models have been increasingly favored by field
ecologists where predator-prey interactions have to be taken into account the
process of predation search. In this paper we study the conditions of the
existence and stability properties of the equilibrium solutions in a
reaction-diffusion model in which predator mortality is neither a constant nor
an unbounded function, but it is increasing with the predator abundance. We
show that analytically at a certain critical value a diffusion driven (Turing
type) instability occurs, i.e. the stationary solution stays stable with
respect to the kinetic system (the system without diffusion). We also show that
the stationary solution becomes unstable with respect to the system with
diffusion and that Turing bifurcation takes place: a spatially non-homogenous
(non-constant) solution (structure or pattern) arises. A numerical scheme that
preserve the positivity of the numerical solutions and the boundedness of prey
solution will be presented. Numerical examples are also included.