  Using molecular dynamics simulation, we calculate fluctuations and response
for steadily sheared hard spheres over a wide range of packing fractions $\phi$
and shear strain rates $\gamma$, using two different methods to dissipate
energy. To a good approximation, shear stress and density fluctuations are
related to their associated response functions by a single effective
temperature $T_{eff}$ that is equal to or larger than the kinetic temperature
$T_{kin}$. We find a crossover in the relationship between the relaxation time
$\tau$ and the the nondimensionalized effective temperature
$T_{eff}/p\sigma^3$, where $p$ is the pressure and $\sigma$ is the sphere
diameter. In the solid response regime, the behavior at fixed packing fraction
satisfies $\tau\gamma\propto \exp(-cp\sigma^3/T_{eff})$, where $c$ depends
weakly on $\phi$, suggesting that the average local yield strain is controlled
by the effective temperature in a way that is consistent with shear
transformation zone theory. In the fluid response regime, the relaxation time
depends on $T_{eff}/p\sigma^3$ as it depends on $T_{kin}/p\sigma^3$ in
equilibrium. This regime includes both near-equilibrium conditions where
$T_{eff} ~ T_{kin}$ and far-from-equilibrium conditions where $T_{eff} \ne
T_{kin}$. We discuss the implications of our results for systems with soft
repulsive interactions.


  In this short letter we show that the one dimensional non linear
Schr\"odinger equation(NLS)can be solved by a Hopf-Cole transformation which
converts it to the Burgers equation in turbulence.


  Every continuous function of two or more real variables can be written as the
superposition of continuous functions of one real variable along with addition.


  The self energy of $\Delta$-baryon is evaluated at finite temperature and
density using the real time formalism of thermal field theory. The
Dyson-Schwinger equation is used to get the exact thermal propagator followed
by the spectral function of $\Delta$. The $\pi N$ scattering cross section
obtained using explicit $\Delta$ exchange is normalized to the experimental
data in vacuum and its medium modification is implemented by means of the exact
thermal propagator. A significant suppression of the peak of the cross-section
is observed at higher temperature and baryon density. Effects on the mean
relaxation time of nucleons and the temperature dependence of the shear
viscosity of a pion nucleon gas are demonstrated.


  In this work we ask when a group is a 3-manifold group, or more specifically,
when does a group presentation come naturally from a Heegaard diagram for a
3-manifold? We will give some conditions for partial answers to this form of
the Isomorphism Problem by addressing how the presentation associated to a
diagram for a splitting is related to the fundamental group of a 3-manifold. In
the process, we determine an invariant of groups (by way of group
presentations) for how far such presentations are from 3-manifolds.


  We report the application of the time gated ion microscopy technique in
accessing online the position of the source of harmonics generated in atomic
gas media. This is achieved by mapping the spatial extreme-ultraviolet
(XUV)-intensity distribution of the harmonic source onto a spatial ion
distribution, produced in a separate focal volume of the generated XUV beam
through single photon ionization of atoms. It is found that the position of the
harmonic source depends on the relative position of the harmonic generation gas
medium and the focus of the driving infrared (IR) beam. In particular, by
translating the gas medium with respect to the IR beam focus different virtual
source positions are obtained online. Access to such online source positioning
allows better control and provides increased possibilities in experiments where
selection of electron trajectory is important. The present study gives also
access to quantitative information which is connected to the divergence, the
coherence properties and the photon flux of the harmonics. Finally, it
constitutes a precise direct method for providing complementary experimental
info to different attosecond metrology techniques.


  We present a simple yet efficient supervised machine learning algorithm that
is designed for the GNSS position time series prediction. This algorithm has
four steps. First, the mean value of the time series is subtracted from it.
Second, the trends in the time series are removed. Third, wavelets are used to
separate the high and low frequencies. And fourth, a number of frequencies are
derived and used for finding the weights between the hidden and the output
layers, using the product of the identity and sine and cosine functions. The
role of the observation precision is taken into account in this algorithm. A
large-scale study of three thousand position times series of GNSS stations
across the globe is presented. Seventeen different machine learning algorithms
are examined. The accuracy levels of these algorithms are checked against the
rigorous statistical method of Theta. It is shown that the most accurate
machine learning algorithm is the method we present, in addition to being
faster. Two applications of the algorithm are presented. In the first
application, it is shown that the outliers and anomalies in a time series can
be detected and removed by the proposed algorithm. In a large scale study, ten
other methods of time series outlier detection are compared with the proposed
algorithm. The study reveals that the proposed algorithm is approximately 3.22
percent more accurate in detecting outliers. In the second application, the
suitability of the algorithm for earthquake prediction is investigated. A case
study is presented for the Tohoku 2011 earthquake. It is shown that this
earthquake could have been predicted approximately 2 hours before its
happening, solely based on each of the 845 GEONET station time series.
Comparison with four different studies show the improvement in prediction of
the time of the earthquake.


  In recent years the possibility of measuring the temporal change of radial
and transverse position of sources in the sky in real time have become
conceivable thanks to the thoroughly improved technique applied to new
astrometric and spectroscopic experiments, leading to the research domain we
call Real-time cosmology. We review for the first time great part of the work
done in this field, analysing both the theoretical framework and some endeavor
to foresee the observational strategies and their capability to constrain
models. We firstly focus on real time measurements of the overall redshift
drift and angular separation shift in distant source, able to trace background
cosmic expansion and large scale anisotropy, respectively. We then examine the
possibility of employing the same kind of observations to probe peculiar and
proper acceleration in clustered systems and therefore the gravitational
potential. The last two sections are devoted to the short time future change of
the cosmic microwave background, as well as to the temporal shift of the
temperature anisotropy power spectrum and maps. We conclude revisiting in this
context the effort made to forecast the power of upcoming experiments like
CODEX, GAIA and PLANCK in providing these new observational tools.


  Let $R$ be a finite ring and define the paraboloid $P = \{(x_1, \dots,
x_d)\in R^d|x_d = x_1^2 + \dots + x_{d-1}^2\}.$ Suppose that for a sequence of
finite rings of size tending to infinity, the Fourier transform of $P$
satisfies a square-root law for some fixed constant $C$. Then all but finitely
many of the rings are fields. Most of our argument works in greater generality:
let $f$ be a polynomial with integer coefficients in $d-1$ variables, with a
fixed order of variable multiplications (so that it defines a function
$R^{d-1}\rightarrow R$ even when $R$ is noncommutative), and set $V_f = \{(x_1,
\dots, x_d)\in R^d|x_d = f(x_1, \dots, x_{d-1})\}$. If (for a sequence of
finite rings of size tending to infinity) we have a square root law for the
Fourier transform of $V_f$, then all but finitely many of the rings are fields
or matrix rings of small dimension. We also describe how our techniques let us
see that certain varieties do not satisfy a square root law even over finite
fields.


  We explore the possibility to explain the properties of the Be/X-ray pulsars
observed in the Small Magellanic Cloud within the magnetic levitation accretion
scenario. This implies that their X-ray emission is powered by a wind-fed
accretion onto a neutron star (NS) which captures matter from a magnetized
stellar wind. The NS in this case is accreting matter from a non-keplerian
magnetically levitating disc (ML-disc) which is surrounding its magnetosphere.
This allows us to explain the observed periods of the pulsars in terms of spin
equilibrium without the need of invoking dipole magnetic fields outside the
usual range ~ 10^11- 10^13 G inferred from cyclotron features of Galactic high
mass X-ray binaries. We find that the equilibrium period of a NS, under certain
conditions, depends strongly on the magnetization of the stellar wind of its
massive companion and, correspondingly, on the magnetic field of the massive
companion itself. This may help to explain why similar NSs in binaries with
similar properties rotate with different periods yielding a large scatter of
periods of the accretion-powered pulsar observed in SMC and our galaxy.


  Electron Microscopy (EM) image (or volume) segmentation has become
significantly important in recent years as an instrument for connectomics. This
paper proposes a novel agglomerative framework for EM segmentation. In
particular, given an over-segmented image or volume, we propose a novel
framework for accurately clustering regions of the same neuron. Unlike existing
agglomerative methods, the proposed context-aware algorithm divides superpixels
(over-segmented regions) of different biological entities into different
subsets and agglomerates them separately. In addition, this paper describes a
"delayed" scheme for agglomerative clustering that postpones some of the merge
decisions, pertaining to newly formed bodies, in order to generate a more
confident boundary prediction. We report significant improvements attained by
the proposed approach in segmentation accuracy over existing standard methods
on 2D and 3D datasets.


  In recent years, the development of technologies for causal inference with
privacy preservation of distributed data has gained considerable attention.
Many existing methods for distributed data focus on resolving the lack of
subjects (samples) and can only reduce random errors in estimating treatment
effects. In this study, we propose a data collaboration quasi-experiment
(DC-QE) that resolves the lack of both subjects and covariates, reducing random
errors and biases in the estimation. Our method involves constructing
dimensionality-reduced intermediate representations from private data from
local parties, sharing intermediate representations instead of private data for
privacy preservation, estimating propensity scores from the shared intermediate
representations, and finally, estimating the treatment effects from propensity
scores. Through numerical experiments on both artificial and real-world data,
we confirm that our method leads to better estimation results than individual
analyses. While dimensionality reduction loses some information in the private
data and causes performance degradation, we observe that sharing intermediate
representations with many parties to resolve the lack of subjects and
covariates sufficiently improves performance to overcome the degradation caused
by dimensionality reduction. Although external validity is not necessarily
guaranteed, our results suggest that DC-QE is a promising method. With the
widespread use of our method, intermediate representations can be published as
open data to help researchers find causalities and accumulate a knowledge base.


  In the papers [6, 7] we have established linear and quadratic bounds, in $k$,
on the growth of the Lebesgue constants associated with the $k$-sections of
Leja sequences on the unit disc $\mathcal{U}$ and $\Re$-Leja sequences obtained
from the latter by projection into $[-1, 1]$. In this paper, we improve these
bounds and derive sub-linear and sub-quadratic bounds. The main novelty is the
introduction of a "quadratic" Lebesgue function for Leja sequences on
$\mathcal{U}$ which exploits perfectly the binary structure of such sequences
and can be sharply bounded. This yields new bounds on the Lebesgue constants of
such sequences, that are almost of order $\sqrt{k}$ when $k$ has a sparse
binary expansion. It also yields an improvement on the Lebesgue constants
associated with $\Re$-Leja sequences.


  This paper proposes a non-Gaussian Markov field with a special feature: an
explicit partition function. To the best of our knowledge, this is an original
contribution. Moreover, the explicit expression of the partition function
enables the development of an unsupervised edge-preserving convex deconvolution
method. The method is fully Bayesian, and produces an estimate in the sense of
the posterior mean, numerically calculated by means of a Monte-Carlo Markov
Chain technique. The approach is particularly effective and the computational
practicability of the method is shown on a simple simulated example.


  Despite its exceptional soft tissue contrast, Magnetic Resonance Imaging
(MRI) faces the challenge of long scanning times compared to other modalities
like X-ray radiography. Shortening scanning times is crucial in clinical
settings, as it increases patient comfort, decreases examination costs and
improves throughput. Recent advances in compressed sensing (CS) and deep
learning allow accelerated MRI acquisition by reconstructing high-quality
images from undersampled data. While reconstruction algorithms have received
most of the focus, designing acquisition trajectories to optimize
reconstruction quality remains an open question. This thesis explores two
approaches to address this gap in the context of Cartesian MRI. First, we
propose two algorithms, lazy LBCS and stochastic LBCS, that significantly
improve upon G\"ozc\"u et al.'s greedy learning-based CS (LBCS) approach. These
algorithms scale to large, clinically relevant scenarios like multi-coil 3D MR
and dynamic MRI, previously inaccessible to LBCS. Additionally, we demonstrate
that generative adversarial networks (GANs) can serve as a natural criterion
for adaptive sampling by leveraging variance in the measurement domain to guide
acquisition. Second, we delve into the underlying structures or assumptions
that enable mask design algorithms to perform well in practice. Our experiments
reveal that state-of-the-art deep reinforcement learning (RL) approaches, while
capable of adaptation and long-horizon planning, offer only marginal
improvements over stochastic LBCS, which is neither adaptive nor does long-term
planning. Altogether, our findings suggest that stochastic LBCS and similar
methods represent promising alternatives to deep RL. They shine in particular
by their scalability and computational efficiency and could be key in the
deployment of optimized acquisition trajectories in Cartesian MRI.


  On a basis of a two-length scale description of hydrophobic interactions we
develop a continuous self-consistent theory of solute-water interactions which
allows to determine a hydrophobic layer of a solute molecules of any geometry
with explicit account of solvent structure described by its correlation
function. We compute the mean solvent density profile n(r) surrounding the
spherical solute molecule as well as its solvation free energy. We compare the
two-length scale theory to the numerical data of Monte-Carlo simulations found
in the literature and discuss the possibility of a self-consistent adjustment
of the free parameters of the theory. In the frameworks of the discussed
approach we compute also the solvation free energies of alkane molecules and
the free energy of interaction of two spheres separated by some distance. We
describe the general setting of a self-consistent account of electrostatic
interactions in the frameworks of the model where the water is considered not
as a continuous media, but as a gas of dipoles. We analyze the limiting cases
where the proposed theory coincides with the electrostatics of a continuous
media.


  We consider a class of participation rights, i.e. obligations issued by a
company to investors who are interested in performance-based compensation.
Albeit having desirable economic properties equity-based debt obligations
(EbDO) pose challenges in accounting and contract pricing. We formulate and
solve the associated mathematical problem in a discrete time, as well as a
continuous time setting. In the latter case the problem is reduced to a
forward-backward stochastic differential equation (FBSDE) and solved using the
method of decoupling fields.


  Topological insulators and superconductors support extended surface states
protected against the otherwise localizing effects of static disorder.
Specifically, in the Wigner-Dyson insulators belonging to the symmetry classes
A, AI, and AII, a band of extended surface states is continuously connected to
a likewise extended set of bulk states forming a ``bridge'' between different
surfaces via the mechanism of spectral flow. In this work we show that this
mechanism is absent in the majority of non-Wigner-Dyson topological
superconductors and chiral topological insulators. In these systems, there is
precisely one point with granted extended states, the center of the band,
$E=0$. Away from it, states are spatially localized, or can be made so by the
addition of spatially local potentials. Considering the three-dimensional
insulator in class AIII and winding number $\nu=1$ as a paradigmatic case
study, we discuss the physical principles behind this phenomenon, and its
methodological and applied consequences. In particular, we show that low-energy
Dirac approximations in the description of surface states can be treacherous in
that they tend to conceal the localizability phenomenon. We also identify
markers defined in terms of Berry curvature as measures for the degree of state
localization in lattice models, and back our analytical predictions by
extensive numerical simulations. A main conclusion of this work is that the
surface phenomenology of non-Wigner-Dyson topological insulators is a lot
richer than that of their Wigner-Dyson siblings, extreme limits being
spectrum-wide quantum critical delocalization of all states vs. full
localization except at the $E=0$ critical point. As part of our study we
identify possible experimental signatures distinguishing between these
different alternatives in transport or tunnel spectroscopy.


  This paper explores the application of machine learning techniques to predict
where hedging occurs in peer-tutoring interactions. The study uses a
naturalistic face-to-face dataset annotated for natural language turns,
conversational strategies, tutoring strategies, and nonverbal behaviours. These
elements are processed into a vector representation of the previous turns,
which serves as input to several machine learning models. Results show that
embedding layers, that capture the semantic information of the previous turns,
significantly improves the model's performance. Additionally, the study
provides insights into the importance of various features, such as
interpersonal rapport and nonverbal behaviours, in predicting hedges by using
Shapley values for feature explanation. We discover that the eye gaze of both
the tutor and the tutee has a significant impact on hedge prediction. We
further validate this observation through a follow-up ablation study.


  The mathematics and physics of each of the three aspects of magnetic field
evolution -- topology, energy, and helicity -- is remarkably simple and clear.
When the resistivity $\eta$ is small compared to an imposed evolution, $a/v$,
timescale, which means $R_m\equiv\mu_0va/\eta>>1$, magnetic field line chaos
dominates the evolution of field-line topology in three-dimensional systems.
Chaos has no direct role in the dissipation of energy. A large current density,
$j_\eta\equiv vB/\eta$, is required for energy dissipation to be on a
comparable time scale to the topological evolution. Nevertheless, chaos plus
Alfv\'en wave damping explain why both timescales tend to be approximately an
order of magnitude longer than the evolution timescale $a/v$. Magnetic helicity
is injected onto tubes of field lines when boundary flows have vorticity. Chaos
can spread but not destroy magnetic helicity. Resistivity has a negligible
effect on helicity accumulation when $R_m>>1$. Helicity accumulates within a
tube of field lines until the tube erupts and moves far from its original
location.


  We present EchoScene, an interactive and controllable generative model that
generates 3D indoor scenes on scene graphs. EchoScene leverages a dual-branch
diffusion model that dynamically adapts to scene graphs. Existing methods
struggle to handle scene graphs due to varying numbers of nodes, multiple edge
combinations, and manipulator-induced node-edge operations. EchoScene overcomes
this by associating each node with a denoising process and enables
collaborative information exchange, enhancing controllable and consistent
generation aware of global constraints. This is achieved through an information
echo scheme in both shape and layout branches. At every denoising step, all
processes share their denoising data with an information exchange unit that
combines these updates using graph convolution. The scheme ensures that the
denoising processes are influenced by a holistic understanding of the scene
graph, facilitating the generation of globally coherent scenes. The resulting
scenes can be manipulated during inference by editing the input scene graph and
sampling the noise in the diffusion model. Extensive experiments validate our
approach, which maintains scene controllability and surpasses previous methods
in generation fidelity. Moreover, the generated scenes are of high quality and
thus directly compatible with off-the-shelf texture generation. Code and
trained models are open-sourced.


  We study the inhomogeneous incompressible Navier-Stokes system endowed with a
general capillary term. Thanks to recent methods based on Lagrangian change of
variables, we obtain local well-posedness in critical Besov spaces (even if the
integration index p is different from 2) and for variable viscosity and
capillary terms. In the case of constant coefficients and for initial data that
are perturbations of a constant state, we are able to prove that the lifespan
goes to infinity as the capillary coefficient goes to zero, connecting our
result to the global existence result obtained by Danchin and Mucha for the
incompressible Navier-Stokes system with constant coefficients.


  In this note we study the asymptotic mean-square stability for two-step
schemes applied to a scalar stochastic differential equation (sde) and applied
to systems of sdes. We derive necessary and sufficient conditions for the
asymptotic MS-stability of the methods in terms of the parameters of the
schemes. The stochastic Backward Differentiation Formula (BDF2) scheme is
asymptotically mean-square stable for any step-size whereas the two-step
Adams-Bashforth (AB2) and Adams-Moulton (AM2) methods are unconditionally
stable. The improved versions of the schemes do not perform better w.r.t their
stability behavior in the scalar case, as expected, but the situation is
different in more dimensions. Numerical experiments confirm theoretical
results.


  In this survey, we aim to explore the fundamental question of whether the
next generation of artificial intelligence requires quantum computing.
Artificial intelligence is increasingly playing a crucial role in many aspects
of our daily lives and is central to the fourth industrial revolution. It is
therefore imperative that artificial intelligence is reliable and trustworthy.
However, there are still many issues with reliability of artificial
intelligence, such as privacy, responsibility, safety, and security, in areas
such as autonomous driving, healthcare, robotics, and others. These problems
can have various causes, including insufficient data, biases, and robustness
problems, as well as fundamental issues such as computability problems on
digital hardware. The cause of these computability problems is rooted in the
fact that digital hardware is based on the computing model of the Turing
machine, which is inherently discrete. Notably, our findings demonstrate that
digital hardware is inherently constrained in solving problems about
optimization, deep learning, or differential equations. Therefore, these
limitations carry substantial implications for the field of artificial
intelligence, in particular for machine learning. Furthermore, although it is
well known that the quantum computer shows a quantum advantage for certain
classes of problems, our findings establish that some of these limitations
persist when employing quantum computing models based on the quantum circuit or
the quantum Turing machine paradigm. In contrast, analog computing models, such
as the Blum-Shub-Smale machine, exhibit the potential to surmount these
limitations.


  It is shown that in a subcritical random graph with given vertex degrees
satisfying a power law degree distribution with exponent $\gamma>3$, the
largest component is of order $n^{1/(\gamma-1)}$. More precisely, the order of
the largest component is approximatively given by a simple constant times the
largest vertex degree. These results are extended to several other random graph
models with power law degree distributions. This proves a conjecture by
Durrett.


  Extended main sequences (eMSs) and extended main-sequence turnoffs (eMSTOs)
are fascinating phenomena that are routinely observed in star clusters. These
phenomena strongly challenge the current canonical "simple stellar population"
picture of star clusters, which postulates that star clusters are coeval and
chemically homogeneous and can thus be described by a single, unique isochrone.
Detections of eMSs and eMSTOs provide valuable insights into stellar physics
and the evolution of star clusters. This comprehensive review delves into the
observational characteristics, underlying mechanisms, and astrophysical
implications of the eMSs and eMSTOs observed in young (less than 600 million
years) and intermediate-age (600 to 2000 million years) star clusters. Several
scenarios or hypotheses have been proposed to explain these phenomena,
including the presence of an age spread, binary interactions, variable stars,
and differences in stellar rotation rates. This review discusses the advantages
and limitations of current models. Among contemporary models and hypotheses,
stellar rotation has been demonstrated as the most plausible mechanism to
explain the occurrence of eMSs and eMSTOs. Research on stellar rotation and its
connection to eMSs has opened up a myriad of fascinating avenues, such as
investigations of the magnetic braking mechanism in stars, searches for tidally
locked binary systems in star clusters, and investigations as to whether binary
mergers can give rise to massive magnetars. These endeavors have yielded
valuable insights and significantly enriched our understanding of stellar
astrophysics.


  Given a presentation for a rack $\mathcal R$, we define a process which
systematically enumerates the elements of $\mathcal R$. The process is modeled
on the systematic enumeration of cosets first given by Todd and Coxeter. This
generalizes and improves the diagramming method for $n$-quandles introduced by
Winker. We provide pseudocode that is similar to that given by Holt for the
Todd-Coxeter process. We prove that the process terminates if and only if
$\mathcal R$ is finite, in which case, the procedure outputs an operation table
for the finite rack. We conclude with an application to knot theory.


  This article is devoted to investigation of cation self-diffusion mechanisms,
taking place in UO2, UO2+x, and UO2-x crystals simulated under periodic (PBC)
and isolated (IBC) boundary conditions using the method of molecular dynamics
in the approximation of rigid ions and pair interactions. It is shown that
under PBC the cations diffuse via an exchange mechanism (with the formation of
Frenkel defects) with activation energy of 15-22 eV, while under IBC there is
competition between the exchange and vacancy (via Schottky defects) diffusion
mechanisms, which give the effective activation energy of 11-13 eV near the
melting temperature of the simulated UO2.00 nanocrystals. Vacancy diffusion
with lower activation energy of 6-7 eV was dominant in the non-stoichiometric
crystals UO2.10, UO2.15 and UO1.85. Observations showed that a cation vacancy
is accompanied by different number of anion vacancies depending on the
deviation from stoichiometry: no vacancies in UO2.15, single vacancy in UO2.00
and four vacancies in UO1.85. The corresponding law of mass action formulas
derived within the Lidiard-Matzke model allowed explaining the obtained
activation energies and predicting a change in the activation energy within the
temperature range of the superionic phase transition. The diffusion of cations
on the surface of nanocrystals had activation energy of 3.1-3.6 eV.


  Web cookies are ubiquitously used to track and profile the behavior of users.
Although there is a solid empirical foundation for understanding the use of
cookies in the global world wide web, thus far, limited attention has been
devoted for country-specific and company-level analysis of cookies. To patch
this limitation in the literature, this paper investigates persistent
third-party cookies used in the Finnish web. The exploratory results reveal
some similarities and interesting differences between the Finnish and the
global web---in particular, popular Finnish web sites are mostly owned by media
companies, which have established their distinct partnerships with online
advertisement companies. The results reported can be also reflected against
current and future privacy regulation in the European Union.


  Motivated by the long-standing hints of lepton-flavour non-universality in
the $b \to c \ell \nu$ and $b \to s \ell^+ \ell^-$ channels, we study Drell-Yan
ditau production at the Large Hadron Collider (LHC). In the context of models
with third-generation gauge vector leptoquarks (LQs), we calculate the complete
${\cal O} (\alpha_s)$ corrections to the $pp \to \tau^+ \tau^-$ process,
achieving next-to-leading order (NLO) plus parton shower (NLO$+$PS) accuracy
using the POWHEG method. We provide a dedicated Monte Carlo code that evaluates
the NLO QCD corrections on-the-fly in the event generation and use it to study
the numerical impact of NLO$+$PS corrections on the kinematic distributions
that enter the existing experimental searches for non-resonant ditau final
states. Based on our phenomenological analysis we derive NLO accurate
constraints on the masses and couplings of third-generation gauge vector LQs
using the latest LHC ditau search results corresponding to an integrated
luminosity of around $140 \, {\rm fb}^{-1}$ of proton-proton collisions at
$\sqrt{s} = 13 \, {\rm TeV}$. The presented NLO$+$PS generator allows for an
improved signal modelling, making it an essential tool for future ATLAS and CMS
searches for vector LQs in $\tau^+ \tau^-$ final states at LHC Run III and
beyond.


  We prove the generalised Tate conjecture for H^3 of products of elliptic
curves over finite fields, by slightly modifying an argument of M. Spiess
concerning the Tate conjecture. We prove it fully if the elliptic curves run
among at most 3 isogeny classes. We also show how things become more intricate
from H^4 onwards, for more that 3 isogeny classes.


  We present RuDSI, a new benchmark for word sense induction (WSI) in Russian.
The dataset was created using manual annotation and semi-automatic clustering
of Word Usage Graphs (WUGs). Unlike prior WSI datasets for Russian, RuDSI is
completely data-driven (based on texts from Russian National Corpus), with no
external word senses imposed on annotators. Depending on the parameters of
graph clustering, different derivative datasets can be produced from raw
annotation. We report the performance that several baseline WSI methods obtain
on RuDSI and discuss possibilities for improving these scores.


  As the field of Spoken Dialogue Systems and Conversational AI grows, so does
the need for tools and environments that abstract away implementation details
in order to expedite the development process, lower the barrier of entry to the
field, and offer a common test-bed for new ideas. In this paper, we present
Plato, a flexible Conversational AI platform written in Python that supports
any kind of conversational agent architecture, from standard architectures to
architectures with jointly-trained components, single- or multi-party
interactions, and offline or online training of any conversational agent
component. Plato has been designed to be easy to understand and debug and is
agnostic to the underlying learning frameworks that train each component.


  Recent breakthroughs in high-resolution imaging of biomolecules in solution
with cryo-electron microscopy (cryo-EM) have unlocked new doors for the
reconstruction of molecular volumes, thereby promising further advances in
biology, chemistry, and pharmacological research. Recent next-generation volume
reconstruction algorithms that combine generative modeling with end-to-end
unsupervised deep learning techniques have shown promising preliminary results,
but still face considerable technical and theoretical hurdles when applied to
experimental cryo-EM images. In light of the proliferation of such methods, we
propose here a critical review of recent advances in the field of deep
generative modeling for cryo-EM volume reconstruction. The present review aims
to (i) unify and compare these new methods using a consistent statistical
framework, (ii) present them using a terminology familiar to machine learning
researchers and computational biologists with no specific background in
cryo-EM, and (iii) provide the necessary perspective on current advances to
highlight their relative strengths and weaknesses, along with outstanding
bottlenecks and avenues for improvements in the field. This review might also
raise the interest of computer vision practitioners, as it highlights
significant limits of deep generative models in low signal-to-noise regimes --
therefore emphasizing a need for new theoretical and methodological
developments.


  The initial mass-final mass relationship (IFMR) of white dwarfs (WD)
represents a crucial benchmark for stellar evolution models, especially for the
efficiency of mixing episodes and mass loss during the asymptotic giant branch
(AGB) phase. In this study, we argue that such relation offers the opportunity
of constraining the third dredge-up (3DU), with important consequences for
chemical yields. The results are discussed in light of recent studies that have
identified a kink in the IFMR for initial masses close to $2\,M_{\odot}$.
Adopting a physically-sound approach in which the efficiency $\lambda$ of the
3DU varies as a function of core and envelope masses, we calibrate $\lambda$ in
solar-metallicity TP-AGB models in order to reproduce the final masses of their
WD progeny, over a the range of initial masses $0.9 \le M_{\rm i}/M_{\odot} \le
6$. In particular, we find that in low-mass stars with $1.4 \le M_{\rm
i}/M_{\odot} \le 2.0$ the efficiency is small, $\lambda \le 0.3$, it steeply
rises to about $\lambda \simeq 0.65$ in intermediate-mass stars with $2.0 \le
M_{\rm i}/M_{\odot} \le 4.0$, and then it drops in massive TP-AGB stars with
$4.0 \le M_{\rm i}/M_{\odot} \le 6.0$. Our study also suggests that a second
kink may show up in the IFMR at the transition between the most massive carbon
stars and those that are dominated by hot-bottom burning.


  In this work, the experiment is discussed on the verification of the
principle of universality of gravitational interactions and some related
problems of gravity theory and physics of elementary particles. The meaning of
this proposal lies in the fact that the self-consistency of General Relativity,
as it turns out, presuppose the existence of the nongravitating form of energy.
Theory predicts that electrons are particles that transfer the nongravitating
form of energy.


  In this note, we first introduce a boundary problem for Lagrangian
submanifolds, analogous to the problem for free boundary hypersurfaces and
capillary hypersurfaces. Then we present several interesting examples of
Lagrangian submanifolds satisfying this boundary condition and we prove a
Lagrangian version of Nitsche (or Hopf) type theorem. Some problems are
proposed at the end of this note.


  Based on NASA satellite infrared and visible range measurements, cloud amount
ISCCP_D1 summer nighttime data, representing the tropospheric cloud activity at
Central Russia are examined over 1994-2007, and the lunar signal in the cloud
amount was extracted. The ISCCP_D1 database was used to confirm previous
results of Pertsev, Dalin and Romejko (2007) on the large importance of lunar
declination effect compared to the lunar phase effect. Since this database
provides much more information than it was used in that previous investigation,
it has become possible to separate the lunar phase effect and the lunar
declination effect in cloudiness. The relative cloud amount tends to grow with
a change of lunar phase from a quadrature to the New Moon or Full Moon and with
increasing of the lunar declination by absolute value. The both effects are
statistically significant, the second one is a little stronger.


  We evaluate the O(alpha) QED corrections to the recoil electron energy
spectrum in the process nu_l + e --> nu_l + e (+gamma), where (+gamma)
indicates the possible emission of a photon and l=e, mu or tau. The soft and
hard bremsstrahlung differential cross sections are computed for an arbitrary
value of the photon energy threshold. We also study the O(alpha) QED
corrections to the differential cross section with respect to the total
combined energy of the recoil electron and a possible accompanying photon.
Their difference from the corrections to the electron spectrum is investigated.
We discuss the relevance and applicability of both radiative corrections,
emphasizing their role in the analysis of precise solar neutrino electron
scattering experiments.


  Unsigned Distance Fields (UDFs) can be used to represent non-watertight
surfaces. However, current approaches to converting them into explicit meshes
tend to either be expensive or to degrade the accuracy. Here, we extend the
marching cube algorithm to handle UDFs, both fast and accurately. Moreover, our
approach to surface extraction is differentiable, which is key to using
pretrained UDF networks to fit sparse data.


  Dynamical phase transitions (DPTs) arise from qualitative changes in the
long-time behavior of stochastic trajectories, often observed in systems with
kinetic constraints or driven out of equilibrium. Here we demonstrate that
first-order DPTs can occur even in the large deviations of a single Brownian
particle without drift, but only when the system's dimensionality exceeds four.
These DPTs are accompanied by temporal phase separations in the trajectories
and exhibit dimension-dependent order due to the threshold behavior for bound
state formation in Schr\"{o}dinger operators. We also discover second-order
DPTs in one-dimensional Brownian motion, characterized by universal exponents
in the rate function of dynamical observables. Our results establish a novel
framework linking classical DPTs to quantum phase transitions.


  It has been found that there is a strong correlation between the circular
velocity V_c and the central stellar velocity dispersion \sigma_0 of galaxies.
In this respect, low surface brightness galaxies (LSB) follow a different
relation when compared to Elliptical and high surface brightness (HSB)
galaxies. The intrinsic scatter of the V_c-\sigma_0 is partially due to the
different concentration of the light distribution. In this work we measure the
C_28 concentration parameter for a sample of 17 LSB finding that the C_28
parameter does not account for the different behavior in the $V_c - {\sigma}_0$
for this class of objects.


  For a two-dimensional Artin group $A$ whose associated Coxeter group is
hyperbolic, we prove that the action of $A$ on the hyperbolic space obtained by
coning off certain subcomplexes of its modified Deligne complex is
acylindrical. Moreover, if for each $s\in S$ there is $t\in S$ with $m_{st}<
\infty$, then this action is universal. As a consequence, for $|S|\geq 3$, if
$A$ is irreducible, then it is acylindrically hyperbolic. We also obtain the
Tits alternative for $A$, and we classify the subgroups of $A$ that virtually
split as a direct product. A key ingredient in our approach is a simple
criterion to show the acylindricity of an action on a two-dimensional
$\mathrm{CAT}(-1)$ complex.


  We report the existence of spiral arms in the recently formed gaseous and
dusty disk of the closest giant elliptical, NGC 5128 (Centaurus A), using high
resolution 12CO(2-1) observations of the central 3 arcmin (3 kpc) obtained with
the Submillimeter Array (SMA). This provides evidence that spiral-like features
can develop within ellipticals if enough cold gas exists. We elucidate the
distribution and kinematics of the molecular gas in this region with a
resolution of 4.4 x 1.9 (80 pc x 40 pc). The spiral arms extend from the
circumnuclear gas at a radius of 200 pc to at least 1 kiloparsec. The general
properties of the arms are similar to those in spiral galaxies: they are
trailing, the width is \sim 500 \pm 200 pc, and the pitch angle is 20 degrees.
From independent estimates of the time when the HI-rich galaxy merger occurred,
we infer that the formation of spiral arms happened on a time scale of less
than \sim10^8 yr. The formation of spiral arms increases the gas density and
thus the star formation efficiency in the early stages of the formation of a
disk.


  Resonance fluorescence of a single trapped ion is spectrally analyzed using a
heterodyne technique. Motional sidebands due to the oscillation of the ion in
the harmonic trap potential are observed in the fluorescence spectrum. From the
width of the sidebands the cooling rate is obtained and found to be in
agreement with the theoretical prediction.


  Math Word Problems (MWP) is an important task that requires the ability of
understanding and reasoning over mathematical text. Existing approaches mostly
formalize it as a generation task by adopting Seq2Seq or Seq2Tree models to
encode an input math problem in natural language as a global representation and
generate the output mathematical expression. Such approaches only learn shallow
heuristics and fail to capture fine-grained variations in inputs. In this
paper, we propose to model a math word problem in a fine-to-coarse manner to
capture both the local fine-grained information and the global logical
structure of it. Instead of generating a complete equation sequence or
expression tree from the global features, we iteratively combine low-level
operands to predict a higher-level operator, abstracting the problem and
reasoning about the solving operators from bottom to up. Our model is naturally
more sensitive to local variations and can better generalize to unseen problem
types. Extensive evaluations on Math23k and SVAMP datasets demonstrate the
accuracy and robustness of our method.


  We tackle the problem of accelerating column generation (CG) approaches to
set cover formulations in operations research. At each iteration of CG we
generate a dual solution that approximately solves the LP over all columns
consisting of a subset of columns in the nascent set. We refer to this linear
program (LP) as the Family Restricted Master Problem (FRMP), which provides a
tighter bound on the master problem at each iteration of CG, while preserving
efficient inference. For example, in the single source capacitated facility
location problem (SSCFLP) the family of a column $l$ associated with facility
$f$ and customer set $N_l$ contains the set of columns associated with $f$ and
the customer set that lies in the power set of $N_l$. The solution to FRMP
optimization is attacked with a coordinate ascent method in the dual. The
generation of direction of travel corresponds to solving the restricted master
problem over columns corresponding to the reduced lowest cost column in each
family given specific dual variables based on the incumbent dual, and is easily
generated without resolving complex pricing problems. We apply our algorithm to
the SSCFLP and demonstrate improved performance over two relevant baselines.


  In our project we have designed an Android application to obtain mobility
data of the citizens in the metropolitan area of Barcelona. Our implementation
synchronously obtains in background on the one hand, periodic location updates
and, on the other hand, the type of activity citizens are doing. At the end of
the day, all this data is processed and sent to a server where are stored to
obtain mobility patterns from citizens that could help to improve the current
transportation infrastructure. MobilitApp is fully functional and stable
although the results can be improved in some situations. In future releases we
will implement machine learning technics to obtain significant improvements,
especially in the activity recognition modules.


  In intensity-modulated radiation therapy, optimal intensity distributions of
incoming beams are decomposed into linear combinations of leaf openings of a
multileaf collimator (segments). In order to avoid inefficient dose delivery,
the decomposition should satisfy a number of dosimetric constraints due to
suboptimal dose characteristics of small segments. However, exact decomposition
with dosimetric constraints is only in limited cases possible. The present work
introduces new heuristic segmentation algorithms for the following optimization
problem: Find a segmentation of an approximated matrix using only allowed
fields and minimize the approximation error. Finally, the decomposition
algorithms were implemented into an optimization programme in order to examine
the assumptions of the algorithms for a clinical example. As a result,
identical dose distributions with much fewer segments and a significantly
smaller number of monitor units could be achieved using dosimetric constraints.
Consequently, the dose delivery is more efficient and less time consuming.


  Relativistic formulae for spin averaged and spin dependent one photon
exchange differential cross sections are developed for spin half fermion
fermion elastic scattering. Spin transfer cross sections are important for the
Polarized Antiproton eXperiments (PAX) project at GSI Darmstadt. In particular,
cross sections for polarization transfer in antiproton electron and antiproton
proton elastic collisions are presented.


  We experimentally determine the equation of state of a laser cooled gas. By
employing the Lane-Emden formalism, widely used in astrophysics, we derive the
equilibrium atomic profiles in large magneto optical traps where the
thermodynamic effects are cast in a polytropic equation of state. The effects
of multiple scattering of light are included, which results in a generalized
Lane-Emden equation for the atomic profiles. A detailed experimental
investigation reveals an excellent agreement with the model, with a two-fold
significance. In one hand, we can infer on the details of the equation of state
of the system, from an ideal gas to a correlated phase due to an effective
electrical charge for the atoms, which is accurately described by a
microscopical description of the effective electrostatic interaction. On the
other hand, we are able map the effects of multiple scattering onto directly
controllable experimental variables, which paves the way to subsequent
experimental investigations of this collective interaction.


  In this paper, we describe physical effects occurring in the regularized
Robertson-Walker spacetime which can reveal the presence of the defect. Our
analysis is based on two main physical quantities: the compressive forces
acting on (human) observers and the energy possessed by massive particles and
photons during their dynamical evolution. In Sec. 3, we claim that with a
characteristic length scale of the order of the Planck length compressive
forces become so intense near the defect that no (human) observer is able to
cross it. In Sec. 4, we show that the energy exhibits an unusual character over
a small time interval around the bounce contrasting with the behaviour in the
standard cosmology picture. We conclude the paper with some considerations and
open problems related to our results.


  A fundamental problem in cognitive radio systems is that the cognitive radio
is ignorant of the primary channel state and the interference it inflicts on
the primary license holder. In this paper we assume that the primary
transmitter sends packets across an erasure channel and the primary receiver
employs ACK/NAK feedback (ARQ) to retransmit erased packets. The cognitive
radio can eavesdrop on the primary's ARQs. Assuming the primary channel states
follow a Markov chain, this feedback gives the cognitive radio an indication of
the primary link quality. Based on the ACK/NACK received, we devise optimal
transmission strategies for the cognitive radio so as to maximize a weighted
sum of primary and secondary throughput. The actual weight used during network
operation is determined by the degree of protection afforded to the primary
link. We study a two-state model where we characterize a scheme that spans the
boundary of the primary-secondary rate region. Moreover, we study a three-state
model where we derive the optimal strategy using dynamic programming. We also
show via simulations that our optimal strategies achieve gains over the simple
greedy algorithm for a range of primary channel parameters.


  The experimental data on $K^0$ and $\Lambda$ production by $\nu$ and
$\bar{\nu}$ beams are compared with the predictions of quark model assuming
that the direct production of secondaries dominates. Disagreement of these
predictions with the data allows one to suppose that there exists considerable
resonance decay contribution to the multiplicities of produced secondaries.


  It is shown that the semimetallic state of the two-dimensional honeycomb
lattice with a point-like Fermi surface is unstable towards a canted
antiferromagnetic insulator upon application of an in-plane magnetic field.
This instability is already present at the mean-field level; the magnetic field
shifts the up- and the down-spin cones in opposite directions thereby
generating a finite density of states at the Fermi surface and a perfect
nesting between the up- and the down-spin Fermi sheets. This perfect nesting
triggers a canted antiferromagnetic insulating state. Our conclusions, based on
mean-field arguments, are confirmed by auxiliary field projective quantum Monte
Carlo methods on lattices up to $12 \times 12$ unit cells.


  In an earlier work (R. Bhandari, Phys. Lett. A 204 (1995) 188), it was shown
that, contrary to the property of achromaticity (independence of wavelength)
usually associated with topological phases, topological phases encountered in
polarization optics can, under certain conditions, show sharp changes and
reversals as a function of wavelength, a phenomenon originating in the
occurrence of phase singularities, earlier observed in interference
experiments. It was shown that a proposed flat lens capable of focussing light
with pure geometric phase shifts can switch from being convex to a concave lens
or vice versa under these conditions. In this paper conditions under which such
reversals can take place for small changes in wavelength are described. Some
general implications of phase singularities in the physics of interference are
pointed out.


  For n at least 2, the concept of n-way expanders was defined by various
researchers. Bigger n gives a weaker notion in general, and 2-way expanders
coincide with expanders in usual sense. Koji Fujiwara asked whether these
concepts are equivalent to that of ordinary expanders for all n for a sequence
of Cayley graphs. In this paper, we answer his question in the affirmative.
Furthermore, we obtain universal inequalities on multi-way isoperimetric
constants on any finite connected vertex-transitive graph, and show that gaps
between these constants imply the imprimitivity of the group action on the
graph.


  This paper proposes new formulas for the probabilities of causation difined
by Pearl (2000). Tian and Pearl (2000a, 2000b) showed how to bound the
quantities of the probabilities of causation from experimental and
observational data, under the minimal assumptions about the data-generating
process. We derive narrower bounds than Tian-Pearl bounds by making use of the
covariate information measured in experimental and observational studies. In
addition, we provide identifiable case under no-prevention assumption and
discuss the covariate selection problem from the viewpoint of estimation
accuracy. These results are helpful in providing more evidence for public
policy assessment and dicision making problems.


  We describe homogeneous sub-Riemannian geodesics for the standard
sub-Riemannian structure on the group of proper motions of the plane SE(2). We
show that this structure is not geodesically orbital, although the cut time is
invariant w.r.t. shift of the initial point along geodesic.


  A conserved stress energy tensor for weak field gravitational waves
propagating in vacuum is derived directly from the linearized wave equation
alone, for an arbitrary gauge using standard general relativity. In any
harmonic gauge, the form of the tensor leads directly to the classical
expression for the outgoing wave energy. The method described here, however, is
a much simpler, shorter, and more physically motivated approach than is the
customary procedure, which involves a lengthy and cumbersome second-order (in
wave-amplitude) calculation starting with the Einstein tensor. Our method has
the added advantage of exhibiting the direct coupling between the outgoing
energy flux in gravitational waves and the work done by the gravitational field
on the sources. For nonharmonic gauges, the directly derived wave stress tensor
has an apparent index asymmetry. This coordinate artefact may be removed, and
the symmetrized (still gauge-invariant) tensor then takes on its widely-used
form. Angular momentum conservation follows immediately. For any harmonic
gauge, however, the stress tensor is manifestly symmetric from the start and
its derivation depends, in its entirety, on the structure of the linearized
wave equation.


  Due to the incapability of one sensory measurement to provide enough
information for condition monitoring of some complex engineered industrial
mechanisms and also for overcoming the misleading noise of a single sensor,
multiple sensors are installed to improve the condition monitoring of some
industrial equipment. Therefore, an efficient data fusion strategy is demanded.
In this research, we presented a Denoising Multi-Modal Autoencoder with a
unique training strategy based on contrastive learning paradigm, both being
utilized for the first time in the machine health monitoring realm. The
presented approach, which leverages the merits of both supervised and
unsupervised learning, not only achieves excellent performance in fusing
multiple modalities (or views) of data into an enriched common representation
but also takes data fusion to the next level wherein one of the views can be
omitted during inference time with very slight performance reduction, or even
without any reduction at all. The presented methodology enables multi-modal
fault diagnosis systems to perform more robustly in case of sensor failure
occurrence, and one can also intentionally omit one of the sensors (the more
expensive one) in order to build a more cost-effective condition monitoring
system without sacrificing performance for practical purposes. The
effectiveness of the presented methodology is examined on a real-world private
multi-modal dataset gathered under non-laboratory conditions from a complex
engineered mechanism, an inline four-stroke spark-ignition engine, aiming for
spark plug fault diagnosis. This dataset, which contains the accelerometer and
acoustic signals as two modalities, has a very slight amount of fault, and
achieving good performance on such a dataset promises that the presented method
can perform well on other equipment as well.


  The rapid development of functional graphene-like nanoribbons with
high-quality has become increasingly reliant on multiple nanofabrication
platforms while traditional methods are facing mounting limitations in this
regard. Consequently, the demand for novel techniques to explore and manipulate
graphene-like nanoribbons has surged. Herein, we report an on-surface synthesis
of graphene-like nanoribbons on pentacene/picene monomers via a series of
self-assembly and annealing on the one-dimensional(1D) Au(110) substrate. Our
scanning tunneling microscope(STM) research reveals that four-/eight- membered
rings are formed between adjacent molecules. Furthermore, we demonstrate the
technique to manipulate the pentacene dimer without breaking its structure by
operating an STM tip. Our results exhibit a possible platform for developing
next generation graphene-based quantum computing designs and a technique to
obtain multiple functional graphene-like nanoribbons with high-precision.


  The emergence of location-based social networks provides an unprecedented
chance to study the interaction between human mobility and social relations.
This work is a step towards quantifying whether a location is suitable for
conducting social activities, and the notion is named location sociality. Being
able to quantify location sociality creates practical opportunities such as
urban planning and location recommendation. To quantify a location's sociality,
we propose a mixture model of HITS and PageRank on a heterogeneous network
linking users and locations. By exploiting millions of check-in data generated
by Instagram users in New York and Los Angeles, we investigate the relation
between location sociality and several location properties, including location
categories, rating and popularity. We further perform two case studies, i.e.,
friendship prediction and location recommendation, experimental results
demonstrate the usefulness of our quantification.


  Let $(M, g)$ denote a cosmological spacetime describing the evolution of a
universe which is isotropic and homogeneous on large scales, but highly
inhomogeneous on smaller scales. We consider two past lightcones, the first,
$\mathcal{C}^-_L(p, g)$, is associated with the physical observer $p\in\,M$ who
describes the actual physical spacetime geometry of $(M, g)$ at the length
scale $L$, whereas the second, $\mathcal{C}^-_L(p, \hat{g})$, is associated
with an idealized version of the observer $p$ who, notwithstanding the presence
of local inhomogeneities at the given scale $L$, wish to model $(M, g)$ with a
member $(M, \hat{g})$ of the family of Friedmann-Lemaitre-Robertson-Walker
spacetimes. In such a framework, we discuss a number of mathematical results
that allows a rigorous comparison between the two lightcones
$\mathcal{C}^-_L(p, g)$ and $\mathcal{C}^-_L(p, \hat{g})$. In particular, we
introduce a scale dependent ($L$) lightcone-comparison functional, defined by a
harmonic type energy, associated with a natural map between the physical
$\mathcal{C}^-_L(p, g)$ and the FLRW reference lightcone $\mathcal{C}^-_L(p,
\hat{g})$. This functional has a number of remarkable properties, in particular
it vanishes iff, at the given length-scale, the corresponding lightcone surface
sections (the celestial spheres) are isometric. We discuss in detail its
variational analysis and prove the existence of a minimum that characterizes a
natural scale-dependent distance functional between the two lightcones. We also
indicate how it is possible to extend our results to the case when caustics
develop on the physical past lightcone $\mathcal{C}^-_L(p, g)$. Finally, we
show how the distance functional is related to spacetime scalar curvature in
the causal past of the two lightcones, and briefly illustrate a number of its
possible applications.


  Black widows (BWs) are millisecond pulsars ablating their companion stars.
The out-flowing material from the companion can block the radio emission of the
pulsar, resulting in eclipses. In this paper, we construct a model for the
radio eclipse by calculating the geometry of the bow shock between the winds of
the pulsar and companion, where the shock shapes the eclipsing medium but had
not been described in detail in previous works. The model is further used to
explain the variations of the flux density and dispersion measure (DM) of three
BW pulsars (i.e., PSR B1957$+$20, J2055$+$3829, and J2051$-$0827) detected by
the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Consequently,
we constrained the parameters of the three BW systems such as the inclination
angles and true anomalies of the observer as well as the mass-loss rates and
wind velocity of the companion stars. With the help of these constraints, it is
expected that magnetic fields of companion stars and even masses of pulsars
could further be determined as some extra observation can be achieved in the
future.


  The [Ne II] fine-structure emission line at 12.8 micron has been detected in
several young stellar objects (YSO) spectra. This line is thought to be
produced by X-ray irradiation of the warm protoplanetary disk atmospheres,
however the observational correlation between [Ne II] luminosities and measured
X-ray luminosities shows a large scatter. Such spread limits the utility of
this line as a probe of the gaseous phase of disks, as several authors have
suggested pollution by outflows as a probable cause of the observed scatter. In
this work we explore the possibility that the large variations in the observed
[Ne II] luminosity may be caused instead by different star-disk parameters. In
particular we study the effects that the hardness of the irradiating source and
the structure (flaring) of the disk have on the luminosity and spectral profile
of the [Ne II] 12.8 micron line. We find that varying these parameter can
indeed cause up to an order of magnitude variation in the emission luminosities
which may explain the scatter observed, although our models predict somewhat
smaller luminosities than those recently reported by other authors who observed
the line with the Spitzer Space Telescope. Our models also show that the
hardness of the spectrum has only a limited (undetectable) effect on the line
profiles, while changes in the flaring power of the disk significantly affect
the size of the [Ne II] emission region and, as a consequence, its line
profile. In particular we suggest that broad line profiles centred on the
stellar radial velocity may be indicative of flat disks seen at large
inclination angles.


  In addition to the ubiquitous structural relaxation of viscous supercooled
liquids, monohydroxy alcohols and several other hydrogen-bonded systems display
a strong single-exponential electrical low-frequency absorption. So far, this
so-called Debye process could be observed only using dielectric techniques.
Exploiting a combination of broad-band and high-resolution rheology experiments
for three isomeric octanols, unambiguous mechanical evidence for the Debye
process is found. Its spectral signature is similar to the viscoelastic
fingerprint of small-chain polymers, enabling us to estimate the effective
molecular weight for the supramolecular structure formed by the studied
monohydroxy alcohols. This finding opens the venue for the application of
further non-dielectric techniques directed at unraveling the microscopic nature
of the Debye process and for an understanding of this phenomenon in terms of
polymer concepts.


  We prove the ascending chain condition for log canonical thresholds of
bounded coregularity.


  We identify the coronal sources of the solar winds sampled by the ACE
spacecraft during 1999-2008, and examine the in situ solar wind properties as a
function of wind sources. The standard two-step mapping technique is adopted to
establish the photospheric footpoints of the magnetic flux tubes along which
the ACE winds flow. The footpoints are then placed in the context of EIT
284~\AA\ images and photospheric magnetograms, allowing us to categorize the
sources into four groups: coronal holes (CHs), active regions (ARs), the quiet
Sun (QS), and "Undefined". This practice also enables us to establish the
response to solar activity of the fractions occupied by each kind of solar
winds, and of their speeds and O$^{7+}$/O$^{6+}$ ratios measured in situ. We
find that during the maximum phase, the majority of ACE winds originate from
ARs. During the declining phase, CHs and ARs are equally important contributors
to the ACE solar winds. The QS contribution increases with decreasing solar
activity, and maximizes in the minimum phase when QS appear to be the primary
supplier of the ACE winds. With decreasing activity, the winds from all sources
tend to become cooler, as represented by the increasingly low O$^{7+}$/O$^{6+}$
ratios. On the other hand, during each activity phase, the AR winds tend to be
the slowest and associated with the highest O$^{7+}$/O$^{6+}$ ratios, and the
CH winds correspond to the other extreme, with the QS winds lying in between.
Applying the same analysis method to the slow winds only, here defined as the
winds with speeds lower than 500 km s$^{-1}$, we find basically the same
overall behavior, as far as the contributions of individual groups of sources
are concerned. This statistical study indicates that QS regions are an
important source of the solar wind during the minimum phase.


  In relation to the BSSN formulation of the Einstein equations, we write down
the boundary conditions that result from the vanishing of the projection of the
Einstein tensor normally to a timelike hypersurface. Furthermore, by setting up
a well-posed system of propagation equations for the constraints, we show
explicitly that there are three constraints that are incoming at the boundary
surface and that the boundary equations are linearly related to them. This
indicates that such boundary conditions play a role in enforcing the
propagation of the constraints in the region interior to the boundary.
Additionally, we examine the related problem for a strongly hyperbolic
first-order reduction of the BSSN equations and determine the characteristic
fields that are prescribed by the three boundary conditions, as well as those
that are left arbitrary.


  Artificial lattices created by assembling atoms on a surface with scanning
tunneling microscopy present a platform to create matter with tailored
electronic, magnetic and topological properties. However, such artificial
lattices studies to date have focused exclusively on surfaces with weak
spin-orbit coupling. Here, we created artificial and coupled quantum dots by
fabricating quantum corrals from iron atoms on the prototypical Rashba surface
alloy, BiCu2, using low-temperature scanning tunneling microscopy. We
quantified the quantum confinement of such quantum dots with various diameter
and related this to the spatially dependent density of states, using scanning
tunneling spectroscopy. We found that the density of states shows complex
distributions beyond the typical isotropic patterns seen in radially symmetric
structures on (111) noble metal surfaces. We related these to the
energy-dependent interplay of the confinement potential with the hexagonal
warping and multiple intra- and interband scattering vectors, which we
simulated with a particle-in-a-box model that considers the Rashba-type band
structure of BiCu2. Based on these results, we studied the effect of coupling
two quantum dots and exploited the resultant anisotropic coupling derived from
the symmetry of the various scattering channels. The large anisotropy and
spin-orbit coupling provided by the BiCu2 platform are two key ingredients
toward creation of correlated artificial lattices with non-trivial topology.


  The finite-density and finite-temperature phase portraits of the baby-Skyrme
and Skyrme models are investigated. Both grand-canonical and canonical
approaches are employed. The grand-canonical approach can be used to find the
``natural'' crystal structure of the baby-Skyrme model and it is shown to have
triangular symmetry. The phase portraits include solid, liquid and
phase-coexistence between solids and vacuum states. Furthermore, a chiral phase
transition can be observed for both models. The phase portrait of the Skyrme
model is compared with that expected of strongly interacting matter, and we
also contrast our results to other models.


  RW Aur is a young binary star that experienced a deep dimming in 2010-11 in
component A and a second even deeper dimming from summer 2014 to summer 2016.
We present new unresolved multi-band photometry during the 2014-16 eclipse, new
emission line spectroscopy before and during the dimming, archive infrared
photometry between 2014-15, as well as an overview of literature data.
  Spectral observations were carried out with the Fibre-fed RObotic Dual-beam
Optical Spectrograph on the Liverpool Telescope. Photometric monitoring was
done with the Las Cumbres Observatory Global Telescope Network and James
Gregory Telescope. Our photometry shows that RW Aur dropped in brightness to R
= 12.5 in March 2016. In addition to the long-term dimming trend, RW Aur is
variable on time scales as short as hours. The short-term variation is most
likely due to an unstable accretion flow. This, combined with the presence of
accretion-related emission lines in the spectra suggest that accretion flows in
the binary system are at least partially visible during the eclipse.
  The equivalent width of [O I] increases by a factor of ten in 2014,
coinciding with the dimming event, confirming previous reports. The
blue-shifted part of the $H\alpha$ profile is suppressed during the eclipse. In
combination with the increase in mid-infrared brightness during the eclipse
reported in the literature and seen in WISE archival data, and constraints on
the geometry of the disk around RW Aur A we arrive at the conclusion that the
obscuring screen is part of a wind emanating from the inner disk.


  Unfaulting of Frank loops in irradiated fluoride oxides are of significance
to microstructural evolution. However, the mechanisms have not been directly
observed. To this end, we utilize molecular dynamics to reveal the atomistic
details related to the unfaulting process of interstitial Frank loop in
ThO$_2$, which involve nucleation of single or multiple Shockley partial pairs
at the loop circumference. The unfaulting is achieved via a synchronous shear
of the partial pairs to remove the extrinsic stacking fault in the cation
sublattice and the intrinsic stacking fault in the anion sublattice. The strong
oxygen motion at the dislocation core may reduce the activation barriers of
dislocation nucleation and migration. These findings provide a fundamental
understanding of the transformation of faulted loops in irradiated ThO$_2$, and
could be transferable to other fluorite systems.


  We explore magnetic behavior of kagome francisites Cu3Bi(SeO3)2O2X (X = Cl
and Br) using first-principles calculations. To this end, we propose an
approach based on the Hubbard model in the Wannier functions basis constructed
on the level of local-density approximation (LDA). The ground-state spin
configuration is determined by a Hartree-Fock solution of the Hubbard model
both in zero magnetic field and in applied magnetic fields. Additionally,
parameters of an effective spin Hamiltonian are obtained by taking into account
the hybridization effects and spin-orbit coupling. We show that only the former
approach, the Hartree-Fock solution of the Hubbard model, allows for a complete
description of the anisotropic magnetization process. While our calculations
confirm that the canted zero-field ground state arises from a competition
between ferromagnetic nearest-neighbor and antiferromagnetic
next-nearest-neighbor couplings in the kagome planes, weaker anisotropic terms
are crucial for fixing spin directions and for the overall magnetization
process. We thus show that the Hartree-Fock solution of an electronic
Hamiltonian is a viable alternative to the analysis of effective spin
Hamiltonians when a magnetic ground state and effects of external field are
considered.


  One practice of employing deep neural networks is to apply the same
architecture to all the input instances. However, a fixed architecture may not
be representative enough for data with high diversity. To promote the model
capacity, existing approaches usually employ larger convolutional kernels or
deeper network structure, which may increase the computational cost. In this
paper, we address this issue by raising the Dynamic Graph Network (DG-Net). The
network learns the instance-aware connectivity, which creates different forward
paths for different instances. Specifically, the network is initialized as a
complete directed acyclic graph, where the nodes represent convolutional blocks
and the edges represent the connection paths. We generate edge weights by a
learnable module \textit{router} and select the edges whose weights are larger
than a threshold, to adjust the connectivity of the neural network structure.
Instead of using the same path of the network, DG-Net aggregates features
dynamically in each node, which allows the network to have more representation
ability. To facilitate the training, we represent the network connectivity of
each sample in an adjacency matrix. The matrix is updated to aggregate features
in the forward pass, cached in the memory, and used for gradient computing in
the backward pass. We verify the effectiveness of our method with several
static architectures, including MobileNetV2, ResNet, ResNeXt, and RegNet.
Extensive experiments are performed on ImageNet classification and COCO object
detection, which shows the effectiveness and generalization ability of our
approach.


  We have searched for proton decays into a charged antilepton ($e^+$, $\mu^+$)
plus a meson ($\eta$, $\rho^0$, $\omega$) and neutron decays into a charged
antilepton ($e^+$, $\mu^+$) plus a meson ($\pi^-$, $\rho^-$) using
Super-Kamiokande (SK) I-IV data, corresponding to 0.316 megaton$\cdot$years of
exposure. This measurement updates the previous published result by using 2.26
times more data and improved analysis methods. No significant evidence for
nucleon decay has been observed and lower limits on the partial lifetime of the
nucleon are obtained. The limits range from 3$\times$10$^{31}$ to
1$\times$10$^{34}$ years at 90% confidence level, depending on the decay mode.


  We study properties of thermal transport and quantum many-body chaos in a
lattice model with $N\to\infty$ oscillators per site, coupled by strong
anharmonic terms. We first consider a model with only optical phonons. We find
that the thermal diffusivity $D_{\rm th}$ and chaos diffusivity $D_L$ (defined
as $D_L = v_B^2/ \lambda_L$, where $v_B$ and $\lambda_L$ are the butterfly
velocity and the scrambling rate, respectively) satisfy $D_{\rm th} \approx
\gamma D_L$ with $\gamma\gtrsim 1$. At intermediate temperatures, the model
exhibits a "quantum phonon fluid" regime, where both diffusivities satisfy
$D^{-1} \propto T$, and the thermal relaxation time and inverse scrambling rate
are of the order the of Planckian timescale $\hbar/k_B T$. We then introduce
acoustic phonons to the model and study their effect on transport and chaos.
The long-wavelength acoustic modes remain long-lived even when the system is
strongly coupled, due to Goldstone's theorem. As a result, for $d=1,2$, we find
that $D_{\rm th}/D_L\to \infty$, while for $d=3$, $D_{\rm th}$ and $D_{L}$
remain comparable.


  With the increased dependence on software, there is a pressing need for
engineering long-lived software. As architectures have a profound effect on the
life-span of the software and the provisioned quality of service, stable
architectures are significant assets. Architectural stability tends to reflect
the success of the system in supporting continuous changes without phasing-out.
The \textit{behavioural} aspect of stability is essential for seamless
operation, to continuously keep the provision of quality requirements stable
and prevent architecture's drifting and phasing-out. In this paper, we present
a framework for reasoning about stability during runtime, leveraging on
self-awareness principles. Specifically, we employ runtime goals for managing
stability goals, online learning for reasoning about stability on the long-run,
and stochastic games for managing associated trade-offs. We evaluate the
proposed work using the case of cloud architectures for its highly dynamics
during runtime. The experimental results have shown the efficiency of
self-awareness techniques in realising the expected behaviour stable during
runtime operation.


  We study non-episodic Reinforcement Learning for Lipschitz MDPs in which
state-action space is a metric space, and the transition kernel and rewards are
Lipschitz functions. We develop computationally efficient UCB-based algorithm,
$\textit{ZoRL-}\epsilon$ that adaptively discretizes the state-action space and
show that their regret as compared with $\epsilon$-optimal policy is bounded as
$\mathcal{O}(\epsilon^{-(2 d_\mathcal{S} + d^\epsilon_z + 1)}\log{(T)})$, where
$d^\epsilon_z$ is the $\epsilon$-zooming dimension. In contrast, if one uses
the vanilla $\textit{UCRL-}2$ on a fixed discretization of the MDP, the regret
w.r.t. a $\epsilon$-optimal policy scales as $\mathcal{O}(\epsilon^{-(2
d_\mathcal{S} + d + 1)}\log{(T)})$ so that the adaptivity gains are huge when
$d^\epsilon_z \ll d$. Note that the absolute regret of any 'uniformly good'
algorithm for a large family of continuous MDPs asymptotically scales as at
least $\Omega(\log{(T)})$. Though adaptive discretization has been shown to
yield $\mathcal{\tilde{O}}(H^{2.5}K^\frac{d_z + 1}{d_z + 2})$ regret in
episodic RL, an attempt to extend this to the non-episodic case by employing
constant duration episodes whose duration increases with $T$, is futile since
$d_z \to d$ as $T \to \infty$. The current work shows how to obtain adaptivity
gains for non-episodic RL. The theoretical results are supported by simulations
on two systems where the performance of $\textit{ZoRL-}\epsilon$ is compared
with that of '$\textit{UCRL-C}$,' the fixed discretization-based extension of
$\textit{UCRL-}2$ for systems with continuous state-action spaces.


  Short duration gamma-ray bursts (SGRBs) are thought to be related to the
violent merger of compact objects, such as neutron stars or black holes, which
makes them promising sources of gravitational waves. The detection of a
'kilonova'-like signature associated to the Swift-detected GRB 130603B has
suggested that this event is the result of a compact object merger. Our
knowledge on SGRB has been, until now, mostly based on the absence of supernova
signatures and the analysis of the host galaxies to which they cannot always be
securely associated. Further progress has been significantly hampered by the
faintness and rapid fading of their optical counterparts (afterglows), which
has so far precluded spectroscopy of such events. Afterglow spectroscopy is the
key tool to firmly determine the distance at which the burst was produced,
crucial to understand its physics, and study its local environment. Here we
present the first spectra of a prototypical SGRB afterglow in which both
absorption and emission features are clearly detected. Together with
multiwavelength photometry we study the host and environment of GRB 130603B.
From these spectra we determine the redshift of the burst to be z =
0.3565+/-0.0002, measure rich dynamics both in absorption and emission, and a
substantial line of sight extinction of A_V = 0.86+/-0.15 mag. The GRB was
located at the edge of a disrupted arm of a moderately star forming galaxy with
near-solar metallicity. Unlike for most long GRBs (LGRBs), N_HX / A_V is
consistent with the Galactic ratio, indicating that the explosion site differs
from those found in LGRBs. The merger is not associated with the most
star-forming region of the galaxy; however, it did occur in a dense region,
implying a rapid merger or a low natal kick velocity for the compact object
binary.


  In 1995 Kim famously proved the Ramsey bound R(3,t) \ge c t^2/\log t by
constructing an n-vertex graph that is triangle-free and has independence
number at most C \sqrt{n \log n}. We extend this celebrated result, which is
best possible up to the value of the constants, by approximately decomposing
the complete graph K_n into a packing of such nearly optimal Ramsey R(3,t)
graphs.
  More precisely, for any \epsilon>0 we find an edge-disjoint collection
(G_i)_i of n-vertex graphs G_i \subseteq K_n such that (a) each G_i is
triangle-free and has independence number at most C_\epsilon \sqrt{n \log n},
and (b) the union of all the G_i contains at least (1-\epsilon)\binom{n}{2}
edges. Our algorithmic proof proceeds by sequentially choosing the graphs G_i
via a semi-random (i.e., Rodl nibble type) variation of the triangle-free
process.
  As an application, we prove a conjecture in Ramsey theory by Fox, Grinshpun,
Liebenau, Person, and Szabo (concerning a Ramsey-type parameter introduced by
Burr, Erdos, Lovasz in 1976). Namely, denoting by s_r(H) the smallest minimum
degree of r-Ramsey minimal graphs for H, we close the existing logarithmic gap
for H=K_3 and establish that s_r(K_3) = \Theta(r^2 \log r).


  Surface wave patterns are investigated experimentally in a system geometry
that has become a paradigm of quantum chaos: the stadium billiard. Linear waves
in bounded geometries for which classical ray trajectories are chaotic are
known to give rise to scarred patterns. Here, we utilize parametrically forced
surface waves (Faraday waves), which become progressively nonlinear beyond the
wave instability threshold, to investigate the subtle interplay between
boundaries and nonlinearity. Only a subset (three main types) of the computed
linear modes of the stadium are observed in a systematic scan. These correspond
to modes in which the wave amplitudes are strongly enhanced along paths
corresponding to certain periodic ray orbits. Many other modes are found to be
suppressed, in general agreement with a prediction by Agam and Altshuler based
on boundary dissipation and the Lyapunov exponent of the associated orbit.
Spatially asymmetric or disordered (but time-independent) patterns are also
found even near onset. As the driving acceleration is increased, the
time-independent scarred patterns persist, but in some cases transitions
between modes are noted. The onset of spatiotemporal chaos at higher forcing
amplitude often involves a nonperiodic oscillation between spatially ordered
and disordered states. We characterize this phenomenon using the concept of
pattern entropy. The rate of change of the patterns is found to be reduced as
the state passes temporarily near the ordered configurations of lower entropy.
We also report complex but highly symmetric (time-independent) patterns far
above onset in the regime that is normally chaotic.


  The transition metal dichalcogenide 1T-TaS2 attract growing attention because
of the formation of rich density-wave (DW) and superconducting transitions.
However, the origin of the incommensurate DW state at the highest temperature
(~ 550 K), which is "the parent state" of the rich physical phenomena, is still
uncovered. Here, we present a natural explanation for the triple-q
incommensurate DW in 1T-TaS2 based on the first-principles Hubbard model with
on-site U. We apply the paramagnon interference mechanism that gives the
nematic order in Fe-based superconductors. The derived order parameter has very
unique characters: (i) the orbital-selective nature, and (ii) the
unconventional sign-reversal in both momentum and energy spaces. The present
study will be useful for understanding rich physics in 1T-TaS2, 1T-VSe2, and
other transition metal dichalcogenides.


  We present high-precision experimental and numerical studies of the Nusselt
number $Nu$ as functions of the Rayleigh number $Ra$ in geostrophic rotating
convection with domain aspect ratio ${\Gamma}$ varying from 0.4 to 3.8 and the
Ekman number Ek from $2.0{\times}10^{-7}$ to $2.7{\times}10^{-5}$. The
heat-transport data $Nu(Ra)$ reveal a gradual transition from
buoyancy-dominated to geostrophic convection at large $Ek$, whereas the
transition becomes sharp with decreasing $Ek$. We determine the power-law
scaling of $Nu{\sim}Ra^{\gamma}$, and show that the boundary flows give rise to
pronounced enhancement of $Nu$ in a broad range of the geostrophic regime,
leading to reduction of the scaling exponent ${\gamma}$ in small ${\Gamma}$
cells. The present work provides new insight into the heat-transport scaling in
geostrophic convection and may explain the discrepancies observed in previous
studies.


  We study nonleptonic Lambda_b -> Lambda_c pi, Sigma_c pi and Sigma_c^* pi
decays in the limit m_b, m_c, E_pi >> Lambda_{QCD} using the soft-collinear
effective theory. Here Sigma_c = Sigma_c(2455) and Sigma_c^* = Sigma_c(2520).
At leading order the Lambda_b -> Sigma_c^{(*)} pi rates vanish, while the
Lambda_b -> Lambda_c pi rate is related to Lambda_b -> Lambda_c\ell\bar\nu, and
is expected to be larger than Gamma(B -> D^{(*)} pi). The dominant
contributions to the Lambda_b -> Sigma_c^{(*)} pi rates are suppressed by
Lambda_{QCD}^2/E_pi^2. We predict Gamma(Lambda_b -> Sigma_c^* pi) /
Gamma(Lambda_b -> Sigma_c pi) = 2 + O[Lambda_{QCD}/m_Q, alpha_s(m_Q)], and the
same ratio for Lambda_b -> Sigma_c^{(*)} rho and for Lambda_b -> Xi_c^{(',*)}K.
``Bow tie'' diagrams are shown to be suppressed. We comment on possible
discovery channels for weakly decaying pentaquarks, Theta_{b,c} and their
nearby heavy quark spin symmetry partners, Theta_{b,c}^*.


  A computer-assisted argument is given, which provides existence proofs for
periodic orbits in state-dependent delayed perturbations of ordinary
differential equations (ODEs). Assuming that the unperturbed ODE has an
isolated periodic orbit, we introduce a set of polynomial inequalities whose
successful verification leads to the existence of periodic orbits in the
perturbed delay equation. We present a general algorithm, which describes a way
of computing the coefficients of the polynomials and optimizing their variables
so that the polynomial inequalities are satisfied. The algorithm uses the tools
of validated numerics together with Chebyshev series expansion to obtain the
periodic orbit of the ODE as well as the solution of the variational equations,
which are both used to compute rigorously the coefficients of the polynomials.
We apply our algorithm to prove the existence of periodic orbits in a
state-dependent delayed perturbation of the van der Pol equation.


  We study the interplay between the chiral and the deconfinement transitions,
both at high temperature and high quark chemical potential, by a non local
Nambu-Jona Lasinio model with the Polyakov loop in the mean field approximation
and requiring neutrality of the ground state. We consider three forms of the
effective potential of the Polyakov loop: two of them with a fixed
deconfinement scale, cases I and II, and the third one with a $\mu$ dependent
scale, case III. In the cases I and II, at high chemical potential $\mu$ and
low temperature $T$ the main contribution to the free energy is due to the
Z(3)-neutral three-quark states, mimicking the quarkyonic phase of the large
$N_c$ phase diagram. On the other hand in the case III the quarkyonic window is
shrunk to a small region. Finally we comment on the relations of these results
to lattice studies and on possible common prospects. We also briefly comment on
the coexistence of quarkyonic and color superconductive phases.


  As machine learning models are increasingly deployed in dynamic environments,
it becomes paramount to assess and quantify uncertainties associated with
distribution shifts. A distribution shift occurs when the underlying
data-generating process changes, leading to a deviation in the model's
performance. The prediction interval, which captures the range of likely
outcomes for a given prediction, serves as a crucial tool for characterizing
uncertainties induced by their underlying distribution. In this paper, we
propose methodologies for aggregating prediction intervals to obtain one with
minimal width and adequate coverage on the target domain under unsupervised
domain shift, under which we have labeled samples from a related source domain
and unlabeled covariates from the target domain. Our analysis encompasses
scenarios where the source and the target domain are related via i) a bounded
density ratio, and ii) a measure-preserving transformation. Our proposed
methodologies are computationally efficient and easy to implement. Beyond
illustrating the performance of our method through a real-world dataset, we
also delve into the theoretical details. This includes establishing rigorous
theoretical guarantees, coupled with finite sample bounds, regarding the
coverage and width of our prediction intervals. Our approach excels in
practical applications and is underpinned by a solid theoretical framework,
ensuring its reliability and effectiveness across diverse contexts.


  The idea of neural Ordinary Differential Equations (ODE) is to approximate
the derivative of a function (data model) instead of the function itself. In
residual networks, instead of having a discrete sequence of hidden layers, the
derivative of the continuous dynamics of hidden state can be parameterized by
an ODE. It has been shown that this type of neural network is able to produce
the same results as an equivalent residual network for image classification. In
this paper, we design a novel neural ODE for the semantic segmentation task. We
start by a baseline network that consists of residual modules, then we use the
modules to build our neural ODE network. We show that our neural ODE is able to
achieve the state-of-the-art results using 57% less memory for training, 42%
less memory for testing, and 68% less number of parameters. We evaluate our
model on the Cityscapes, CamVid, LIP, and PASCAL-Context datasets.


  We consider the evolution of $N$ bosons interacting with a repulsive short
range pair potential in three dimensions. The potential is scaled according to
the Gross-Pitaevskii scaling, i.e. it is given by $N^2V(N(x_i-x_j))$. We
monitor the behavior of the solution to the $N$-particle Schr\"odinger equation
in a spatial window where two particles are close to each other. We prove that
within this window a short scale interparticle structure emerges dynamically.
The local correlation between the particles is given by the two-body zero
energy scattering mode. This is the characteristic structure that was expected
to form within a very short initial time layer and to persist for all later
times, on the basis of the validity of the Gross-Pitaevskii equation for the
evolution of the Bose-Einstein condensate. The zero energy scattering mode
emerges after an initial time layer where all higher energy modes disperse out
of the spatial window. We can prove the persistence of this structure up to
sufficiently small times before three-particle correlations could develop.


  We measured the proper motion of a $\gamma$-ray radio-quiet pulsar J0633+0632
using Chandra observations performed in 2009 and 2017. The measured proper
motion is $53\pm15$~mas~yr$^{-1}$. We found that the proper motion direction
does not follow the extension of the J0633+0632 pulsar wind nebula. The
J0633+0632 pulsar wind nebula therefore can be a jet-like feature or a
misaligned outflow. We also discuss a possible birth cite of the pulsar.


  The Ginzburg-Landau theory of a trapped Fermi gas with a BEC-BCS crossover is
derived by the path-integral method. In addition to the standard
Ginzburg-Landau equation, a second equation describing the total atom density
is obtained. These two coupled equations are necessary to describe both
homogeneous and inhomogeneous systems. The Ginzburg-Landau theory is valid near
the transition temperature $T_c$ on both sides of the crossover. In the
weakly-interacting BEC region, it is also accurate at zero temperature where
the Ginzburg-Landau equation can be mapped onto the Gross-Pitaevskii (GP)
equation. The applicability of GP equation at finite temperature is discussed.
On the BEC side, the fluctuation of the order parameter is studied and the
renormalization to the molecule coupling constant is obtained.


  An ab-initio analysis based on coupled mode theory (CMT) is applied to
describe the interaction dynamics of high dielectric resonators (DRs) with its
containing aqueous solution. We prove that the coupling mechanism is
reciprocal. Such property is exploited to find closed form and accurate
expressions of the coupling coefficient, the main factor characterizing the
system performance. Based on such expressions, it is shown that, for wireless
power transfer (WPT) applications, up sizing the DRs relaxes the need of using
ultra high dielectric constant materials. The nature of interaction is captured
by the coupling matrix, which shows that the behaviour of the system is
identical to the ones studied extensively in the literature when the contained
aqueous solution is replaced by an enclosing cavity. It follows, as in a
typical three coupled resonators setting, that when two DRs are inserted in the
aqueous solution a non-bonding mode emerges; hence enabling efficient wireless
power transfer (WPT) via the opening of an electromagnetic induced transparency
like window. Due to the inevitable situations where the DRs are not
symmetrically placed inside the solution, the general eigenvalue problem, with
asymmetrically placed DR inserts is solved and the eigenvectors representing
the coupled modes are depicted by vectors in a 3D mathematical space where the
uncoupled modes represent its basis. Moreover, the strong coupling between the
DR inserts and the aqueous medium allows the proposed WPT system to tolerate
intrinsic aqueous solution losses and the presence of extraneous objects.
Additionally, the value of the load at maximum efficiency is independent of the
aqueous solution loss tangent, thus tolerating the variation of the medium
salinity. The Proposed EIT like scheme can find applications for mid/short
range power transfer in/through swimming pools, chemical reactors, fish tanks,
etc.


  In this paper we simulate the emission by charged particles in complex
structures with help of Geant4. We take into account Cherenkov radiation,
transition radiation, bremsstrahlung, pair production and other accompanying
processes. As an application we investigate the full size electromagnetic
calorimeter for the muon g-2 experiment at Fermilab. A calorimeter module (24
are expected in the experiment) consists of a Delrin front panel for
installation of the laser calibration system, 54 PbF2 Cherenkov crystals
wrapped by the black Millipore paper, and silicon photo-multiplier sensors. We
report here on a simulation of radiation from positrons passing through the
calorimeter system. We carry out the simulation using Geant4 toolkit, which
provides a complete set of tools for all areas of detector simulation:
geometry, tracking, detector response, run, event and track management, and
visualization. We consider Cherenkov photons expansion when a positron moves
down through the calorimeter at the arbitrary angle of incidence. Both spectral
and angular distributions of Cherenkov optical photons in different parts of
the calorimeter system have been evaluated as well as the transition radiation
and pre-shower distributions from the panel and from the Al vacuum chamber of
the storage ring. (The paper is in progress).


  In this paper, we present ManyTypes4Py, a large Python dataset for machine
learning (ML)-based type inference. The dataset contains a total of 5,382
Python projects with more than 869K type annotations. Duplicate source code
files were removed to eliminate the negative effect of the duplication bias. To
facilitate training and evaluation of ML models, the dataset was split into
training, validation and test sets by files. To extract type information from
abstract syntax trees (ASTs), a lightweight static analyzer pipeline is
developed and accompanied with the dataset. Using this pipeline, the collected
Python projects were analyzed and the results of the AST analysis were stored
in JSON-formatted files. The ManyTypes4Py dataset is shared on zenodo and its
tools are publicly available on GitHub.


  Heavy sterile neutrinos with masses ${\mathcal O}(100)$ MeV mixing with
active neutrinos can be produced in the core of a collapsing supernova (SN). In
order to avoid an excessive energy loss, shortening the observed duration of
the SN 1987A neutrino burst, we show that the active-sterile neutrino mixing
angle should satisfy $\sin^2 \theta \lesssim 5 \times 10^{-7}$. For a mixing
with tau flavour, this bound is much stronger than the ones from laboratory
searches. Moreover, we show that in the viable parameter space the decay of
such "heavy" sterile neutrinos in the SN envelope would lead to a very
energetic flux of daughter active neutrinos; if not too far below current
limits, this would be detectable in large underground neutrino observatories,
like Super-Kamiokande, as a (slightly time-delayed) high-energy bump in the
spectrum of a forthcoming Galactic SN event.


  The existence of Majorana neutrinos must lead to lepton-number violating
processes, and the Majorana nature of neutrinos can only be experimentally
verified via lepton-number violating processes. We propose a new approach to
search for Majorana neutrinos at future electron-positron colliders by
exploiting this feature. We investigate the $\Delta L = 2$ like-sign dilepton
production and find that lepton colliders with different center-of-mass
energies have comparative advantages in resonant production of a Majorana
neutrino in either light neutrino mass range or heavy mass range. At the future
Circular Electron-Positron Collider (CEPC), with 250 GeV center-of-mass energy
and 5 ab$^{-1}$ integrated luminosity, we find that there could be more
significant sensitivity for resonant production of a Majorana neutrino in the
mass range of 5-80 GeV than previous results at LEP2 or LHC. At the 1 TeV ILC
with 1 ab$^{-1}$ integrated luminosity, it has better sensitivity than the
similar process at LHC while the neutrino mass is larger than 250 GeV.