  Different approaches have been applied to the calculation of form factors of
various hadronic systems within relativistic quantum mechanics. In a one-body
current approximation, they can lead to results evidencing large discrepancies.
Looking for an explanation of this spreading, it is shown that, for the largest
part, these discrepancies can be related to a violation of Poincar\'e
space-time translation invariance. Beyond energy-momentum conservation, which
is generally assumed, fulfilling this symmetry implies specific relations that
are generally ignored. Their relevance within the present context is discussed
in detail both to explain the differences between predictions and to remove
them.


  Causal models with unobserved variables impose nontrivial constraints on the
distributions over the observed variables. When a common cause of two variables
is unobserved, it is impossible to uncover the causal relation between them
without making additional assumptions about the model. In this work, we
consider causal models with a promise that unobserved variables have known
cardinalities. We derive inequality constraints implied by d-separation in such
models. Moreover, we explore the possibility of leveraging this result to study
causal influence in models that involve quantum systems.


  Necessary and sufficient conditions for when every non-zero ideal in a
relative Cuntz-Pimsner ring contains a non-zero graded ideal, when a relative
Cuntz-Pimsner ring is simple, and when every ideal in a relative Cuntz-Pimsner
ring is graded, are given. A "Cuntz-Krieger uniqueness theorem" for relative
Cuntz-Pimsner rings is also given and condition (L) and condition (K) for
relative Cuntz-Pimsner rings are introduced.


  In this paper, we construct codes for local recovery of erasures with high
availability and constant-bounded rate from the Hermitian curve. These new
codes, called Hermitian-lifted codes, are evaluation codes with evaluation set
being the set of $\mathbb{F}_{q^2}$-rational points on the affine curve. The
novelty is in terms of the functions to be evaluated; they are a special set of
monomials which restrict to low degree polynomials on lines intersected with
the Hermitian curve. As a result, the positions corresponding to points on any
line through a given point act as a recovery set for the position corresponding
to that point.


  We consider the system of particles with equal charges and nearest neighbour
Coulomb interaction on the interval. We study local properties of this system,
in particular the distribution of distances between neighbouring charges. For
zero temperature case there is sufficiently complete picture and we give a
short review. For Gibbs distribution the situation is more difficult and we
present two related results.


  The general framework of diffractive deep inelastic scattering is introduced
and reports given in the session on diffractive interactions at the
International Workshop on Deep-Inelastic Scattering and Related Phenomena,
Rome, April 1996, are presented.


  A novel method for the production of important medical radioisotopes has been
developed. The approach is based on performing the nuclear reaction in inverse
kinematics, namely sending a heavy-ion beam of appropriate energy on a light
target (e.g. H, d, He) and collecting the isotope of interest. In this work, as
a proof-of-concept, we studied the production of the theranostic radionuclide
67Cu (T 1/2 =62 h) via the reaction of a 70Zn beam at 15 MeV/nucleon with a
hydrogen gas target. The 67Cu radionuclide, alongside other coproduced
isotopes, was collected after the gas target on an Al catcher foil and their
radioactivity was measured by off-line {\gamma}-ray analysis. After 36 h from
the end of the irradiation, apart from the product of interest 67Cu, the main
radioimpurity coming from the 70Zn+p reaction was 69mZn (T 1/2 =13.8 h) that
can be reduced by further radio-cooling. Moreover, along with the radionuclide
of interest produced in inverse kinematics, the production of additional
radioisotopes is possible by making use of the forward-focused neutrons from
the reaction and letting them interact with a secondary target. A preliminary
successful test of this concept was realized in the present study. The main
requirement to obtain activities appropriate for preclinical studies is the
development of high-intensity heavy-ion primary beams.


  Using the notions of Topological dynamics, H. Furstenberg defined central
sets and proved the Central Sets Theorem. Later V. Bergelson and N. Hindman
characterized central sets in terms of algebra of the Stone-\v{C}ech
compactification of discrete semigroup. They found that central sets are the
members of the minimal idempotents of \b{eta}S, the Stone-\v{C}ech
compactification of a semigroup (S, .). Hindman and leader introduced the
notion of Central set near zero algebraically. Later dynamical and
combinatorial characterization have also been established. For any given filter
F in S a set A is said to be a F- central set if it is a member of a minimal
idempotent of a closed subsemigroup of \b{eta}S, generated by the filter F. In
a recent article Bergelson, Hindman and Strauss introduced strongly central and
very strongly central sets in [BHS]. They also dynamically characterized the
sets in the same paper. In the present article we will characterize the
strongly F- central sets dynamically and combinatorially. Here we introduce the
filter version of strongly central sets and very strongly central sets. We also
provide dynamical and combinatorial characterization of such sets.


  In [Ann. Math. 190 (2019), 657-661], James Hyde presented the first example
of non-left-orderable, finitely generated subgroup of
$\mathrm{Homeo}(D,\partial D)$, the group of homeomorphisms of the disk fixing
the boundary. This implies that the group $\mathrm{Homeo}(D,\partial D)$ itself
is not left-orderable. We revisit the construction, and present a slightly
different proof of purely dynamical flavor, avoiding direct references to
properties of left-orders. Our approach allows to solve the analogue problem
for actions on the circle.


  We present an analysis of multi-epoch low-resolution spectrophotometry,
complemented by the light curves provided by massive photometric surveys
spanning over 100 years, of the symbiotic binary LMC S63. We showed that it is
an eclipsing binary with the orbital period of 1050d. We also found evidence of
outbursts in history of the white dwarf. If it was a Z-And type outburst, as is
most likely, it would be a second such outburst recorded in the Magellanic
Cloud symbiotic system. We confirmed that the red giant is enhanced in carbon,
and estimated C/O~1.2 by fitting a model atmosphere to the SALT spectrum. We
also found bi-periodic pulsations of the red giant, and demonstrated that it is
similar to other carbon variables with confirmed bi-periodicity.


  In the contemporary digital landscape, the continuous generation of extensive
streaming data across diverse domains has become pervasive. Yet, a significant
portion of this data remains unlabeled, posing a challenge in identifying
infrequent events such as anomalies. This challenge is further amplified in
non-stationary environments, where the performance of models can degrade over
time due to concept drift. To address these challenges, this paper introduces a
new method referred to as VAE4AS (Variational Autoencoder for Anomalous
Sequences). VAE4AS integrates incremental learning with dual drift detection
mechanisms, employing both a statistical test and a distance-based test. The
anomaly detection is facilitated by a Variational Autoencoder. To gauge the
effectiveness of VAE4AS, a comprehensive experimental study is conducted using
real-world and synthetic datasets characterized by anomalous rates below 10\%
and recurrent drift. The results show that the proposed method surpasses both
robust baselines and state-of-the-art techniques, providing compelling evidence
for their efficacy in effectively addressing some of the challenges associated
with anomalous sequence detection in non-stationary streaming data.


  To each function $f$ of bounded quadratic variation ($f\in V_2$) we associate
a Hausdorff measure $\mu_f$. We show that the map $f\to\mu_f$ is locally
Lipschitz and onto the positive cone of $\mathcal{M}[0,1]$. We use the measures
$\{\mu_f:f\in V_2\}$ to determine the structure of the subspaces of $V_2^0$
which either contain $c_0$ or the square stopping time space $S^2$.


  The pursuit of exotic phases of matter outside of the extreme conditions of a
quantizing magnetic field has been a long standing quest of solid state
physics. Recent experiments have observed spontaneous valley polarization and
fractional Chern insulators (FCIs) in zero magnetic field in twisted bilayers
of MoTe$_2$, at partial filling of the topological valence band ($\nu=-2/3$ and
$-3/5$). We study the topological valence band at $\textit{half}$ filling,
using exact diagonalization and density matrix renormalization group
calculations. We discover a composite Fermi liquid (CFL) phase even at zero
magnetic field that covers a large portion of the phase diagram centered around
twist angle ${\sim}3.6^\circ$. The CFL is a non-Fermi liquid phase that shows
metallic behavior despite the absence of Landau quasiparticles. We discuss
experimental implications including the competition between the CFL and a Fermi
liquid, which can be tuned with a displacement field. The topological valence
band has excellent quantum geometry over a wide range of twist angles and a
small bandwidth that is, remarkably, reduced by interactions for a range of
angles. These key properties are responsible for stabilizing the exotic quantum
Hall phases we find at zero field. Finally, we present an optical signature
involving "extinguished" optical responses as a means to identify Chern bands
with ideal quantum geometry.


  Let $P$ be a set of $n$ points in general position in the plane. A subset $I$
of $P$ is called an \emph{island} if there exists a convex set $C$ such that $I
= P \cap C$. In this paper we define the \emph{generalized island Johnson
graph} of $P$ as the graph whose vertex consists of all islands of $P$ of
cardinality $k$, two of which are adjacent if their intersection consists of
exactly $l$ elements. We show that for large enough values of $n$, this graph
is connected, and give upper and lower bounds on its diameter.


  Deep learning and reinforcement learning methods have been shown to enable
learning of flexible and complex robot controllers. However, the reliance on
large amounts of training data often requires data collection to be carried out
in simulation, with a number of sim-to-real transfer methods being developed in
recent years. In this paper, we study these techniques for tactile sensing
using the TacTip optical tactile sensor, which consists of a deformable tip
with a camera observing the positions of pins inside this tip. We designed a
model for soft body simulation which was implemented using the Unity physics
engine, and trained a neural network to predict the locations and angles of
edges when in contact with the sensor. Using domain randomisation techniques
for sim-to-real transfer, we show how this framework can be used to accurately
predict edges with less than 1 mm prediction error in real-world testing,
without any real-world data at all.


  The spontaneous evolution of magnetic reconnection in generalized situations
(with thermodynamic asymmetry regarding the current sheet and magnetic shear)
is investigated using two-dimensional magnetohydrodynamic simulation. We focus
on the asymptotic state of temporal evolution, i.e., the self-similarly
expanding phase (Nitta et al. 2001). 1) A long fast-mode shock is generated in
front of the shorter plasmoid as in the shear-less thermodynamically asymmetric
case; however, the sheared magnetic component weakens the shock. This fast
shock may work as a particle acceleration site. 2) The shorter plasmoid-side
plasma infiltrates the longer plasmoid across the current sheet. Then, the
plasmas from both sides of the current sheet coexist on the same magnetic field
lines in the longer plasmoid. This may result in efficient plasma mixing. 3)
The thermodynamic asymmetry and magnetic shear drastically decrease the
reconnection rate in many orders of magnitude.


  I analyze the topological structures generated by diffusion-limited
aggregation (DLA), using the recently developed "branched growth model". The
computed bifurcation number B for DLA in two dimensions is B ~ 4.9, in good
agreement with the numerically obtained result of B ~ 5.2. In high dimensions,
B -> 3.12; the bifurcation ratio is thus a decreasing function of
dimensionality. This analysis also determines the scaling properties of the
ramification matrix, which describes the hierarchy of branches.


  The Schwinger boson theory provides a natural path for treating quantum spin
systems with large quantum fluctuations. In contrast to semi-classical
treatments, this theory allows us to describe a continuous transition between
magnetically ordered and spin liquid states, as well as the continuous
evolution of the corresponding excitation spectrum. The square lattice
Heisenberg antiferromagnet is one of the first models that was approached with
the Schwinger boson theory. Here we revisit this problem to reveal several
subtle points that were omitted in previous treatments and that are crucial to
further develop this formalism. These points include the freedom for the choice
of the saddle point (Hubbard-Stratonovich decoupling and choice of the
condensate) and the $1/N$ expansion in the presence of a condensate. A key
observation is that the spinon condensate leads to Feynman diagrams that
include contributions of different order in $1/N$, which must be accounted to
get a qualitatively correct excitation spectrum. We demonstrate that a proper
treatment of these contributions leads to an exact cancellation of the
single-spinon poles of the dynamical spin structure factor, as expected for a
magnetically ordered state. The only surviving poles are the ones arising from
the magnons (two-spinon bound states), which are the true collective modes of
an ordered magnet.


  Process mining allows analysts to exploit logs of historical executions of
business processes to extract insights regarding the actual performance of
these processes. One of the most widely studied process mining operations is
automated process discovery. An automated process discovery method takes as
input an event log, and produces as output a business process model that
captures the control-flow relations between tasks that are observed in or
implied by the event log. Various automated process discovery methods have been
proposed in the past two decades, striking different tradeoffs between
scalability, accuracy and complexity of the resulting models. However, these
methods have been evaluated in an ad-hoc manner, employing different datasets,
experimental setups, evaluation measures and baselines, often leading to
incomparable conclusions and sometimes unreproducible results due to the use of
closed datasets. This article provides a systematic review and comparative
evaluation of automated process discovery methods, using an open-source
benchmark and covering twelve publicly-available real-life event logs, twelve
proprietary real-life event logs, and nine quality metrics. The results
highlight gaps and unexplored tradeoffs in the field, including the lack of
scalability of some methods and a strong divergence in their performance with
respect to the different quality metrics used.


  This paper is devoted to the study of stable radial solutions of $-\Delta
u=f(u) \mbox{ in } \mathbb{R}^N\setminus B_1=\{ x\in \mathbb{R}^N : \vert
x\vert\geq 1\}$, where $f\in C^1(\mathbb{R})$ and $N\geq 2$. We prove that such
solutions are either large [in the sense that $\vert u(r)\vert \geq M
r^{-N/2+\sqrt{N-1}+2}\ $, if $2\leq N\leq 9$; $\vert u(r)\vert \geq M \log (r)\
$, if $N=10$; $\vert u(r)-u_\infty \vert \geq M r^{\-N/2+\sqrt{N-1}+2}\ $, if
$N\geq 11$; $\forall r\geq r_0$, for some $M>0$, $r_0\geq 1$] or small [in the
sense that $\vert u(r)\vert \leq M\log (r)\ $, if $N=2$; $\vert u(r)-u_\infty
\vert \leq M r^{\-N/2-\sqrt{N-1}+2}$;\, if $N\geq 3$; $\forall r\geq 2$, for
some $M>0$], where $u_\infty=\lim_{r\rightarrow \infty}u(r)\in
[-\infty,+\infty]$. These results can be applied to stable outside a compact
set radial solutions of equations of the type $-\Delta u=g(u) \mbox{ in }
\mathbb{R}^N$. We prove also the optimality of these results, by considering
solutions of the form $u(r)=r^\alpha$ or $u(r)=\log (r)$, $\forall r\geq 1$,
where $\alpha \in \mathbb{R} \setminus \{ 0\}$.


  A condition for the synchronizability of a pair of PDE systems, coupled
through a finite set of variables, is commonly the existence of internal
synchronization or internal coherence in each system separately. The condition
was previously illustrated in a forced-dissipative system, and is here extended
to Hamiltonian systems, using an example from particle physics. Full
synchronization is precluded by Liouville's theorem. A form of synchronization
weaker than "measure synchronization" is manifest as the positional coincidence
of coherent oscillations ("breathers" or "oscillons") in a pair of coupled
scalar field models in an expanding universe with a nonlinear potential, and
does not occur with a variant of the model that does not exhibit oscillons.


  We present predictions for the total cross sections for pair production of
squarks and gluinos at the LHC including a combined NNLL resummation of soft
and Coulomb gluon effects. We derive all terms in the NNLO cross section that
are enhanced near the production threshold, which include contributions from
spin-dependent potentials and so-called annihilation corrections. The NNLL
corrections at $\sqrt{s}=13$ TeV range from up to $20\%$ for squark-squark
production to $90\%$ for gluino pair production relative to the NLO results and
reduce the theoretical uncertainties of the perturbative calculation to the
$10\%$ level. Grid files with our numerical results are publicly available.


  Order-revealing encryption is a useful cryptographic primitive that provides
range queries on encrypted data since anyone can compare the order of
plaintexts by running a public comparison algorithm. Most studies on
order-revealing encryption focus only on comparing ciphertexts generated by a
single client, and there is no study on comparing ciphertexts generated by
multiple clients. In this paper, we propose the concept of multi-client
order-revealing encryption that supports comparisons not only on ciphertexts
generated by one client but also on ciphertexts generated by multiple clients.
We also define a simulation-based security model for multi-client
order-revealing encryption. The security model is defined with respect to the
leakage function which quantifies how much information is leaked from the
scheme. Next, we present two specific multi-client order-revealing encryption
schemes with different leakage functions in bilinear maps and prove their
security in the random oracle model. Finally, we give the implementation of the
proposed schemes and suggest methods to improve the performance of ciphertext
comparisons.


  Intelligent reflecting surface (IRS) has emerged as a promising and
revolutionizing technology for future wireless networks. Most existing IRS
studies focus on simple cooperative systems which usually have a single
frequency band. In realistic non-cooperative multi-band networks, however, the
existing IRS designs may be not applicable or have severe performance
degradation. Thus, in the complex network environment, it is more rational to
consider IRSs as public resources to be dynamically allocated to appropriate
users. In this paper, we first introduce the auction theory to tackle the
resource management problem for a multi-IRS-assisted non-cooperative network.
An efficient auction algorithm framework is introduced to sub-optimally solve
this non-convex problem. Simulation result illustrates that the significant
performance improvement can be achieved by applying the auction algorithm in
the complex multi-IRS-assisted non-cooperative network.


  We explore the second order bilinear magnetoelectric resistance (BMER) effect
in the d-electron-based two-dimensional electron gas (2DEG) at the SrTiO3 (111)
surface. We find an evidence of a spin-split band structure with the archetypal
spin-momentum locking of the Rashba effect for the in-plane component. Under an
out-of-plane magnetic field, we find a BMER signal that breaks the six-fold
symmetry of the electronic dispersion, which is a fingerprint for the presence
of a momentum dependent out-of-plane spin component. Relativistic electronic
structure calculations reproduce this spin-texture and indicate that the
out-of-plane component is a ubiquitous property of oxide 2DEGs arising from
strong crystal field effects. We further show that the BMER response of the
SrTiO3 (111) 2DEG is tunable and unexpectedly large.


We classify which complete multipartite graphs are intrinsically chiral.


  Investigations were carried out on the stability of the two gas giant system
HD 60532 itself including additional, smaller bodies. The methods used were
numerical simulations with the Lie Series integration method, and secular
perturbation theory. The aims were to find stable regions for potential
Earth-like planets within the system, and confirming the stability of the
detected planets. As results, the given configuration can be considered stable
for a period of at least 65 million years. The two planets create a large
unstable section between 0.25 and 3.6 AU, where no additional body is able to
remain stable. Variations in the mutual inclination between test bodies and the
rest of the system of up to 20{\deg} have little effects on the size of the
zone of instability.


  Strong effects of the Faraday instability on suspensions of rodlike colloidal
particles are reported through measurements of the critical acceleration and of
the surface wave amplitude. We show that the transition to parametrically
excited surface waves displays discontinuous and hysteretic features. This
subcritical behaviour is attributed to the shear-thinning properties of our
colloidal suspensions thanks to a phenomenological model based on rheological
data under large amplitude oscillatory shear. Birefringence measurements
provide direct evidence that Faraday waves induce local nematic ordering of the
rodlike colloids. While local alignment simply follows the surface oscillations
for dilute, isotropic suspensions, permanent nematic patches are generated by
surface waves in samples close to the isotropic-to-nematic transition and above
the transition large domains align in the flow direction. This strong coupling
between the fluid microstructure and a hydrodynamic instability is confirmed by
numerical computations based on the microstructural response of rodlike viruses
in shear flow.


  Quantitative trading (QT), which refers to the usage of mathematical models
and data-driven techniques in analyzing the financial market, has been a
popular topic in both academia and financial industry since 1970s. In the last
decade, reinforcement learning (RL) has garnered significant interest in many
domains such as robotics and video games, owing to its outstanding ability on
solving complex sequential decision making problems. RL's impact is pervasive,
recently demonstrating its ability to conquer many challenging QT tasks. It is
a flourishing research direction to explore RL techniques' potential on QT
tasks. This paper aims at providing a comprehensive survey of research efforts
on RL-based methods for QT tasks. More concretely, we devise a taxonomy of
RL-based QT models, along with a comprehensive summary of the state of the art.
Finally, we discuss current challenges and propose future research directions
in this exciting field.


  We explore the evolution of the X-ray luminosity function of quasars and the
intrinsic correlation between the X-ray and 2500\AA $\,$ ultraviolet
luminosities, utilizing techniques verified in previous works and a sample of
over 4000 quasars detected with Chandra and XMM-Newton in the range $0<z<5$. We
find that quasars have undergone significantly less evolution with redshift in
their total X-ray luminosity than in other wavebands. We then determine that
the best fit intrinsic power law correlation between the X-ray and ultraviolet
luminosities, of the form $L'_{\rm X} \propto ({L'_{\rm UV}})^{\gamma}$, is
$\gamma=0.28\pm$0.03, and we derive the luminosity function and density
evolution in the X-ray band. We discuss the implications of these results for
models of quasar systems.


  We report the results of 3-dimensional magnetohydrodynamic (MHD) simulations
of a jet formation by the interaction between an accretion disk and a large
scale magnetic field. The disk is not treated as a boundary condition but is
solved self-consistently. To investigate the stability of MHD jet, the
accretion disk is perturbed with a non-axisymmetric sinusoidal or random
fluctuation of the rotational velocity. The dependences of the jet velocity
$(v_z)$, mass outflow rate $(\dot{M}_w)$, and mass accretion rate $(\dot{M}_a)$
on the initial magnetic field strength in both non-axisymmetric cases are
similar to those in the axisymmetric case. That is, $v_z \propto B_0^{1/3}$,
$\dot{M}_w \propto B_0$ and $\dot{M}_a \propto B_0^{1.4}$ where $B_0$ is the
initial magnetic field strength. The former two relations are consistent with
the Michel's steady solution, $v_z \propto (B_0^2/\dot{M}_w)^{1/3}$, although
the jet and accretion do not reach the steady state. In both perturbation
cases, a non-axisymmetric structure with $m=2$ appears in the jet, where $m$
means the azimuthal wave number. This structure can not be explained by
Kelvin-Helmholtz instability and seems to originate in the accretion disk.
Non-axisymmetric modes in the jet reach almost constant levels after about 1.5
orbital periods of the accretion disk, while all modes in the accretion disk
grow with oscillation. As for the angular momentum transport by Maxwell stress,
the vertical component, $<B_\phi B_z/4\pi>$, is comparable to the radial
component, $<B_\phi B_r/4\pi>$, in the wide range of initial magnetic field
strength.


  We show that dualization of Stueckelberg-like massive gauge theories and
$B\wedge F$ models, follows form a general p-dualization of interacting
theories in d spacetime dimensions. This is achieved by a particular choice of
the external current.


  We show that closures of families of unitary local systems on quasiprojective
varieties for which the dimension of a graded component of Hodge filtration has
a constant value can be identified with a finite union of polytopes. We also
present a local version of the theorem. This yields the "Hodge decomposition"
of the set of unitary local systems with a non-vanishing cohomology extending
Hodge decomposition of characteristic varieties of links of plane curves
studied by the author earlier. We consider a twisted version of the
characteristic varieties generalizing the twisted Alexander polynomials.
Several explicit calculations for complements to arrangements are made.


  Despite its versatility and high chemical specificity, conventional NMR
spectroscopy is limited in measurement throughput due to the need for
high-homogeneity magnetic fields, necessitating sequential sample analysis, and
bulky devices. Here, we propose a multichannel NMR device that overcomes these
limitations that leverages the zero-to-ultralow field (ZULF) regime, where
simultaneous detection of multiple samples is carried out via an array of
compact optically pumped magnetometers (OPMs). A magnetic field is used only
for pre-polarization, permitting the use of large-bore, high-field,
inhomogeneous magnets that can accommodate many samples concurrently. Through
systematic advances, we demonstrate high-sensitivity, high resolution ZULF NMR
spectroscopy with sensitivity comparable to benchtop NMR systems. The
spectroscopy remains robust without the need for field shimming for periods on
the order of weeks. We show the detection of ZULF NMR signals from organic
molecules without isotopic enrichment, and demonstrate the parallelized
detection of three distinct samples simultaneously as a proof-of-concept, with
the potential to scale further to over 100 channels at a cost comparable to
high-resolution liquid state NMR systems. This work sets the stage for using
multichannel "NMR camera" devices for inline reaction monitoring, robotic
chemistry, quality control, and high-throughput assays.


  The study of register in computational language research has historically
been divided into register analysis, seeking to determine the registerial
character of a text or corpus, and register synthesis, seeking to generate a
text in a desired register. This article surveys the different approaches to
these disparate tasks. Register synthesis has tended to use more theoretically
articulated notions of register and genre than analysis work, which often seeks
to categorize on the basis of intuitive and somewhat incoherent notions of
prelabeled 'text types'. I argue that an integration of computational register
analysis and synthesis will benefit register studies as a whole, by enabling a
new large-scale research program in register studies. It will enable
comprehensive global mapping of functional language varieties in multiple
languages, including the relationships between them. Furthermore, computational
methods together with high coverage systematically collected and analyzed data
will thus enable rigorous empirical validation and refinement of different
theories of register, which will have also implications for our understanding
of linguistic variation in general.


  This paper rigorously analyses preconditioners for the time-harmonic Maxwell
equations with absorption, where the PDE is discretised using curl-conforming
finite-element methods of fixed, arbitrary order and the preconditioner is
constructed using Additive Schwarz domain decomposition methods. The theory
developed here shows that if the absorption is large enough, and if the
subdomain and coarse mesh diameters and overlap are chosen appropriately, then
the classical two-level overlapping Additive Schwarz preconditioner (with PEC
boundary conditions on the subdomains) performs optimally -- in the sense that
GMRES converges in a wavenumber-independent number of iterations -- for the
problem with absorption. An important feature of the theory is that it allows
the coarse space to be built from low-order elements even if the PDE is
discretised using high-order elements. It also shows that additive methods with
minimal overlap can be robust. Numerical experiments are given that illustrate
the theory and its dependence on various parameters. These experiments motivate
some extensions of the preconditioners which have better robustness for
problems with less absorption, including the propagative case. At the end of
the paper we illustrate the performance of these on two substantial
applications; the first (a problem with absorption arising from medical
imaging) shows the empirical robustness of the preconditioner against
heterogeneity, and the second (scattering by a COBRA cavity) shows good
scalability of the preconditioner with up to 3,000 processors.


  This article studies constructions of reproducing kernel Banach spaces
(RKBSs) which may be viewed as a generalization of reproducing kernel Hilbert
spaces (RKHSs). A key point is to endow Banach spaces with reproducing kernels
such that machine learning in RKBSs can be well-posed and of easy
implementation. First we verify many advanced properties of the general RKBSs
such as density, continuity, separability, implicit representation, imbedding,
compactness, representer theorem for learning methods, oracle inequality, and
universal approximation. Then, we develop a new concept of generalized Mercer
kernels to construct $p$-norm RKBSs for $1\leq p\leq\infty$. The $p$-norm RKBSs
preserve the same simple format as the Mercer representation of RKHSs.
Moreover, the $p$-norm RKBSs are isometrically equivalent to the standard
$p$-norm spaces of countable sequences. Hence, the $p$-norm RKBSs possess more
geometrical structures than RKHSs including sparsity. The generalized Mercer
kernels also cover many well-known kernels, for example, min kernels, Gaussian
kernels, and power series kernels. Finally, we propose to solve the support
vector machines in the $p$-norm RKBSs, which are to minimize the regularized
empirical risks over the $p$-norm RKBSs. We show that the infinite dimensional
support vector machines in the $p$-norm RKBSs can be equivalently transferred
to finite dimensional convex optimization problems such that we obtain the
finite dimensional representations of the support vector machine solutions for
practical applications. In particular, we verify that some special support
vector machines in the $1$-norm RKBSs are equivalent to the classical $1$-norm
sparse regressions. This gives fundamental supports of a novel learning tool
called sparse learning methods to be investigated in our next research project.


  Let $\pi:P\to M^n$ be a principal G-bundle, and let ${\mathcal{L}}: J^1P
\to\Lambda^n(M)$ be a G-invariant Lagrangian density. We obtain the
Euler-Poincare equations for the reduced Lagrangian l defined on ${\mathcal
C}(P)$, the bundle of connections on P.


  Spin-orbit coupled materials have attracted revived prominent research
interest as of late, especially due their direct connection with topological
notions. Arguably, a hallmark of this pursuit is formed by the concept of the
topological band insulator (TBI). In these incompressible systems band
inversions, often driven by strong spin-orbit coupling, result in a state that
is topologically distinct from the usual insulator as long as time reversal
symmetry is maintained. More generally, topological states that arise by virtue
of a protecting symmetry have resulted in a flourishing research field on both
the experimental as well as theoretical side of the condensed matter agenda. As
a prime signature topological band insulators can exhibit protected spin
filtered edge states, whose time reversal invariant partner is spatially
separated on the other edge. While these edge states have resultantly been
identified with many exotic physical phenomena, we here wish to provide a
perspective on the equally rich, although far less explored, aspects of the
bulk. That is, we will focus on the role of lattice defects, dislocations in
particular, and their relation with the topological nature of the bulk.


  The STAR experiment at RHIC measures the longitudinal double-spin asymmetry
$A_{LL}$ for a variety of final states in collisions of longitudinally
polarized protons to constrain the polarized gluon distribution in the proton.
Asymmetries for mid-rapidity charged pion production benefit from large
cross-sections and the excellent tracking and particle identification
capabilities of the STAR Time Projection Chamber. This contribution presents a
measurement of the ratio of cross sections for inclusive $\pi^{-}$ and
$\pi^{+}$ production using data collected in 2005, as well as a new measurement
of $A_{LL}$ for charged pions opposite a jet obtained from the 2006 RHIC run.


  Motivated by the fact that QCD critical point (CP) belongs to the same
universality class as the liquid-gas transition, the dynamical density
fluctuations around the CP is analyzed using relativistic fluid dynamics for a
viscous fluid. It is shown that relativistic effects on the dynamical structure
factor of the density fluctuation appears only in the width of the sound and
thermal modes through a modification of the transport/kinetic coefficients. It
is found that the mechanical density fluctuation which is enhanced by the
relativistic effects are attenuated, whereas the entropy fluctuation in turn
becomes more prominent around the QCD CP. This attenuation of the density
fluctuation around the QCD CP may imply that if the suppression or even total
disappearance of Mach cone is observed as the incident energy of the
relativistic heavy-ion collisionsis lowered, it can be a signal of the
existence of the QCD critical point.


  Training convolutional neural networks (CNNs) requires intense computations
and high memory bandwidth. We find that bandwidth today is over-provisioned
because most memory accesses in CNN training can be eliminated by rearranging
computation to better utilize on-chip buffers and avoid traffic resulting from
large per-layer memory footprints. We introduce the MBS CNN training approach
that significantly reduces memory traffic by partially serializing mini-batch
processing across groups of layers. This optimizes reuse within on-chip buffers
and balances both intra-layer and inter-layer reuse. We also introduce the
WaveCore CNN training accelerator that effectively trains CNNs in the MBS
approach with high functional-unit utilization. Combined, WaveCore and MBS
reduce DRAM traffic by 75%, improve performance by 53%, and save 26% system
energy for modern deep CNN training compared to conventional training
mechanisms and accelerators.


  We classify a large class of small groups of finite Morley rank:
$N_\circ^\circ$-groups which are the infinite analogues of Thompson's
$N$-groups. More precisely, we constrain the $2$-structure of groups of finite
Morley rank containing a definable, normal, non-soluble,
$N_\circ^\circ$-subgroup.


  The mathematical physicists Bershadsky-Cecotti-Ooguri-Vafa (BCOV) proposed,
in a seminal article from '94, a conjecture extending genus zero mirror
symmetry to higher genera. With a view towards a refined formulation of the
Grothendieck-Riemann-Roch theorem, we offer a mathematical description of the
BCOV conjecture at genus one. As an application of the arithmetic Riemann-Roch
theorem of Gillet-Soul\'e and of our previous results on the BCOV invariant, we
establish this conjecture for Calabi-Yau hypersurfaces in projective spaces.
Our contribution takes place on the $B$-side, and together with the work of
Zinger on the $A$-side, it provides the first complete examples of the mirror
symmetry program in higher dimensions. The case of quintic threefolds was
studied by Fang-Lu-Yoshikawa. Our approach also lends itself to arithmetic
considerations of the BCOV invariant, and we study a Chowla-Selberg type
theorem expressing it in terms of special $\Gamma$ values for certain
Calabi-Yau manifolds with complex multiplication.


  The spontaneous formation of lattice structure of quantized vortices is a
characteristic feature of superfluidity in closed systems under thermal
equilibrium. In exciton-polariton Bose-Einstein condensate, which is a typical
example of macroscopic quantum state in open systems, spontaneous vortex
lattices have also been proposed by not yet observed. Here, we take into
account the finite decay rate of exciton reservoir, and theoretically
investigate the vortex structures in circularly pumped polariton Bose-Einstein
condensate. Our results show that a decreasing reservoir decay rate can reduce
the number of vortices and destabilize the lattice structure, hence is
unfavorable to the formation and observation of vortex lattices. These
detrimental effects can be prevailed by applying an external angular momentum.


  Astrophysical indications that the fine structure constant has undergone a
small time variation during the cosmological evolution are discussed within the
framework of the standard model of the electroweak and strong interactions and
of grand unification. A variation of the electromagnetic coupling constant
could either be generated by a corresponding time variation of the unified
coupling constant or by a time variation of the unification scale, or by both.
The various possibilities, differing substantially in their implications for
the variation of how energy physics parameters like the nuclear mass scale, are
discussed. The case in which the variation is caused by a time variation of the
unification scale is of special interest. It is supported in addition by recent
hints towards a time change of the proton- electron mass ratio.


  Building sets were introduced in the study of wonderful compactifications of
hyperplane arrangement complements and were later generalized to finite
meet-semilattices. Convex geometries, the duals of antimatroids, offer a robust
combinatorial abstraction of convexity. Supersolvable convex geometries and
antimatroids appear in the study of poset closure operators, Coxeter groups,
and matroid activities. We prove that the building sets on a finite
meet-semilattice form a supersolvable convex geometry. As an application, we
demonstrate that building sets and nested set complexes respect certain
restrictions of finite meet-semilattices unifying and extending results of
several authors.


  Quantitatively assessing relationships between latent variables and observed
variables is important for understanding and developing generative models and
representation learning. In this paper, we propose latent-observed
dissimilarity (LOD) to evaluate the dissimilarity between the probabilistic
characteristics of latent and observed variables. We also define four essential
types of generative models with different independence/conditional independence
configurations. Experiments using tractable real-world data show that LOD can
effectively capture the differences between models and reflect the capability
for higher layer learning. They also show that the conditional independence of
latent variables given observed variables contributes to improving the
transmission of information and characteristics from lower layers to higher
layers.


  We consider small mass asymptotics of the motion of a charged particle in a
noisy force field combined with a variable magnetic field. The
Smoluchowski-Kramers approximation does not hold in this case. We show that
after a regularization of noise, a Smoluchowski-Kramers type approximation
works.


  We show that $\scriptstyle{#9(S^2\times S^3)}$ admits an 8-dimensional
complex family of inequivalent non-regular Sasakian-Einstein structures. These
are the first known Einstein metrics on this 5-manifold. In particular, the
bound $\scriptstyle{b_2(M)\leq8}$ which holds for any regular Sasakian-Einstein
$\scriptstyle{M}$ does not apply to the non-regular case. We also discuss the
failure of the Hitchin-Thorpe inequality in the case of 4-orbifolds and
describe the orbifold version.


  Given an essentially unitary contraction and an arbitrary unitary dilation of
it, there is a naturally associated spectral flow which is shown to be equal to
the index of the operator. This purely operator theoretic result is interpreted
in terms of the $K$-theory of an associated mapping cone. It is then extended
to connect $Z_2$ indices of odd symmetric Fredholm operators to a $Z_2$-valued
spectral flow.


  The coupling between mechanical and thermal properties due to thermal
expansion complicates the problem of measuring frequency-dependent
thermoviscoelastic properties, in particular for highly viscous liquids. A
simplification arises if there is spherical symmetry where - as detailed in the
present paper - the thermoviscoelastic problem may be solved analytically in
the inertia-free limit, i.e., the limit where the sample is much smaller than
the wavelength of sound waves at the frequencies of interest. As for the
one-dimensional thermoviscoelastic problem [Christensen et al., Phys. Rev. E
75, 041502 (2007)], the solution is conveniently formulated in terms of the
so-called transfer matrix, which directly links to the boundary conditions that
can be experimentally controlled. Once the transfer matrix has been calculated,
it is fairly easy to deduce the equations describing various experimentally
relevant special cases (boundary conditions that are adiabatic, isothermal,
isochoric, etc.). In most situations the relevant frequency-dependent specific
heat is the longitudinal specific heat, a quantity that is in between the
isochoric and isobaric frequency-dependent specific heats.


  The elliptic gamma function is a generalization of the Euler gamma function.
Its trigonometric and rational degenerations are the Jackson q-gamma function
and the Euler gamma function. We prove multiplication formulas for the elliptic
gamma function, whose degenerations are the Gauss-Askey multiplication formula
for the Euler and trigonometric gamma functions.


  In recent years, $\gamma$-ray emission has been detected from star-forming
galaxies (SFGs) in the local universe, including M82, NGC 253, Arp 220 and M33.
The bulk of this emission is thought to be of hadronic origin, arising from the
interactions of cosmic rays (CRs) with the interstellar medium of their host
galaxy. Distant SFGs are presumably also bright in $\gamma$-rays. Although they
would not be resolvable as point sources, distant unresolved SFG populations
contribute $\gamma$-rays to the extra-galactic $\gamma$-ray background (EGB).
Despite the wealth of high-quality all-sky EGB data collected over more than a
decade of operation with the \textit{Fermi}-LAT $\gamma$-ray space telescope,
the exact contribution of SFGs to the EGB remains unsettled. In this study, we
model the $\gamma$-ray emission from SFG populations and demonstrate that such
emission can be characterized by just a small number of physically-motivated
parameters. We further show that source populations would leave anisotropic
signatures in the EGB, which could be used to yield information about the
underlying properties, dynamics and evolution of CR-rich SFGs.


  The minimum spanning tree of a graph is a well-studied structure that is the
basis of countless graph theoretic and optimization problem. We study the
minimum spanning tree (MST) perturbation problem where the goal is to spend a
fixed budget to increase the weight of edges in order to increase the weight of
the MST as much as possible. Two popular models of perturbation are bulk and
continuous. In the bulk model, the weight of any edge can be increased exactly
once to some predetermined weight. In the continuous model, one can pay a
fractional amount of cost to increase the weight of any edge by a proportional
amount. Frederickson and Solis-Oba \cite{FS96} have studied these two models
and showed that bulk perturbation for MST is as hard as the $k$-cut problem
while the continuous perturbation model is solvable in poly-time. In this
paper, we study an intermediate unit perturbation variation of this problem
where the weight of each edge can be increased many times but at an integral
unit amount every time. We provide an $(opt/2 -1)$-approximation in polynomial
time where $opt$ is the optimal increase in the weight. We also study the
associated dual targeted version of the problem where the goal is to increase
the weight of the MST by a target amount while minimizing the cost of
perturbation. We provide a $2$-approximation for this variation. Furthermore we
show that assuming the Small Set Expansion Hypothesis, both problems are hard
to approximate. We also point out an error in the proof provided by
Frederickson and Solis-Oba in \cite{FS96} with regard to their solution to the
continuous perturbation model. Although their algorithm is correct, their
analysis is flawed. We provide a correct proof here.


  In this talk I address three topics related to the shape of hadrons:
  1. The Lorentz contraction of bound states. Few dedicated studies of this
exist - I describe a recent calculation for ordinary atoms (positronium).
  2. Does the A-dependence of nuclear structure functions indicate a change of
proton shape in the nuclear environment? (My short answer is no.)
  3. The size of Fock states contributing to processes involving large momentum
transfers. End-point configurations can be transversally extended and yet
sufficiently short-lived to contribute coherently to hard scattering.


  Ideal Sharvin contact in a multimode regime shows the conductance
$G\approx{}G_{\rm Sharvin}=g_0k_F{}W/\pi$ (with $g_0$ the conductance quantum,
$k_F$ the Fermi momentum, and $W$ the contact width) accompanied by strongly
suppressed shot-noise quantified by small Fano factor $F\approx{}0$. For
ballistic graphene away from the charge-neutrality point the sub-Sharvin
transport occurs, characterised by suppressed conductance
$G\approx{}(\pi/4)\,G_{\rm Sharvin}$ and enhanced shot noise $F\approx{}1/8$.
All these results can be derived from a basic model of quantum scattering,
involving assumptions of infinite height and perfectly rectangular shape of the
potential barrier in the sample. Here we have carried out the numerical
analysis of the scattering on a family of smooth barriers of finite height
interpolating between parabollic and rectangular shapes. We find that tuning
the barrier shape one can modify the asymmetry between electron- and hole-doped
systems. For electronic dopings, the system crosses from Sharvin to sub-Sharvin
transport regime (indicated by both the conductance and the Fano factor) as the
potential becomes closer to the rectangular shape. In contrast, for hole
dopings, the conductivity is strongly suppressed when the barrier is parabolic
and slowly converges to $G\approx{}(\pi/4)\,G_{\rm Sharvin}$ as the potential
evolves towards rectangular shape. In such a case the Sharvin transport regime
is inaccessible, shot noise is generically enhanced (with much slower
convergence to $F\approx{}1/8$) comparing to the electron-doped case, and
aperiodic oscillations of both $G$ and $F$ are prominent due to the formation
of quasibound states.


  Analysts often use data-driven approaches to supplement their substantive
knowledge when selecting covariates for causal effect estimation. Multiple
variable selection procedures tailored for causal effect estimation have been
devised in recent years, but additional developments are still required to
adequately address the needs of data analysts. In this paper, we propose a
Generalized Bayesian Causal Effect Estimation (GBCEE) algorithm to perform
variable selection and produce double robust estimates of causal effects for
binary or continuous exposures and outcomes. GBCEE employs a prior distribution
that targets the selection of true confounders and predictors of the outcome
for the unbiased estimation of causal effects with reduced standard errors.
Double robust estimators provide some robustness against model
misspecification, whereas the Bayesian machinery allows GBCEE to directly
produce inferences for its estimate. GBCEE was compared to multiple
alternatives in various simulation scenarios and was observed to perform
similarly or to outperform double robust alternatives. Its ability to directly
produce inferences is also an important advantage from a computational
perspective. The method is finally illustrated for the estimation of the effect
of meeting physical activity recommendations on the risk of hip or upper-leg
fractures among elderly women in the Study of Osteoporotic Fractures. The 95%
confidence interval produced by GBCEE is 61% shorter than that of a double
robust estimator adjusting for all potential confounders in this illustration.


  Dynamic systems have found their use in sound synthesis as well as score
synthesis. These levels can be integrated in monolithic autonomous systems in a
novel approach to algorithmic composition that shares certain aesthetic
motivations with some work with autonomous music systems, such as the search
for emergence. We discuss various strategies for achieving variation on
multiple time-scales by using slow-fast, hybrid dynamic systems, and
statistical feedback. The ideas are illustrated with a case study.


  The recent publications of the DENIS Catalogue towards the Magellanic Clouds
(MCs) with more than 1.3 million sources identified in at least two of the
three DENIS filters (I J K_s) and of the incremental releases of the 2MASS
point source catalogues (J H K_s) covering the same region of the sky, provide
an unprecedented wealth of data related to stellar populations in the MCs. In
order to build a reference catalogue of stars towards the Magellanic Clouds, we
have performed a cross-identification of these two catalogues. This implied
developing new tools for cross-identification and data mining.
  This study is partly supported by the Astrovirtel program that aims at
improving access to astronomical archives as virtual telescopes. The main goal
of the present study is to validate new cross-matching procedures for very
large catalogues, and to derive results concerning the astrometric and
photometric accuracy of these catalogues. The cross-matching of large surveys
is an essential tool to improve our understanding of their specific contents.
This approach can be considered as a new step towards a Virtual Observatory.


  In this paper, we will prove the existence of full dimensional tori for
1-dimensional nonlinear Schr\"odinger equation with periodic boundary
conditions \begin{equation*}\label{L1}
\mathbf{i}u_t-u_{xx}+V*u+\epsilon|u|^4u=0,\hspace{12pt}x\in\mathbb{T},
\end{equation*} where $V*$ is the convolution potential. Here the radius of the
invariant torus satisfies a slower decay, i.e. \begin{equation*}\label{031601}
I_n\sim e^{- \ln^{\sigma}|n|},\qquad \mbox{as}\ |n|\rightarrow\infty,
\end{equation*} for any $\sigma>2$, which improves the result given by Bourgain
(J. Funct. Anal. 229 (2005), no.1, 62-94).


  Backdoor attacks (BAs) are an emerging form of adversarial attack typically
against deep neural network image classifiers. The attacker aims to have the
classifier learn to classify to a target class when test images from one or
more source classes contain a backdoor pattern, while maintaining high accuracy
on all clean test images. Reverse-Engineering-based Defenses (REDs) against BAs
do not require access to the training set but only to an independent clean
dataset. Unfortunately, most existing REDs rely on an unrealistic assumption
that all classes except the target class are source classes of the attack. REDs
that do not rely on this assumption often require a large set of clean images
and heavy computation. In this paper, we propose a Lagrangian-based RED (L-RED)
that does not require knowledge of the number of source classes (or whether an
attack is present). Our defense requires very few clean images to effectively
detect BAs and is computationally efficient. Notably, we detect 56 out of 60
BAs using only two clean images per class in our experiments on CIFAR-10.


  Let $G/H$ be a compact homogeneous space, and let $\hat{g}_0$ and $\hat{g}_1$
be $G$-invariant Riemannian metrics on $G/H$. We consider the problem of
finding a $G$-invariant Einstein metric $g$ on the manifold $G/H\times [0,1]$
subject to the constraint that $g$ restricted to $G/H\times \{0\}$ and
$G/H\times \{1\}$ coincides with $\hat{g}_0$ and $\hat{g}_1$, respectively. By
assuming that the isotropy representation of $G/H$ consists of pairwise
inequivalent irreducible summands, we show that we can always find such an
Einstein metric.


  In this paper we study the Real Gromov-Witten theory of local 3-folds over
Real curves. We show that this gives rise to a 2-dimensional Klein TQFT defined
on an extension of the category of unorientable surfaces. We use this structure
to completely solve the theory by providing a closed formula for the local RGW
invariants in terms of representation theoretic data, extending earlier results
of Bryan and Pandharipande. As a consequence we obtain the local version of the
real Gopakumar-Vafa formula that expresses the connected real Gromov-Witten
invariants in terms of integer invariants. In the case of the resolved conifold
the partition function of the RGW invariants agrees with that of the SO/Sp
Chern-Simons theory.


  The polycrystalline Bi1-xHoxFeO3 (x=0, 0.05, 0.1) compounds were synthesized
by conventional solid-state route. Rietveld refinement reveals that all the
compounds were stabilized in rhombohedral structure with R3c (IUCr No. 161)
space group. A competing ferro and anti-ferro magnetic interaction was observed
in Ho-substituted compounds. A change in the Fe-O-Fe bond-angle and Fe-O bond
distance increase the Neel Transition temperature with increasing Ho
concentration. The appearance of peak in imaginary part of impedance (Z") for
each concentration and shifting of this peak with temperature towards higher
frequency side indicated that the presence of electric relaxations. Correlated
Barrier Hopping model (CBH) was employed to explain the frequency and
temperature dependence of ac conductivity and the mechanism of transport in the
material BFO and Ho substituted BFO. Density of states near Fermi level was
calculated by using the ac conductivity data.


  Given a graph $G$, the number of nowhere-zero $\ZZ_q$-flows $\phi_G(q)$ is
known to be a polynomial in $q$. We extend the definition of nowhere-zero
$\ZZ_q$-flows to simplicial complexes $\Delta$ of dimension greater than one,
and prove the polynomiality of the corresponding function $\phi_{\Delta}(q)$
for certain $q$ and certain subclasses of simplicial complexes.


  We give improved pseudorandom generators (PRGs) for Lipschitz functions of
low-degree polynomials over the hypercube. These are functions of the form
psi(P(x)), where P is a low-degree polynomial and psi is a function with small
Lipschitz constant. PRGs for smooth functions of low-degree polynomials have
received a lot of attention recently and play an important role in constructing
PRGs for the natural class of polynomial threshold functions. In spite of the
recent progress, no nontrivial PRGs were known for fooling Lipschitz functions
of degree O(log n) polynomials even for constant error rate. In this work, we
give the first such generator obtaining a seed-length of (log
n)\tilde{O}(d^2/eps^2) for fooling degree d polynomials with error eps.
Previous generators had an exponential dependence on the degree.
  We use our PRG to get better integrality gap instances for sparsest cut, a
fundamental problem in graph theory with many applications in graph
optimization. We give an instance of uniform sparsest cut for which a powerful
semi-definite relaxation (SDP) first introduced by Goemans and Linial and
studied in the seminal work of Arora, Rao and Vazirani has an integrality gap
of exp(\Omega((log log n)^{1/2})). Understanding the performance of the
Goemans-Linial SDP for uniform sparsest cut is an important open problem in
approximation algorithms and metric embeddings and our work gives a
near-exponential improvement over previous lower bounds which achieved a gap of
\Omega(log log n).


  We introduce labelled sequent calculi for the basic normal non-distributive
modal logic L and 31 of its axiomatic extensions, where the labels are atomic
formulas of a first order language which is interpreted on the canonical
extensions of the algebras in the variety corresponding to the logic L. Modular
proofs are presented that these calculi are all sound, complete and
conservative w.r.t. L, and enjoy cut elimination and the subformula property.
The introduction of these calculi showcases a general methodology for
introducing labelled calculi for the class of LE-logics and their analytic
axiomatic extensions in a principled and uniform way.


  We propose a model which includes a nearest-neighbor intrinsic spin-orbit
coupling and a dimer Hamiltonian in the Kagom\'{e} lattice and promises to host
the transition from the quantum spin Hall insulator to the normal insulator. In
addition, we design an experimental scheme to simulate and detect this
transition in the ultracold atom system. The lattice intrinsic spin-orbit
coupling is generated via the laser-induced-gauge-field method. Furthermore, we
establish the connection between the spin Chern number and the spin-atomic
density which enables us to detect the topological quantum spin Hall insulator
directly by the standard density-profile technique used in the atomic systems.


  We categorify representations of quantum sl(n) whose highest weight is twice
a fundamental weight.


  A classical action for open superstring field theory has been proposed which
does not suffer from contact term problems. After generalizing this action to
include the non-GSO projected states of the Neveu-Schwarz string, the pure
tachyon contribution to the tachyon potential is explicitly computed. The
potential has a minimum of $V = -{1\over{32 g^2}}$ which is 60% of the
predicted exact minimum of $V=-{1\over{2\pi^2 g^2}}$ from D-brane arguments.


  We study the Weihrauch degrees of closed choice for finite sets, closed
choice for convex sets and sorting infinite sequences over finite alphabets.
Our main results are: One, that choice for finite sets of cardinality $i + 1$
is reducible to choice for convex sets in dimension $j$, which in turn is
reducible to sorting infinite sequences over an alphabet of size $k + 1$, iff
$i \leq j \leq k$. Two, that convex choice in dimension two is not reducible to
the product of convex choice in dimension one with itself. Three, that
sequential composition of one-dimensional convex choice is not reducible to
convex choice in any dimension. The latter solves an open question raised at a
Dagstuhl seminar on Weihrauch reducibility in 2015. Our proofs invoke Kleene's
recursion theorem, and we describe in some detail how Kleene's recursion
theorem gives rise to a technique for proving separations of Weihrauch degrees.


  In this paper we study photon emission in the interaction of the laser beam
with an under-dense target and the attached reflecting plasma mirror. Photons
are emitted due to the inverse Compton scattering when accelerated electrons
interact with a reflected part of the laser pulse. The enhancement of photon
generation in this configuration lies in using the laser pulse with a steep
rising edge. Such a laser pulse can be obtained by the preceding interaction of
the incoming laser pulse with a thin solid-density foil. Using numerical
simulations we study the origin of such a laser pulse and its effect on photon
emission. As a result, accelerated electrons can interact directly with the
most intense part of the laser pulse that enhances photon emission. This
approach increases the number of created photons and improves photon beam
divergence.


  Using $e^+e^-\to\Lambda_c^+\bar\Lambda_c^-$ production from a 567 pb$^{-1}$
data sample collected by BESIII at 4.6 GeV, a full angular analysis is carried
out simultaneously on the four decay modes of $\Lambda_c^+\to pK_S^0$, $\Lambda
\pi^+$, $\Sigma^+\pi^0$, and $\Sigma^0\pi^+$. For the first time, the
$\Lambda_c^+$ transverse polarization is studied in unpolarized $e^+e^-$
collisions, where a non-zero effect is observed with a statistical significance
of 2.1$\sigma$. The decay asymmetry parameters of the $\Lambda_c^+$ weak
hadronic decays into $pK_S^0$, $\Lambda\pi^+$, $\Sigma^+\pi^0$ and
$\Sigma^0\pi^+$ are measured to be $0.18\pm0.43(\rm{stat})\pm0.14(\rm{syst})$,
$-0.80\pm0.11(\rm{stat})\pm0.02(\rm{syst})$,
$-0.57\pm0.10(\rm{stat})\pm0.07(\rm{syst})$, and
$-0.73\pm0.17(\rm{stat})\pm0.07(\rm{syst})$, respectively. In comparison with
previous results, the measurements for the $\Lambda\pi^+$ and $\Sigma^+\pi^0$
modes are consistent but with improved precision, while the parameters for the
$pK_S^0$ and $\Sigma^0\pi^+$ modes are measured for the first time.


  Freeman has considered the following two-stage procedure for finding a
confidence interval for the treatment difference theta, using data from an
AB/BA crossover trial. In the first stage, a preliminary test of the null
hypothesis that the differential carryover is zero, is carried out. If this
hypothesis is accepted then the confidence interval for theta is constructed
assuming that the differential carryover is zero. If, on the other hand, this
hypothesis is rejected then this confidence interval is constructed using only
data from the first period. Freeman has shown that this confidence interval has
minimum coverage probability far below nominal. He therefore concludes that
this confidence interval should not be used. In the present paper, we analyse
the performance of a similar two-stage procedure for an ABAB/BABA crossover
trial. This trial differs in very significant ways from an AB/BA crossover
trial, including the fact that for an ABAB/BABA crossover trial there is an
unbiased estimator of the differential carryover that is unaffected by
between-subject variation. Despite these great differences, we arrive at the
same conclusion as Freeman. Namely, that the confidence interval resulting from
the two-stage procedure should not be used.


  Very few K-nearest-neighbor (KNN) ensembles exist, despite the efficacy of
this approach in regression, classification, and outlier detection. Those that
do exist focus on bagging features, rather than varying k or bagging
observations; it is unknown whether varying k or bagging observations can
improve prediction. Given recent studies from topological data analysis,
varying k may function like multiscale topological methods, providing stability
and better prediction, as well as increased ensemble diversity.
  This paper explores 7 KNN ensemble algorithms combining bagged features,
bagged observations, and varied k to understand how each of these contribute to
model fit. Specifically, these algorithms are tested on Tweedie regression
problems through simulations and 6 real datasets; results are compared to
state-of-the-art machine learning models including extreme learning machines,
random forest, boosted regression, and Morse-Smale regression.
  Results on simulations suggest gains from varying k above and beyond bagging
features or samples, as well as the robustness of KNN ensembles to the curse of
dimensionality. KNN regression ensembles perform favorably against
state-of-the-art algorithms and dramatically improve performance over KNN
regression. Further, real dataset results suggest varying k is a good strategy
in general (particularly for difficult Tweedie regression problems) and that
KNN regression ensembles often outperform state-of-the-art methods.
  These results for k-varying ensembles echo recent theoretical results in
topological data analysis, where multidimensional filter functions and
multiscale coverings provide stability and performance gains over
single-dimensional filters and single-scale covering. This opens up the
possibility of leveraging multiscale neighborhoods and multiple measures of
local geometry in ensemble methods.


  Background:Diverse tacrolimus population pharmacokinetic models in adult
liver transplant recipients have been established to describe the PK
characteristics of tacrolimus in the last two decades. However, their
extrapolated predictive performance remains unclear.Therefore,in this study,we
aimed to evaluate their external predictability and identify their potential
influencing factors. Methods:The external predictability of each selected popPK
model was evaluated using an independent dataset of 84 patients with 572 trough
concentrations prospectively collected from Huashan Hospital. Prediction and
simulation based diagnostics and Bayesian forecasting were conducted to
evaluate model predictability. Furthermore, the effect of model structure on
the predictive performance was investigated.Results:Sixteen published popPK
models were assessed. In prediction-based diagnostics,the prediction error
within 30% was below 50% in all the published models. The simulation based
normalised prediction distribution error test and visual predictive check
indicated large discrepancies between the observations and simulations in most
of the models. Bayesian forecasting showed improvement in model predictability
with two to three prior observations. Additionally, the predictive performance
of the nonlinear Michaelis Menten model was superior to that of linear
compartment models,indicating the underlying nonlinear kinetics of tacrolimus
in liver transplant recipients.Conclusions:The published models performed
inadequately in prediction and simulation based diagnostics. Bayesian
forecasting may improve the predictive performance of the models. Furthermore,
nonlinear kinetics of tacrolimus may be mainly caused by the properties of the
drug itself, and incorporating nonlinear kinetics may be considered to improve
model predictability.


  The projection of the four-dimensional two-body Bethe-Salpeter equation at
the light-front hypersurface is discussed. Elimination of the relative time is
performed using a quasi-potential expansion, which is shown to be equivalent to
an infinite set of coupled equations for the Green's functions of the different
light-front Fock-states.


  Spin ices can now be fabricated in a variety of geometries which control
their collective behavior and exotic properties. Therefore, their proper
framework is graph theory. We relate spin ice notions such as ice rule, ice
manifold, Coulomb phases, charges and monopoles, to graph-theoretical notions,
such as balance, in/out-degrees, and Eulerianicity. We then propose a
field-theoretical treatment in which topological charges and monopoles are the
degrees of freedom while the binary spins are subsumed into entropic
interaction among charges. We show that for a spin ice on a graph in a Gaussian
approximation, the kernel of the entropic interaction is the inverse of the
graph Laplacian, and we compute screening functions from the graph spectra as
Green operators for the screened Poisson problem on a graph. We then apply the
treatment on star graphs, tournaments, cycles, and regular spin ice in
different dimensions.


  Emergent technologies that make use of novel materials and quantum properties
of light states are at the forefront in the race for the physical
implementation, encoding and transmission of information. Photonic crystals
(PCs) enter this paradigm with optical materials that allow the control of
light propagation and can be used for optical communication, and photonics and
electronics integration making use of materials ranging from semiconductors, to
metals, metamaterials, and topological insulators, to mention but a few. In
particular, here we show how designer superconductor materials integrated into
PCs fabrication allow for an extraordinary reduction of electromagnetic waves
damping and possibilitate their optimal propagation and tuning through the
structure, below critical superconductor temperature. We experimentally
demonstrate, for the first time, a successful integration of ferroelectric and
superconductor materials into a one-dimensional (1D) PC composed of
(BTO/YBCO)N/STO bilayers that work in the whole visible spectrum, and below
(and above) critical superconductor temperature (measured in the 10-300 K
range). Theoretical calculations support, for different number of bilayers N,
the effectiveness of the produced 1D PCs and pave the way for novel
optoelectronics integration and information processing in the visible spectrum
at low temperature, while preserving their electric and optical properties.


  Space asteroseismology reveals that stellar structure and evolution models of
intermediate- and high-mass stars are in need of improvement in terms of
angular momentum and chemical element transport. We aim to probe the interior
structure of a hot massive star in the core-hydrogen burning phase of its
evolution. We analyse CoRoT space photometry, Gaia DR2 space astrometry, and
high-resolution high signal-to-noise HERMES and HARPS time-series spectroscopy
of the slowly rotating B2V star HD 170580. From the time-series spectroscopy we
derive $vsini=4\pm 2\,$km\,s$^{-1}$, where the uncertainty results from the
complex pulsational line-profile variability. We detect 42 frequencies with
amplitude above 5$\sigma$. Among these we identify 5 rotationally split
triplets and 1 quintuplet. Asteroseismic modelling based on CoRoT, Gaia DR2 and
spectroscopic data leads to a star of 8M$_\odot$ near core-hydrogen exhaustion
and an extended overshoot zone. The detected low-order pressure-mode
frequencies cannot be fit within the uncertainties of the CoRoT data by models
without atomic diffusion.
  Irrespective of this limitation, the low-order gravity modes reveal HD 170580
to be a slow rotator with an average rotation period between 73 and 98 d and a
hint of small differential rotation. Future Gaia DR3 data taking into account
the multiplicity of the star, along with long-term TESS photometry would allow
to put better observational constraints on the asteroseismic models of this
blue evolved massive star. Improved modelling with atomic diffusion, including
radiative levitation, is needed to achieve compliance with the low helium
surface abundance of the star. This poses immense computational challenges but
is required to derive the interior rotation and mixing profiles of this star.


  Let a be a positive integer greater than 1, and Q_a(x;k,j) be the set of
primes p less than x such that the residual order of a(mod p) is congruent to j
modulo k. In this paper, the natural densities of Q_a(x;4,j) (j=0,1,2,3) are
considered. We assume a is square-free and a is congruent to 1 (mod 4). Then,
for j=0, 2, we can prove unconditionally that their natural densities are equal
to 1/3. On the contrary, for j=1, 3, we assume Generalized Riemann Hypothesis,
then we can prove that their densities are equal to 1/6.


  This paper extends and applies algebraic invariants and constructions for
mixing finite group extensions of shifts of finite type. For a finite abelian
group G, Parry showed how to define a G-extension S_A from a square matrix A
over Z_+G, and classified the extensions up to topological conjugacy by the
strong shift equivalence class of A over Z_+G. Parry asked in this case if the
det(I-tA) (which captures the "periodic data" of the extension) would classify
up to finitely many topological conjugacy classes the extensions by G of a
fixed mixing shift of finite type. When the algebraic K-theory group NK_1(ZG)
is nontrivial (e.g., for G=Z/4), we show the dynamical zeta function for any
such extension is consistent with infinitely many topological conjugacy
classes. Independent of NK_1(ZG): for every nontrivial abelian G we show there
exists a shift of finite type with an infinite family of mixing nonconjugate G
extensions with the same dynamical zeta function. We define computable complete
invariants for the periodic data of the extension for G not necessarily
abelian, and extend all the above results to the nonabelian case. There is
other work on basic invariants. The constructions require the "positive
K-theory" setting for positive equivalence of matrices over ZG[t].


  We develop an intensive embedding for visualizing the space of all
predictions for probabalistic models, using replica theory. Our embedding is
isometric (preserves the distinguishability between models) and faithful
(yields low-dimensional visualizations of models with simple emergent
behavior). We apply our intensive embedding to the Ising model of statistical
mechanics and the $\Lambda$CDM model applied to cosmic microwave background
radiation. It provides an intuitive, quantitative visualization applicable to
renormalization-group calculations and optimal experimental design.


  The advanced development of the Internet facilitates efficient information
exchange while also been exploited by adversaries. Intrusion detection system
(IDS) as an important defense component of network security has always been
widely studied in security research. However, research on intrusion prediction,
which is more critical for network security, is received less attention. We
argue that the advanced anticipation and timely impede of invasion is more
vital than simple alarms in security defenses. General research methods
regarding prediction are analyzing short term of system-calls to predict
forthcoming abnormal behaviors. In this paper we take advantages of the
remarkable performance of recurrent neural networks (RNNs) in dealing with long
sequential problem, introducing the sequence-to-sequence model into our
intrusion prediction work. By semantic modeling system-calls we build a robust
system-call sequence-to-sequence prediction model. With taking the system-call
traces invoked during the program running as known prerequisite, our model
predicts sequence of system-calls that is most likely to be executed in a near
future period of time that enabled the ability of monitoring system status and
prophesying the intrusion behaviors. Our experiments show that the predict
method proposed in this paper achieved well prediction performance on ADFALD
intrusion detection test data set. Moreover, the predicted sequence, combined
with the known invoked traces of system, significantly improves the performance
of intrusion detection verified on various classifiers.


  A set formed by five reversibly-switchable fluorescent proteins (RSFPs)
display spread over 40~nm in absorption maxima and only 18~nm in emission. The
five proteins -- Dronpa, rsFastLime, rsKame, Padron(anionic form) and bsDronpa
-- carry exactly the same chromophore and differ just in a few mutations. Thus
they form an ideal set for mechanistic investigation. Starting with the results
of molecular dynamics simulations we use QM/MM calculations to investigate the
effects controlling the spectral tuning . In this contribution we show that the
models, which are based on CASPT2//CASSCF level of QM theory, reproduce the
observed absorption trend with only a limited blue-shift of 4.5 kcal/mol and
emission trend with even smaller blue-shift of 1.5 kcal/mol. Using CASSCF QM/MM
calculations we analyze the chromophore's charge-transfer patterns during the
absorption and emission, which, in turn trigger a cascade of
hydrogen-bond-network rearrangements indicating a preparation to an
isomerization event. We also show how the contribution of individual aminoacids
to the chromophore conformational changes correlates with spectral tuning of
the absorption and emission. Furthermore, we identify how the conical
intersection topography correlates with protein's photophysical properties. In
conclusion, we establish a detailed mechanistic explanation of variations in
photo-switching speed as well as higher sensitivity of RSFPs to mutation
observed for light absorption relative to light emission.


  The performance of automatic speech recognition (ASR) systems has advanced
substantially in recent years, particularly for languages for which a large
amount of transcribed speech is available. Unfortunately, for low-resource
languages, such as minority languages, regional languages or dialects, ASR
performance generally remains much lower. In this study, we investigate whether
data augmentation techniques could help improve low-resource ASR performance,
focusing on four typologically diverse minority languages or language variants
(West Germanic: Gronings, West-Frisian; Malayo-Polynesian: Besemah, Nasal). For
all four languages, we examine the use of self-training, where an ASR system
trained with the available human-transcribed data is used to generate
transcriptions, which are then combined with the original data to train a new
ASR system. For Gronings, for which there was a pre-existing text-to-speech
(TTS) system available, we also examined the use of TTS to generate ASR
training data from text-only sources. We find that using a self-training
approach consistently yields improved performance (a relative WER reduction up
to 20.5% compared to using an ASR system trained on 24 minutes of manually
transcribed speech). The performance gain from TTS augmentation for Gronings
was even stronger (up to 25.5% relative reduction in WER compared to a system
based on 24 minutes of manually transcribed speech). In sum, our results show
the benefit of using self-training or (if possible) TTS-generated data as an
efficient solution to overcome the limitations of data availability for
resource-scarce languages in order to improve ASR performance.


  The CONT14 campaign with state-of-the-art VLBI data has observed the source
0642+449 with about one thousand observables each day during a continuous
observing period of fifteen days, providing tens of thousands of closure
delays---the sum of the delays around a closed loop of baselines. The closure
delay is independent of the instrumental and propagation delays and provides
valuable additional information about the source structure. We demonstrate the
use of this new "observable" for the determination of the structure in the
radio source 0642+449. This source, as one of the defining sources in the
second realization of the International Celestial Reference Frame (ICRF2), is
found to have two point-like components with a relative position offset of -426
microarcseconds in right ascension and -66 microarcseconds in declination. The
two components are almost equally bright with a flux-density ratio of 0.92. The
standard deviation of closure delays for source 0642+449 was reduced from 139
ps to 90 ps by using this two-component model. Closure delays larger than one
nanosecond are found to be related to the source structure, demonstrating that
structure effects for a source with this simple structure could be up to tens
of nanoseconds. The method described in this paper does not rely on a priori
source structure information, such as knowledge of source structure determined
from direct (Fourier) imaging of the same observations or observations at other
epochs. We anticipate our study to be a starting point for more effective
determination of the structure effect in VLBI observations.


  The energy sharing collision of bright optical solitons in the Manakov
system, governing pulse propagation in high birefringent fiber, is employed
theoretically to realize optical logic gates. Especially, for the first time,
we successfully construct (theoretically) the universal NOR gate and the OR
gate from the energy sharing collisions of just four bright solitons which can
be well described by the exact bright four-soliton solution of the Manakov
system. This construction procedure has the important merits like realizing the
two input gates with a minimal number of soliton collisions and possibilities
of multi-state logic. The recent experiments on Manakov solitons suggest the
possibility of implementation of this theoretical construction of such gates
and ultimately an all optical computer.


  We investigate a model of the interacting holographic dark energy with cold
dark matter (CDM). If the holographic energy density decays into CDM, we find
two types of the effective equation of state. In this case we have to use the
effective equations of state ($\omega^{\rm eff}_{\rm \Lambda}$) instead of the
equation of state ($\omega_{\rm \Lambda})$. For a fixed ratio of two energy
densities, their effective equations of state are given by the same negative
constant. Actually, the cosmic anti-friction arisen from the vacuum decay
process may induce the acceleration with $\omega^{\rm eff}_{\rm \Lambda}<-1/3$.
For a variable ratio, their effective equations of state are slightly
different, but they approach the same negative constant in the far future.
Consequently, we show that such an interacting holographic energy model cannot
accommodate a transition from the dark energy with $\omega^{\rm eff}_{\rm
\Lambda}\ge-1$ to the phantom regime with $\omega^{\rm eff}_{\rm \Lambda}<-1$.


  A subset $S$ of vertices in a graph $G=(V, E)$ is Dominating Set if each
vertex in $V(G)\setminus S$ is adjacent to at least one vertex in $S$. Chellali
et al. in 2013, by restricting the number of neighbors in $S$ of a vertex
outside $S$, introduced the concept of $[1,j]$-dominating set. A set $D
\subseteq V$ of a graph $G = (V, E)$ is called $[1,j]$-Dominating Set of $G$ if
every vertex not in $D$ has at least one neighbor and at most $j$ neighbors in
$D$. The Minimum $[1,j]$-Domination problem is the problem of finding the
minimum set $D$. Given a positive integer $k$ and a graph $G = (V, E)$, the
$[1,j]$-Domination Decision problem is to decide whether $G$ has
$[1,j]$-dominating set of cardinality at most $k$. A polynomial-time algorithm
was obtained in split graphs for a constant $j$ in contrast to the classic
Dominating Set problem which is NP-hard in split graphs. This result motivates
us to investigate the effect of restriction $j$ on the complexity of
$[1,j]$-domination problem on various classes of graphs. Although for $j\geq
3$, it has been proved that the minimum of classical domination is equal to
minimum $[1,j]$-domination in interval graphs, the complexity of finding the
minimum $[1,2]$-domination in interval graphs is still outstanding. In this
paper, we propose a polynomial-time algorithm for computing a minimum $[1,2]$
on non-proper interval graphs by a dynamic programming technique. Next, on the
negative side, we show that the minimum $[1,2]$-dominating set problem on
circle graphs is $NP$-complete.


  MINOS is an accelerator neutrino oscillation experiment at Fermilab. An
intense high energy neutrino beam is produced at Fermilab and sent to a near
detector on the Fermilab site and also to a 5 kTon far detector 735 km away in
the Soudan mine in northern Minnesota. The experiment has now had several years
of running with millions of events in the near detector and hundreds of events
recorded in the far detector. I will report on the recent results from this
experiment which include precise measurement of $|\Delta m^2_{32}|$, ~analysis
of neutral current data to limit the component of sterile neutrinos, and the
search for $\nu_\mu \to \nu_e$ conversion. The focus will be on the analysis of
data for $\nu_\mu \to \nu_e$ conversion. Using data from an exposure of
$3.14\times 10^{20}$ protons on target, we have selected electron type events
in both the near and the far detector. The near detector is used to measure the
background which is extrapolated to the far detector. We have found 35 events
in the signal region with a background expectation of $27\pm 5(stat)\pm
2(syst)$. Using this observation we set a 90% C.L. limit of $\sin^2 2
\theta_{13} < 0.29$ for $\delta_{cp} = 0$ and normal mass hierarchy. Further
analysis is under way to reduce backgrounds and improve sensitivity.


  Processes of heavy quark photoproduction at HERA energies are considered
using the semihard (k_T factorization) QCD approach with emphasis of the BFKL
dynamics of gluon distributions. We investigate the dependences of the total
cross section of heavy quark photoproduction and also p_T, and rapidity
distributions on different forms of the unintegrated gluon distribution. We
present a comparision of the theoretical results with available H1 and ZEUS
experimental data for charm and beauty photoproductions.


  Microlasers are of ample interest for advancing quantum chaos studies at the
intersection of wave dynamics and geometric optics in resonators. However, the
mode structures of three-dimensional microlasers without rotational symmetry
remain largely unexplored due to fabrication limitations. Previous studies of
such cavities revealed lasing modes localized on periodic orbits exclusively
confined to a single plane. In this work, we report on the characterization of
pyramidal, polymer-based microlasers and demonstrate that the lasing modes are
localized on a genuine three-dimensional periodic orbit. The consequences on
the laser features are further discussed, in particular stability and
polarization issues.


  The rheology of suspensions showing discontinuous shear thickening (DST) is
well documented in conventional rheometer with rotating tools, but their study
in capillary flow is still lacking. We present results obtained in a homemade
capillary rheometer working in an imposed pressure regime. We show that the
shape of the experimental curve giving the volume flow rate versus the wall
stress in a capillary can be qualitatively reproduced from the curve obtained
in rotational geometry at imposed stress but instead of a sharp decrease of the
volume flow rate observed at a critical stress, this transposition predicts a
progressive decrease in flow rate. The Wyart-Cates theory is used to reproduce
the stress-shear rate curve obtained in rotational geometry and then applied to
predict the volume flow rate at imposed pressure. The theoretical curve
predicts a total stop of the flow at high stress, whereas experimentally it
remains constant. We propose a modification of the theory which, by taking into
account the relaxation of the frictional contacts in the absence of shear rate,
well predicts the high stress behavior. We also hypothesized that the DST
transition propagates immediately inside the capillary, once the wall shear
stress has reached its critical value: $\tau_R=\tau_c$, even if the internal
shear stress $\tau(r<R)$ is below the critical one. In this way the whole
experimental curve can be well reproduced by the modified W-C model.


  We statistically estimate the conversion rate of the energy released during
an active-region transient brightening to Doppler motion and thermal and
non-thermal energies. We used two types of datasets for the energy estimation
and detection of transient brightenings. One includes spectroscopic images of
Fe xiv, Fe xv, and Fe xvi lines observed by the Hinode/EUV Imaging
Spectrometer. The other includes images obtained from the 211 \AA channel of
the Solar Dynamics Observatory/Atmospheric Imaging Assembly (AIA). The observed
active region was NOAA 11890 on November 09, 2013, and the day after that. As a
result, the released Doppler motion and non-thermal energies were found to be
approximately 0.1 \-- 1% and 10 \-- 100% of the change in the amount of thermal
energy in each enhancement, respectively. Using this conversion rate, we
estimated the contribution of the total energy flux of AIA transient
brightenings to the active region heating to be at most 2% of the conduction
and radiative losses.


  The following problem was posed by user "Kevin" on Mathoverflow. How to prove
this polynomial always has integer values at all integers?
$$P_m(x)=\sum_{i=0}^{m}\sum_{j=0}^{m} \binom{x+j}{j} \binom{x-1}{j}
\binom{j}{i} \binom{m}{i} \binom{i}{m-j} \frac{3}{(2i-1)(2j+1)(2m-2i-1)}.$$
  We provide an answer.


  V1118 Ori is an eruptive variable belonging to the EXor class of Pre-Main
Sequence stars whose episodic outbursts are attributed to disk accretion
events. Since 2006, V1118 Ori is in the longest quiescence stage ever observed
between two subsequent outbursts of its recent history. We present
near-infrared photometry of V1118 Ori carried out during the last eight years,
along with a complete spectroscopic coverage from 0.35 to 2.5 um. A longterm
sampling of V1118 Ori in quiescence has never been done, hence we can benefit
from the current circumstance to determine the lowest values (i.e. the zeroes)
of the parameters to be used as a reference for evaluating the physical changes
typical of more active phases. A quiescence mass accretion rate between 1--3
$\times$ 10$^{-9}$ M$_{\sun}$ yr$^{-1}$ can be derived and the difference with
previous determinations is discussed. From line emission and IR colors analysis
a visual extinction of 1-2 mag is consistently derived, confirming that V1118
Ori (at least in quiescence) is a low-extinction T Tauri star with a bolometric
luminosity of about 2.1 L$_{\sun}$. An anti-correlation exists between the
equivalent width of the emission lines and the underlying continuum. We
searched the literature for evaluating whether or not such a behaviour is a
common feature of the whole class. The anti-correlation is clearly recognizable
for all the available EXors in the optical range (H$\beta$ and H$\alpha$
lines), while it is not as much evident in the infrared (Pa$\beta$ and
Br$\gamma$ lines). The observed anti-correlation supports the accretion-driven
mechanism as the most likely to account for continuum variations.


  Molecular line observations of starless (prestellar) cores combined with a
chemical evolution modeling and radiative transfer calculations are a powerful
tool to study the earliest stages of star formation. However, conclusions drawn
from such a modeling may noticeably depend on the assumed thermal structure of
the cores. The assumption of isothermality, which may work well in
chemo-dynamical studies, becomes a critical factor in molecular line formation
simulations. We argue that even small temperature variations, which are likely
to exist in starless cores, can have a non-negligible effect on the
interpretation of molecular line data and derived core properties. In
particular, ``chemically pristine'' isothermal cores (low depletion) can have
centrally peaked C$^{18}$O and C$^{34}$S radial intensity profiles, while
having ring-like intensity distributions in models with a colder center and/or
warmer envelope assuming the same underlying chemical structure. Therefore,
derived molecular abundances based on oversimplified thermal models may lead to
a mis-interpretation of the line data.


  We prove stability of rank two tautological bundles on the Hilbert square of
a surface (under a mild positivity condition) and compute their Chern classes.


  So far, the infrared behavior of the gluon and ghost propagator based on the
Gribov-Zwanziger approach predicted a positivity violating gluon propagator
vanishing at zero momentum, and an infrared enhanced ghost propagator. However,
recent data based on huge lattices have revealed a positivity violating gluon
propagator which turns out to attain a finite nonvanishing value very close to
zero momentum. At the same time the ghost propagator does not seem to be
infrared enhanced anymore. We point out that these new features can be
accounted for by yet unexploited dynamical effects within the Gribov-Zwanziger
approach, leading to an infrared behavior in qualitatively good agreement with
the new data.


  From the moment astronomical observations are made the resulting data
products begin to grow stale. Even if perfect binary copies are preserved
through repeated timely migration to more robust storage media, data standards
evolve and new tools are created that require different kinds of data or
metadata. The expectations of the astronomical community change even if the
data do not. We discuss data engineering to mitigate the ensuing risks with
examples from a recent project to refactor seven million archival images to new
standards of nomenclature, metadata, format, and compression.


  A thrackle is a drawing of a graph in which each pair of edges meets
precisely once. Conway's Thrackle Conjecture asserts that a thrackle drawing of
a graph on the plane cannot have more edges than vertices. We prove the
Conjecture for thrackle drawings all of whose vertices lie on the boundaries of
$d \le 3$ connected domains in the complement of the drawing. We also give a
detailed description of thrackle drawings corresponding to the cases when $d=2$
(annular thrackles) and $d=3$ (pants thrackles).


  This article introduces new multiplicative updates for nonnegative matrix
factorization with the $\beta$-divergence and sparse regularization of one of
the two factors (say, the activation matrix). It is well known that the norm of
the other factor (the dictionary matrix) needs to be controlled in order to
avoid an ill-posed formulation. Standard practice consists in constraining the
columns of the dictionary to have unit norm, which leads to a nontrivial
optimization problem. Our approach leverages a reparametrization of the
original problem into the optimization of an equivalent scale-invariant
objective function. From there, we derive block-descent
majorization-minimization algorithms that result in simple multiplicative
updates for either $\ell_{1}$-regularization or the more "aggressive"
log-regularization. In contrast with other state-of-the-art methods, our
algorithms are universal in the sense that they can be applied to any
$\beta$-divergence (i.e., any value of $\beta$) and that they come with
convergence guarantees. We report numerical comparisons with existing heuristic
and Lagrangian methods using various datasets: face images, an audio
spectrogram, hyperspectral data, and song play counts. We show that our methods
obtain solutions of similar quality at convergence (similar objective values)
but with significantly reduced CPU times.


  We derive optimal-order homogenization rates for random nonlinear elliptic
PDEs with monotone nonlinearity in the uniformly elliptic case. More precisely,
for a random monotone operator on $\mathbb{R}^d$ with stationary law (i.e.
spatially homogeneous statistics) and fast decay of correlations on scales
larger than the microscale $\varepsilon>0$, we establish homogenization error
estimates of the order $\varepsilon$ in case $d\geq 3$, respectively of the
order $\varepsilon |\log \varepsilon|^{1/2}$ in case $d=2$. Previous results in
nonlinear stochastic homogenization have been limited to a small algebraic rate
of convergence $\varepsilon^\delta$. We also establish error estimates for the
approximation of the homogenized operator by the method of representative
volumes of the order $(L/\varepsilon)^{-d/2}$ for a representative volume of
size $L$. Our results also hold in the case of systems for which a
(small-scale) $C^{1,\alpha}$ regularity theory is available.


  New emerging technologies powered by Artificial Intelligence (AI) have the
potential to disruptively transform our societies for the better. In
particular, data-driven learning approaches (i.e., Machine Learning (ML)) have
been a true revolution in the advancement of multiple technologies in various
application domains. But at the same time there is growing concern about
certain intrinsic characteristics of these methodologies that carry potential
risks to both safety and fundamental rights. Although there are mechanisms in
the adoption process to minimize these risks (e.g., safety regulations), these
do not exclude the possibility of harm occurring, and if this happens, victims
should be able to seek compensation. Liability regimes will therefore play a
key role in ensuring basic protection for victims using or interacting with
these systems. However, the same characteristics that make AI systems
inherently risky, such as lack of causality, opacity, unpredictability or their
self and continuous learning capabilities, may lead to considerable
difficulties when it comes to proving causation. This paper presents three case
studies, as well as the methodology to reach them, that illustrate these
difficulties. Specifically, we address the cases of cleaning robots, delivery
drones and robots in education. The outcome of the proposed analysis suggests
the need to revise liability regimes to alleviate the burden of proof on
victims in cases involving AI technologies.