  Machine learning models have recently enjoyed a significant increase in size
and popularity. However, this growth has created concerns about dataset
privacy. To counteract data leakage, various privacy frameworks guarantee that
the output of machine learning models does not compromise their training data.
However, this privatization comes at a cost by adding random noise to the
training process, which reduces model performance. By making models more
resistant to small changes in input and thus more stable, the necessary amount
of noise can be decreased while still protecting privacy. This paper
investigates various techniques to enhance stability, thereby minimizing the
negative effects of privatization in machine learning.


  While new and effective methods for anomaly detection are frequently
introduced, many studies prioritize the detection task without considering the
need for explainability. Yet, in real-world applications, anomaly explanation,
which aims to provide explanation of why specific data instances are identified
as anomalies, is an equally important task. In this work, we present a novel
approach for efficient and accurate model-agnostic anomaly explanation for
tabular data using Predicate-based Association Rules (PARs). PARs can provide
intuitive explanations not only about which features of the anomaly instance
are abnormal, but also the reasons behind their abnormality. Our user study
indicates that the anomaly explanation form of PARs is better comprehended and
preferred by regular users of anomaly detection systems as compared to existing
model-agnostic explanation options. Furthermore, we conduct extensive
experiments on various benchmark datasets, demonstrating that PARs compare
favorably to state-of-the-art model-agnostic methods in terms of computing
efficiency and explanation accuracy on anomaly explanation tasks. The code for
PARs tool is available at https://github.com/NSIBF/PARs-EXAD.


  We improve the current upper bound on the axion-photon coupling derived from
stellar evolution using the $R_2$ parameter, the ratio of stellar populations
on the Asymptotic Giant Branch to Horizontal Branch in Globular Clusters. We
compare this with data from simulations using the stellar evolution code MESA
which include the effects of axion production. Particular attention is given to
quantifying in detail the effects of uncertainties on the $R$ and $R_2$
parameters due to the modelling of convective core boundaries. Using a
semiconvective mixing scheme we constrain the axion-photon coupling to be
$g_{a\gamma\gamma} < 0.47 \times 10^{-10}~\mathrm{GeV}^{-1}$. This rules out
new regions of QCD axion and axion-like particle parameter space. Complementary
evidence from asteroseismology suggests that this could improve to as much as
$g_{a\gamma\gamma} < 0.34 \times 10^{-10}~\mathrm{GeV}^{-1}$ as the
uncertainties surrounding mixing across convective boundaries are better
understood.


  This paper describes a novel approach to learning term-weighting schemes
(TWSs) in the context of text classification. In text mining a TWS determines
the way in which documents will be represented in a vector space model, before
applying a classifier. Whereas acceptable performance has been obtained with
standard TWSs (e.g., Boolean and term-frequency schemes), the definition of
TWSs has been traditionally an art. Further, it is still a difficult task to
determine what is the best TWS for a particular problem and it is not clear
yet, whether better schemes, than those currently available, can be generated
by combining known TWS. We propose in this article a genetic program that aims
at learning effective TWSs that can improve the performance of current schemes
in text classification. The genetic program learns how to combine a set of
basic units to give rise to discriminative TWSs. We report an extensive
experimental study comprising data sets from thematic and non-thematic text
classification as well as from image classification. Our study shows the
validity of the proposed method; in fact, we show that TWSs learned with the
genetic program outperform traditional schemes and other TWSs proposed in
recent works. Further, we show that TWSs learned from a specific domain can be
effectively used for other tasks.


  Chandra observations of nearby galaxies have revealed a number of X-ray
sources characterized by high luminosities ($L_X > \sim10^{36}$ erg s$^{-1}$)
and $k T$ in the range $100 - 350$ eV. These ``quasisoft X-ray sources'' (QSSs)
are harder than luminous supersoft X-ray sources (SSSs), whose characteristic
temperatures are tens of eV, but, with little or no emission above 2 keV, they
are significantly softer than most canonical X-ray sources. They are likely to
include a range of physical systems; some may be common systems in unusual
states: neutron stars or stellar-mass black holes (BHs), or SNRs. Others may be
accreting BHs of intermediate mass. We have analyzed {\it Chandra} data from
$19 $ near-by galaxies to identify QSSs with sufficiently high count rates to
allow spectral fits. Six of these galaxies have been studied in great detail;
in these we find 89 SSSs and 122 QSSs. In this paper we present spectra for
QSSs those with more than 50 counts. We also use data from six of these
galaxies to study the broadband spectral distributions of QSSs and to compare
them with those of other X-ray sources. Since QSSs in the Milky Way are likely
to be missed by our selection procedures, we discuss other signatures by which
they can be found. If some of the QSSs for which we have spectra are accreting
BHs, the lower bounds for the BH mass range from roughly $30 M_\odot$ to $1000
M_\odot$.


  The Pfaffian state, which may describe the quantized Hall plateau observed at
Landau level filling fraction $\nu = 5/2$, can support topologically-protected
qubits with extremely low error rates. Braiding operations also allow perfect
implementation of certain unitary transformations of these qubits. However, in
the case of the Pfaffian state, this set of unitary operations is not quite
sufficient for universal quantum computation (i.e. is not dense in the unitary
group). If some topologically unprotected operations are also used, then the
Pfaffian state supports universal quantum computation, albeit with some
operations which require error correction. On the other hand, if certain
topology-changing operations can be implemented, then fully
topologically-protected universal quantum computation is possible. In order to
accomplish this, it is necessary to measure the interference between
quasiparticle trajectories which encircle other moving trajectories in a
time-dependent Hall droplet geometry.


  We consider the question of implementability of a social choice function in a
classical setting where the preferences of finitely many selfish individuals
with private information have to be aggregated towards a social choice. This is
one of the central questions in mechanism design. If the concept of weak
implementation is considered, the Revelation Principle states that one can
restrict attention to truthful implementations and direct revelation
mechanisms, which implies that implementability of a social choice function is
easy to check. For the concept of strong implementation, however, the
Revelation Principle becomes invalid, and the complexity of deciding whether a
given social choice function is strongly implementable has been open so far. In
this paper, we show by using methods from polyhedral theory that strong
implementability of a social choice function can be decided in polynomial space
and that each of the payments needed for strong implementation can always be
chosen to be of polynomial encoding length. Moreover, we show that strong
implementability of a social choice function involving only a single selfish
individual can be decided in polynomial time via linear programming.


  We present the results of a photometric and spectroscopic analysis of the
Galactic Bulge Survey X-ray source CXOGBS J174954.5-294335 (hereafter, referred
to as CX19). CX19 is a long period, eclipsing intermediate polar type
cataclysmic variable with broad, single-peaked Balmer and Paschen emission
lines along with HeII $\lambda4686$ and Bowen blend emission features. With
coverage of one full and two partial eclipses and archival photometry, we
determine the ephemeris for CX19 to be HJD(eclipse) = 2455691.8581(5) +
0.358704(2)$\times$N. We also recovered the white dwarf spin period of P$_{\rm
spin}$ = 503.32(3) seconds which gives a P$_{\rm spin}$/P$_{\rm orb}$ =
0.016(6), comparable to several confirmed, long period intermediate polars.
CX19 also shows a clear X-ray eclipse in the 0.3-8.0 keV range observed with
Chandra. Two optical outbursts were observed lasting between 6-8 hours (lower
limits) reaching $\sim$1.3 mags in amplitude. The outbursts, both in duration
and magnitude, the accretion disc dominated spectra and hard X-ray emission are
reminiscent of the intermediate polar V1223 Sgr sharing many of the same
characteristics. If we assume a main sequence companion, we estimate the donor
to be an early G-type star and find a minimum distance of $d \approx$ 2.1 kpc
and a 0.5-10.0 keV X-ray luminosity upper limit of 2.0 $\times$ 10$^{33}$ erg
s$^{-1}$. Such an X-ray luminosity is consistent with a white dwarf accretor in
a magnetic cataclysmic variable system. To date, CX19 is only the second
deeply-eclipsing intermediate polar with X-ray eclipses and the first which is
optically accessible.


  Understanding the mechanism of electroweak symmetry breaking and the origin
of boson and fermion masses is among the most pressing questions raised in
contemporary particle physics. If these issues involve one (several) Higgs
boson(s), a precise measurement of all its (their) properties will be of prime
importance. Among those, the Higgs coupling to matter fermions (the Yukawa
coupling). At a Linear Collider, the process e+e- -> ttH will allow in
principle a direct measurement of the top-Higgs Yukawa coupling. We present a
realistic feasibility study of the measurement in the context of the TESLA
collider. Four channels are studied and the analysis is repeated for several
Higgs mass values within the range 120 GeV - 200 GeV.


  We investigate the structures of crossed products of the Cuntz algebra
${\mathcal O}_\infty$ by quasi-free actions of abelian groups. We completely
determine their ideal structures and compute the strong Connes spectra and
K-groups.


  The zCOSMOS SINFONI project is aimed at studying the physical and kinematical
properties of a sample of massive z~1.4-2.5 star-forming galaxies, through
SINFONI near-IR integral field spectroscopy (IFS), combined with the
multi-wavelength information from the zCOSMOS (COSMOS) survey. The project is
based on 1 hour of natural-seeing observations per target, and Adaptive Optics
(AO) follow-up for a major part of the sample, which includes 30 galaxies
selected from the zCOSMOS/VIMOS spectroscopic survey. This first paper presents
the sample selection, and the global physical characterization of the target
galaxies from multicolor photometry, i.e., star formation rate (SFR), stellar
mass, age, etc. The Halpha integrated properties such as, flux, velocity
dispersion, and size, are derived from the natural-seeing observations, while
the follow up AO observations will be presented in the next paper of this
series. Our sample appears to be well representative of star-forming galaxies
at z~2, covering a wide range in mass and SFR. The Halpha integrated properties
of the 25 Halpha detected galaxies are similar to those of other IFS samples at
the same redshifts. Good agreement is found among the SFRs derived from Halpha
luminosity and other diagnostic methods, provided the extinction affecting the
Halpha luminosity is about twice that affecting the continuum. A preliminary
kinematic analysis, based on the maximum observed velocity difference across
the source, and on the integrated velocity dispersion, indicates that the
sample splits nearly 50-50 into rotation-dominated and velocity
dispersion-dominated galaxies, in good agreement with previous surveys.


  Symmetry detection, especially partial and extrinsic symmetry, is essential
for various downstream tasks, like 3D geometry completion, segmentation,
compression and structure-aware shape encoding or generation. In order to
detect partial extrinsic symmetries, we propose to learn rotation, reflection,
translation and scale invariant local shape features for geodesic point cloud
patches via contrastive learning, which are robust across multiple classes and
generalize over different datasets. We show that our approach is able to
extract multiple valid solutions for this ambiguous problem. Furthermore, we
introduce a novel benchmark test for partial extrinsic symmetry detection to
evaluate our method. Lastly, we incorporate the detected symmetries together
with a region growing algorithm to demonstrate a downstream task with the goal
of computing symmetry-aware partitions of 3D shapes. To our knowledge, we are
the first to propose a self-supervised data-driven method for partial extrinsic
symmetry detection.


  A conic fibration has an associated sheaf of even Clifford algebras on the
base. In this paper, we study the relation between the moduli spaces of modules
over the sheaf of even Clifford algebras and the Prym variety associated to the
conic fibration. In particular, we construct a rational map from the moduli
space of modules over the sheaf of even Clifford algebras to the special
subvarieties in the Prym variety, and check that the rational map is birational
in some cases. As an application, we get an explicit correspondence between
instanton bundles of minimal charge on cubic threefolds and twisted Higgs
bundles on curves.


  We propose an algorithm to reduce a k-chromatic graph to a complete graph of
largest possible order through a well defined sequence of contractions. We
introduce a new matrix called transparency matrix and state its properties. We
then define correct contraction procedure to be executed to get largest
possible complete graph from given connected graph. We finally give a
characterization for k-chromatic graphs and use it to settle Hadwigers
conjecture.


  Owing to the analogy with the ordinary photons in the visible range of the
electromagnetic spectrum, the Glauber theory is generalized to address the
quantum coherence of the gauge field fluctuations parametrically amplified
during an inflationary stage of expansion. The first and second degrees of
quantum coherence of relic photons are then computed beyond the effective
horizon defined by the evolution of the susceptibility. In the zero-delay limit
the Hanbury Brown-Twiss correlations exhibit a super-Poissonian statistics
which is however different from the conventional results of the single-mode
approximation customarily employed, in quantum optics, to classify the
coherence properties of visible light. While in the case of large-scale
curvature perturbations the degrees of quantum coherence coincide with the
naive expectation of the single-mode approximation, the net degree of
second-order coherence computed for the relic photons diminishes thanks to the
effect of the polarizations. We suggest that the Hanbury Brown-twiss
correlations are probably the only tool to assess the quantum or classical
origin of the large-scale magnetic fluctuations and of the corresponding
curvature perturbations.


  Context. We have recently investigated the origin of chemical signatures
observed in Galactic halo stars by means of a stochastic chemical evolution
model. We have found that rotating massive stars are a promising way to explain
several signatures observed in these fossil stars. Aims. In the present paper
we discuss how the extremely metal-poor halo star TYC 8442-1036-1, for which we
have now obtained detailed abundances from VLT-UVES spectra, fits into the
framework of our previous work. Methods. We apply a standard 1D LTE analysis to
the spectrum of this star. We measure the abundances of 14 chemical elements;
for Na, Mg, Ca, Sc, Ti, V, Cr, Mn, Fe, Ni and Zn we compute the abundances
using equivalent widths; for C, Sr and Ba we obtain the abundances by means of
synthetic spectra generated by MOOG. Results. We find an abundance of [Fe/H]=
$-$3.5 $\pm$0.13 dex based on our high resolution spectrum; this points to an
iron content lower by a factor of three (0.5 dex) compared to the one obtained
by a low resolution spectrum. The star has a [C/Fe] = 0.4 dex, and it is not
carbon enhanced like most of the stars at this metallicity. Moreover, this star
lies in the plane [Ba/Fe] vs. [Fe/H] in a relatively unusual position, shared
by a few others galactic halo stars that is only marginally explained by our
past results. Conclusions. The comparison of the model results with the
chemical abundance characteristics of this group of stars can be improved if we
consider in our model the presence of faint supernovae coupled with rotating
massive stars. These results seem to imply that rotating massive stars and
faint supernovae scenarios are complementary to each other, and are both
required in order to match the observed chemistry of the earliest phases of the
chemical enrichment of the Universe.


  In this study, we present a general framework for comparing two dynamical
processes that describe the synchronization of oscillators coupled through
networks of the same size. We introduce a measure of dissimilarity defined in
terms of a metric on a hypertorus, allowing us to compare the phases of coupled
oscillators. In the first part, this formalism is implemented to examine
systems of networked identical phase oscillators that evolve with the Kuramoto
model. In particular, we analyze the effect of the weight of an edge in the
synchronization of two oscillators, the introduction of new sets of edges in
interacting cycles, the effect of bias in the couplings, and the addition of a
link in a ring. We also compare the synchronization of nonisomorphic graphs
with four nodes. Finally, we explore the dissimilarities generated when we
contrast the Kuramoto model with its linear approximation for different random
initial phases in deterministic and random networks. The approach introduced
provides a general tool for comparing synchronization processes on networks,
allowing us to understand the dynamics of a complex system as a consequence of
the coupling structure and the processes that can occur in it.


  Let $A(x)=A\_0+x\_1A\_1+...+x\_nA\_n$ be a linear matrix, or pencil,
generated by given symmetric matrices $A\_0,A\_1,...,A\_n$ of size $m$ with
rational entries. The set of real vectors x such that the pencil is positive
semidefinite is a convex semi-algebraic set called spectrahedron, described by
a linear matrix inequality (LMI). We design an exact algorithm that, up to
genericity assumptions on the input matrices, computes an exact algebraic
representation of at least one point in the spectrahedron, or decides that it
is empty. The algorithm does not assume the existence of an interior point, and
the computed point minimizes the rank of the pencil on the spectrahedron. The
degree $d$ of the algebraic representation of the point coincides
experimentally with the algebraic degree of a generic semidefinite program
associated to the pencil. We provide explicit bounds for the complexity of our
algorithm, proving that the maximum number of arithmetic operations that are
performed is essentially quadratic in a multilinear B\'ezout bound of $d$. When
$m$ (resp. $n$) is fixed, such a bound, and hence the complexity, is polynomial
in $n$ (resp. $m$). We conclude by providing results of experiments showing
practical improvements with respect to state-of-the-art computer algebra
algorithms.


  We consider the problem of minimizing the sum of a smooth function $h$ with a
bounded Hessian, and a nonsmooth function. We assume that the latter function
is a composition of a proper closed function $P$ and a surjective linear map
$\cal M$, with the proximal mappings of $\tau P$, $\tau > 0$, simple to
compute. This problem is nonconvex in general and encompasses many important
applications in engineering and machine learning. In this paper, we examined
two types of splitting methods for solving this nonconvex optimization problem:
alternating direction method of multipliers and proximal gradient algorithm.
For the direct adaptation of the alternating direction method of multipliers,
we show that, if the penalty parameter is chosen sufficiently large and the
sequence generated has a cluster point, then it gives a stationary point of the
nonconvex problem. We also establish convergence of the whole sequence under an
additional assumption that the functions $h$ and $P$ are semi-algebraic.
Furthermore, we give simple sufficient conditions to guarantee boundedness of
the sequence generated. These conditions can be satisfied for a wide range of
applications including the least squares problem with the $\ell_{1/2}$
regularization. Finally, when $\cal M$ is the identity so that the proximal
gradient algorithm can be efficiently applied, we show that any cluster point
is stationary under a slightly more flexible constant step-size rule than what
is known in the literature for a nonconvex $h$.


  We consider the dynamical evolution of a thin rod described by an
appropriately scaled wave equation of nonlinear elasticity. Under the
assumption of well-prepared initial data and external forces, we prove that a
solution exists for arbitrarily large times, if the diameter of the cross
section is chosen sufficiently small. The scaling regime is such that the
limiting equations are linear.


  The experimental sensitivity to $\mu \to e$ conversion on nuclei is set to
improve by four orders of magnitude in coming years. However, various operator
coefficients add coherently in the amplitude for $\mu \to e$ conversion,
weighted by nucleus-dependent functions, and therefore in the event of a
detection, identifying the relevant new physics scenarios could be difficult.
Using a representation of the nuclear targets as vectors in coefficient space,
whose components are the weighting functions, we quantify the expectation that
different nuclear targets could give different constraints.We show that all but
two combinations of the 10 Spin-Independent (SI) coefficients could be
constrained by future measurements, but discriminating among the axial, tensor
and pseudoscalar operators that contribute to the Spin-Dependent (SD) process
would require dedicated nuclear calculations. We anticipate that $\mu \to e$
conversion could constrain 10 to 14 combinations of coefficients; if $\mu \to e
\gamma$ and $\mu \to 3e$ constrain eight more, that leaves 60 to 64 "flat
directions" in the basis of QED$\times$QCD-invariant operators which describe
$\mu \to e$ flavour change below $m_W$.


  We show that the count of rational points by de la Bret\`{e}che, Browning and
Salberger on the Cayley ruled cubic surface extends to all non-normal integral
hypercubics which are not cones.


  We propose a novel architecture for federated learning within healthcare
consortia. At the heart of the solution is a unique integration of privacy
preserving technologies, built upon native enterprise blockchain components
available in the Ethereum ecosystem. We show how the specific characteristics
and challenges of healthcare consortia informed our design choices, notably the
conception of a new Secure Aggregation protocol assembled with a protected
hardware component and an encryption toolkit native to Ethereum. Our
architecture also brings in a privacy preserving audit trail that logs events
in the network without revealing identities.


  I analyze $D$-$\ol D$ mixing using the techniques of heavy quark effect field
theory. The analysis suggests that the there may be important cancellations
among the dispersive effects of different kinds of final states, so that the
total mixing may be considerably smaller than previous estimates.


  We propose a scheme for measuring topological properties in a
two-photon-driven Kerr-nonlinear resonator (KNR) subjected to a single-photon
modulation. The topological properties are revealed through the observation of
the Berry curvature and hence the first Chern number, as a nonadiabatic
response of the physical observable to the change rate of the control parameter
of the modulated drive. The parameter manifold, constructed from the system's
Hamiltonian that determines its dynamics constrained in the state space spanned
by the even and odd cat states as two basis states, is adjusted so that the
degeneracy crossing the manifold indicates a topological transition. The
scheme, with such continuous variable states in mesoscpic systems, provides a
new perspective for exploration of the geometry and the related topology with
complex systems.


  Most state-of-the-art semi-supervised video object segmentation methods rely
on a pixel-accurate mask of a target object provided for the first frame of a
video. However, obtaining a detailed segmentation mask is expensive and
time-consuming. In this work we explore an alternative way of identifying a
target object, namely by employing language referring expressions. Besides
being a more practical and natural way of pointing out a target object, using
language specifications can help to avoid drift as well as make the system more
robust to complex dynamics and appearance variations. Leveraging recent
advances of language grounding models designed for images, we propose an
approach to extend them to video data, ensuring temporally coherent
predictions. To evaluate our method we augment the popular video object
segmentation benchmarks, DAVIS'16 and DAVIS'17 with language descriptions of
target objects. We show that our language-supervised approach performs on par
with the methods which have access to a pixel-level mask of the target object
on DAVIS'16 and is competitive to methods using scribbles on the challenging
DAVIS'17 dataset.


  The apparent conflict between general relativity and quantum mechanics
remains one of the unresolved mysteries of the physical world. According to
recent theories, this conflict results in gravity-induced quantum state
reduction of "Schr\"odinger cats", quantum superpositions of macroscopic
observables. In recent years, great progress has been made in cooling
micromechanical resonators towards their quantum mechanical ground state. This
work is an important step towards the creation of Schr\"odinger cats in the
laboratory, and the study of their destruction by decoherence. A direct test of
the gravity-induced state reduction scenario may therefore be within reach.
However, a recent analysis shows that for all systems reported to date, quantum
superpositions are destroyed by environmental decoherence long before
gravitational state reduction takes effect. Here we report optical trapping of
glass microspheres in vacuum with high oscillation frequencies, and cooling of
the center-of-mass motion from room temperature to a minimum temperature of 1.5
mK. This new system eliminates the physical contact inherent to clamped
cantilevers, and can allow ground-state cooling from room temperature. After
cooling, the optical trap can be switched off, allowing a microsphere to
undergo free-fall in vacuum. During free-fall, light scattering and other
sources of environmental decoherence are absent, so this system is ideal for
studying gravitational state reduction. A cooled optically trapped object in
vacuum can also be used to search for non-Newtonian gravity forces at small
scales, measure the impact of a single air molecule, and even produce
Schr\"odinger cats of living organisms.


  Pinpointing the neutrino sources is crucial to unveil the mystery of
high-energy cosmic rays. The search for neutrino-source candidates from
coincident neutrino-photon signatures and electromagnetic objects with peculiar
flaring behaviors have the potential to increase our chances of finding
neutrino emitters. In this paper, we first study the temporal correlations of
astrophysical flares with neutrinos, considering a few hundreds of
multi-frequency sources from ALMA, WISE, Swift, and Fermi in the containment
regions of IceCube high-energy alerts. Furthermore, the spatial correlations
between blazars and neutrinos are investigated using the subset of 10-year
IceCube track-like neutrinos with around 250 thousand events. In the second
test, we account for 2700 blazars with different types of flaring phases in
addition to sole position. No significant neutrino emissions were found from
our analyses. Our results indicate an interesting trend showing the infrared
flaring stages of WISE blazars might be correlated with arrival times of the
neutrino alerts. Possible overflow of neutrinos associated with two of our
blazar sub-samples are also illustrated. One is characterized by a significant
flaring lag in infrared with respect to gamma-rays, like seen for TXS0506+056,
and the other is characterized by highly simultaneous infrared and gamma-ray
flares. These phenomena suggest the need to improve current multi-frequency
light-curve catalogs to pair with the advent of more sensitive neutrino
observatories.


  In this paper, we study the asymptotic behavior of the colored Jones
polynomials evaluated at roots of unity for a special class of knots. We show
that certain limit is zero as predicted by the volume conjecture.


  The twisting function describing a nonstandard (super-Jordanian) quantum
deformation of $osp(1|2)$ is given in explicite closed form. The quantum
coproducts and universal R-matrix are presented. The non-uniqueness of the
twisting function as well as two real forms of the deformed $osp(1|2)$
superalgebras are considered. One real quantum $osp(1|2)$ superalgebra is
interpreted as describing the $\kappa$-deformation of D=1, N=1 superconformal
algebra, which can be applied as a symmetry algebra of N=1 superconformal
mechanics.


  This paper explores goal-directed proof search in first-order multi-modal
logic. The key issue is to design a proof system that respects the modularity
and locality of assumptions of many modal logics. By forcing ambiguities to be
considered independently, modular disjunctions in particular can be used to
construct efficiently executable specifications in reasoning tasks involving
partial information that otherwise might require prohibitive search. To achieve
this behavior requires prior proof-theoretic justifications of logic
programming to be extended, strengthened, and combined with proof-theoretic
analyses of modal deduction in a novel way.


  Laser-produced Sn plasma sources are used to generate extreme ultraviolet
(EUV) light in state-of-the-art nanolithography. An ultraviolet and optical
spectrum is measured from a droplet-based laser-produced Sn plasma, with a
spectrograph covering the range 200 - 800 nm. This spectrum contains hundreds
of spectral lines from lowly charged tin ions Sn$^{1+}$ - Sn$^{4+}$ of which a
major fraction was hitherto unidentified. We present and identify a selected
class of lines belonging to the quasi-one-electron, Ag-like ([Kr]$4d^{10} nl$
electronic configuration), Sn$^{3+}$ ion, linking the optical lines to a
specific charge state by means of a masking technique. These line
identifications are made with iterative guidance from COWAN code calculations.
Of the 53 lines attributed to Sn$^{3+}$, some 20 were identified from
previously known energy levels, and 33 lines are used to determine previously
unknown level energies of 13 electronic configurations, i.e., $ 7p $, $ (7,8)d
$, $ (5,6)f $, $ (6-8)g $, $ (6-8)h $, $ (7,8)i $. The consistency of the level
energy determination is verified by the quantum-defect scaling procedure. The
ionization limit of Sn$^{3+}$ is confirmed and refined to 328908.4 cm$^{-1}$
with an uncertainty of 2.1 cm$^{-1}$. The relativistic Fock space coupled
cluster (FSCC) calculation of the measured level energies are generally in good
agreement with experiment, but fail to reproduce the anomalous behavior of the
$5d$ $^2$D and $nf$ $^2$F terms. By combining the strengths of FSCC, COWAN code
calculations, and configuration interaction many-body perturbation theory
(CI+MBPT), this behavior is shown to arise from interactions with
doubly-excited configurations.


  Despite recent progress towards scaling up multimodal vision-language models,
these models are still known to struggle on compositional generalization
benchmarks such as Winoground. We find that a critical component lacking from
current vision-language models is relation-level alignment: the ability to
match directional semantic relations in text (e.g., "mug in grass") with
spatial relationships in the image (e.g., the position of the mug relative to
the grass). To tackle this problem, we show that relation alignment can be
enforced by encouraging the directed language attention from 'mug' to 'grass'
(capturing the semantic relation 'in') to match the directed visual attention
from the mug to the grass. Tokens and their corresponding objects are softly
identified using the cross-modal attention. We prove that this notion of soft
relation alignment is equivalent to enforcing congruence between vision and
language attention matrices under a 'change of basis' provided by the
cross-modal attention matrix. Intuitively, our approach projects visual
attention into the language attention space to calculate its divergence from
the actual language attention, and vice versa. We apply our Cross-modal
Attention Congruence Regularization (CACR) loss to UNITER and improve on the
state-of-the-art approach to Winoground.


  This letter considers temporal-correlated massive access, where each device,
once activated, is likely to transmit continuously over several consecutive
frames. Motivated by that the device activity at each frame is correlated to
not only its previous frame but also its next frame, we propose a double-sided
information (DSI) aided joint activity detection and channel estimation
algorithm based on the approximate message passing (AMP) framework. The DSI is
extracted from the estimation results in a sliding window that contains the
target detection frame and its previous and next frames. The proposed algorithm
demonstrates superior performance over the state-of-the-art methods.


  Density-based spatial clustering of applications with noise (DBSCAN) is a
data clustering algorithm which has the high-performance rate for dataset where
clusters have the constant density of data points. One of the significant
attributes of this algorithm is noise cancellation. However, DBSCAN
demonstrates reduced performances for clusters with different densities.
Therefore, in this paper, an adaptive DBSCAN is proposed which can work
significantly well for identifying clusters with varying densities.


  Central limit theorems (CLTs) for high-dimensional random vectors with
dimension possibly growing with the sample size have received a lot of
attention in the recent times. Chernozhukov et al. (2017) proved a
Berry--Esseen type result for high-dimensional averages for the class of
hyperrectangles and they proved that the rate of convergence can be upper
bounded by $n^{-1/6}$ upto a polynomial factor of $\log p$ (where $n$
represents the sample size and $p$ denotes the dimension). Convergence to zero
of the bound requires $\log^7p = o(n)$. We improve upon their result which only
requires $\log^4p = o(n)$ (in the best case). This improvement is made possible
by a sharper dimension-free anti-concentration inequality for Gaussian process
on a compact metric space. In addition, we prove two non-uniform variants of
the high-dimensional CLT based on the large deviation and non-uniform CLT
results for random variables in a Banach space by Bentkus, Ra{\v c}kauskas, and
Paulauskas. We apply our results in the context of post-selection inference in
linear regression and of empirical processes.


  Inference for causal effects can benefit from the availability of an
instrumental variable (IV) which, by definition, is associated with the given
exposure, but not with the outcome of interest other than through a causal
exposure effect. Estimation methods for instrumental variables are now well
established for continuous outcomes, but much less so for dichotomous outcomes.
In this article we review IV estimation of so-called conditional causal odds
ratios which express the effect of an arbitrary exposure on a dichotomous
outcome conditional on the exposure level, instrumental variable and measured
covariates. In addition, we propose IV estimators of so-called marginal causal
odds ratios which express the effect of an arbitrary exposure on a dichotomous
outcome at the population level, and are therefore of greater public health
relevance. We explore interconnections between the different estimators and
support the results with extensive simulation studies and three applications.


  Until recently it was believed that photosynthesis, a fundamental process for
life on earth, could be fully understood with semi-classical models. However,
puzzling quantum phenomena have been observed in several photosynthetic
pigment-protein complexes, prompting questions regarding the nature and role of
these effects. Recent attention has focused on discrete vibrational modes that
are resonant or quasi-resonant with excitonic energy splittings and strongly
coupled to these excitonic states. Here we unambiguously identify excited state
coherent superpositions in photosynthetic light-harvesting complexes using a
new experimental approach. Decoherence on the timescale of the excited state
lifetime allows low energy (56 cm-1) oscillations on the signal intensity to be
observed. In conjunction with an appropriate model, these oscillations provide
clear and direct experimental evidence that the persistent coherences observed
require strong vibronic mixing among excited states.


  We present several equilibrium methods that allow to compute isentropic
processes, either during the compression or the release of the material. These
methods are applied to compute the isentropic release of a shocked monoatomic
liquid at high pressure and temperature. Moreover, equilibrium results of
isentropic release are compared to the direct nonequilibrium simulation of the
same process. We show that due to the viscosity of the liquid but also to
nonequilibrium effects, the release of the system is not strictly isentropic.


  Machine Learning models, extensively used for various multimedia
applications, are offered to users as a blackbox service on the Cloud on a
pay-per-query basis. Such blackbox models are commercially valuable to
adversaries, making them vulnerable to extraction attacks to reverse engineer
the proprietary model thereby violating the model privacy and Intellectual
Property. Here, the adversary first extracts the model architecture or
hyperparameters through side channel leakage, followed by stealing the
functionality of the target model by training the reconstructed architecture on
a synthetic dataset. While the attacks proposed in literature are empirical,
there is a need for a theoretical framework to measure the information leaked
under such extraction attacks. To this extent, in this work, we propose a novel
probabilistic framework, Airavata, to estimate the information leakage in such
model extraction attacks. This framework captures the fact that extracting the
exact target model is difficult due to experimental uncertainty while inferring
model hyperparameters and stochastic nature of training to steal the target
model functionality. Specifically, we use Bayesian Networks to capture
uncertainty in estimating the target model under various extraction attacks
based on the subjective notion of probability. We validate the proposed
framework under different adversary assumptions commonly adopted in literature
to reason about the attack efficacy. This provides a practical tool to infer
actionable details about extracting blackbox models and help identify the best
attack combination which maximises the knowledge extracted (or information
leaked) from the target model.


  This paper explores new methods for locating the sources used to write a
text, by fine-tuning a variety of language models to rerank candidate sources.
After retrieving candidates sources using a baseline BM25 retrieval model, a
variety of reranking methods are tested to see how effective they are at the
task of source attribution. We conduct experiments on two datasets, English
Wikipedia and medieval Arabic historical writing, and employ a variety of
retrieval and generation based reranking models. In particular, we seek to
understand how the degree of supervision required affects the performance of
various reranking models. We find that semisupervised methods can be nearly as
effective as fully supervised methods while avoiding potentially costly
span-level annotation of the target and source documents.


  In photo-sensor cameras of Cherenkov telescopes the light images from
particle showers always contain the background noise induced by photons of the
night sky. An image cleaning procedure is needed to reduce the contribution of
those noise photons in further analysis stages. The conventional topological
next neighbor method lacks reconstruction efficiency for low light content
images and image peripheries with low signal levels. We present here a simple
optimization of the traditional next-neighbor image cleaning method that
exploits the limited time duration of shower flashes and short time-difference
between neighboring image pixels. This method reduces greatly the noise
contribution by applying dynamical cuts in the parameter space formed by signal
amplitude and time-difference between neighboring pixels


  An effective approach to improve the detection efficiency of nanoscale light
sources relies on a planar antenna configuration, which beams the emitted light
into a narrow cone. Planar antennas operate like optical Yagi-Uda antennas,
where reflector and director elements are made of metal films. Here we
introduce and investigate, both theoretically and experimentally, a scanning
implementation of a planar antenna. Using a small ensemble of molecules
contained in fluorescent nanobeads placed in the antenna, we independently
address the intensity, the radiation pattern and the decay rate as a function
of distance between a flat-tip scanning gold wire (reflector) and a thin gold
film coated on a glass coverslip (director). The scanning planar antenna
changes the radiation pattern of a single fluorescent bead and it beams light
into a narrow cone down to angles of 45{\deg} (full width at half maximum).
Moreover, the collected signal compared to the case of a glass coverslip is
larger than a factor of 3, which is mainly due to the excitation enhancement.
These results offer a better understanding of the modification of light-matter
interaction by planar antennas and they hold promise for applications, such as
sensing, imaging and diagnostics.


  Polarimetry is a novel tool to detect and characterize exoplanets and their
atmospheres. Polarized scattered light from the non-transiting hot Jupiter
$\upsilon$~And~b is measured to further constrain its orbit, mass, density, and
geometrical albedo. We obtained polarimetric measurements in the $UBV$ bands
over the orbital period and deduce an average peak-to-peak amplitude of $(49
\pm 5)\times10^{-6}$ in both Stokes $q$ and $u$. From our data we evaluate the
orbit inclination $i=111\degr\pm11\degr$, longitude of the ascending node
$\Omega=236\degr\pm12\degr$ (or equivalently 56\degr), the effective size of
the scattering atmosphere in the optical blue of $1.36\pm0.20$\,$R_{\rm J}$.
These combined with spectroscopic measurements result in the planet mass
$0.74\pm0.07$\,$M_{\rm J}$, mean density $0.36\pm0.08$\,g\,cm$^{-3}$, and
surface gravity $\sim10^3$\,cm\,s$^{-2}$, which favor a close similarity of
$\upsilon$~And~b to other inflated hot Jupiters. We also significantly improved
the periastron epoch $T_{\rm p}={\rm JD}2,450,032.451$, interior conjunction
epoch $T_{\rm t}={\rm JD}2,450,034.668$, and periastron longitude
$\omega=279\degr\pm14\degr$. The latter indicates that the apsidal resonance
known for planets c and d includes also planet b.
  Obtained limits on the wavelength dependent geometrical albedo (average 0.35)
indicate its similarity to Neptune with peak reflectivity in the blue.
Combining all available measurements at various passbands, we construct a
unified wavelength dependent albedo of an average hot Jupiter. It appears to be
largely shaped by Rayleigh scattering in the blue and atomic and molecular
absorption in the optical and near infrared. Our findings demonstrate the power
of polarimetry for studying non-transiting exoplanets.


  This paper is devoted to the nonlinear analysis of a kinetic model introduced
by Saintillan and Shelley to describe suspensions of active rodlike particles
in viscous flows. We investigate the stability of the constant state
$\Psi(t,x,p) = \frac{1}{4\pi} $ corresponding to a distribution of particles
that is homogeneous in space (variable $x \in \mathbb{T}^3$) and uniform in
orientation (variable $p \in \mathbb{S}^2$). We prove its nonlinear stability
under the optimal condition of linearized spectral stability, without any
addition of spatial diffusion. The mathematical novelty and difficulty compared
to previous linear studies comes from the presence of a quasilinear term in $x$
due to nonlinear convection. A key feature of our work, which we hope to be of
independent interest, is an analysis of enhanced dissipation and mixing
properties of the advection diffusion operator $$\partial_t + (p + u(t,x))
\cdot \nabla_x - \nu \Delta_p $$ on $\mathbb{T}^3 \times \mathbb{S}^2$ for a
given appropriately small vector field $u$.


  In this paper, we generalize the notion of border bases of zero-dimensional
polynomial ideals to the module setting. To this end, we introduce order
modules as a generalization of order ideals and module border bases of
submodules with finite codimension in a free module as a generalization of
border bases of zero-dimensional ideals in the first part of this paper. In
particular, we extend the division algorithm for border bases to the module
setting, show the existence and uniqueness of module border bases, and
characterize module border bases analogously like border bases via the special
generation property, border form modules, rewrite rules, commuting matrices,
and liftings of border syzygies. Furthermore, we deduce Buchberger's Criterion
for Module Border Bases and give an algorithm for the computation of module
border bases that uses linear algebra techniques. In the second part, we
further generalize the notion of module border bases to quotient modules. We
then show the connection between quotient module border bases and special
module border bases and deduce characterizations similar to the ones for module
border bases. Moreover, we give an algorithm for the computation of quotient
module border bases using linear algebra techniques, again. At last, we prove
that subideal border bases are isomorphic to special quotient module border
bases. This isomorphy immediately yields characterizations and an algorithm for
the computation of subideal border bases.


  A Rayleigh-Taylor-like instability of a dense colloidal layer under gravity
in a capillary of microfluidic dimensions is considered. We access all relevant
lengthscales with particle-level microscopy and computer simulations which
incorporate long-range hydrodynamic interactions between the particles. By
tuning the gravitational driving force, we reveal a mechanism whose growth is
connected to the fluctuations of specific wavelengths, non-linear pattern
formation and subsequent diffusion-dominated relaxation. Our linear stability
theory captures the initial regime and thus predicts mixing conditions, with
important implications for fields ranging from biology to nanotechnology.


  The problem is considered as to whether a monotone function defined on a
subset P of a Euclidean space can be strictly monotonically extended to the
whole space. It is proved that this is the case if and only if the function is
{\em separably increasing}. Explicit formulas are given for a class of
extensions which involves an arbitrary bounded increasing function. Similar
results are obtained for monotone functions that represent strict partial
orders on arbitrary abstract sets X. The special case where P is a Pareto
subset is considered.


  The nature and properties of dark matter (DM) are both outstanding issues in
physics. Besides clustering in halos, the universal character of gravity
implies that self-gravitating compact DM configurations might be spread
throughout the universe. The astrophysical signature of these objects may be
used to probe fundamental particle physics, or even to provide an alternative
description of compact objects in active galactic nuclei. Here we discuss the
most promising dissection tool of these configurations: the inspiral of a
compact stellar-size object and consequent gravitational-wave emission. The
inward motion of this "test probe" encodes unique information about the nature
of the central, supermassive DM configuration. When the probe travels through
some compact DM profile we show that, within a Newtonian approximation, the
quasi-adiabatic evolution of the inspiral is mainly driven by DM accretion into
the small compact object and by dynamical friction, rather than by
gravitational-wave radiation-reaction. These effects circularize the orbits and
leave a peculiar imprint on the gravitational waves emitted at late time. When
accretion dominates, the frequency and the amplitude of the gravitational-wave
signal produced during the latest stages of the inspiral are nearly constant.
In the exterior region we study a relativistic model in which the inspiral is
driven by the emission of gravitational and scalar waves. Resonances in the
energy flux appear whenever the orbital frequency matches the mass of the DM
particle and they correspond to the excitation of the central object's
quasinormal frequencies. Unexpectedly, these resonances can lead to large
dephasing with respect to standard inspiral templates, to such an extent as to
prevent detection with matched filtering techniques. We discuss some
observational consequences of these effects for gravitational-wave detection.


  We analyze possible nodal superconducting phases that emerge from a doped
nodal-line semimetal. We show that nodal-line superconducting phases are
favored by interactions mediated by short-range ferromagnetic fluctuations or
Hund's coupling. It is found that the leading pairing channels are
momentum-independent, orbital-singlet and spin-triplet. In the pairing state,
we show that the Bogoliubov-de Gennes (BdG) Hamiltonian hosts a pair of
topologically protected nodal rings on the equators of the torus Fermi surface
(FS). Using a topological classification for gapless systems with inversion
symmetry, we find that these nodal rings are topologically nontrivial and
protected by integer-valued monopole charges $\nu = \pm 2$. In the scenario of
pairing driven by ferromagnetic fluctuations, we analyze the fate of
superconductivity in the magnetically ordered phase. Based on Ginzburg-Landau
free energy analysis, we find the energetically favored superconducting state
is characterized by the coexistence of two pairing orders whose $\bf d$-vectors
are perpendicular to the magnetization axis $\bf M$ with their phases unfixed.
In this case, each nodal loop in the pairing state splits into two, carrying a
$\pm 1$ monopole charge. For bulk-boundary correspondence, these nodal rings
enclose flat-band Majorana zero modes on top and bottom surface Brillouin Zones
with distinct $\mathbb{Z}$-valued topological invariants.


  The notion of a natural model of type theory is defined in terms of that of a
representable natural transfomation of presheaves. It is shown that such models
agree exactly with the concept of a category with families in the sense of
Dybjer, which can be regarded as an algebraic formulation of type theory. We
determine conditions for such models to satisfy the inference rules for
dependent sums, dependent products, and intensional identity types, as used in
homotopy type theory. It is then shown that a category admits such a model if
it has a class of maps that behave like the abstract fibrations in axiomatic
homotopy theory: they should be stable under pullback, closed under composition
and relative products, and there should be weakly orthogonal factorizations
into the class. It follows that many familiar settings for homotopy theory also
admit natural models of the basic system of homotopy type theory.


  To understand how planetary systems form in the dusty disks around
pre-main-sequence stars a detailed knowledge of the structure and evolution of
these disks is required. While this is reasonably well understood for the
regions of the disk beyond about 1 AU, the structure of these disks inward of 1
AU remains a puzzle. This is partly because it is very difficult to spatially
resolve these regions with current telescopes. But it is also because the
physics of this region, where the disk becomes so hot that the dust starts to
evaporate, is poorly understood. With infrared interferometry it has become
possible in recent years to directly spatially resolve the inner AU of
protoplanetary disks, albeit in a somewhat limited way. These observations have
partly confirmed current models of these regions, but also posed new questions
and puzzles. Moreover, it has turned out that the numerical modeling of these
regions is extremely challenging. In this review we give a rough overview of
the history and recent developments in this exciting field of astrophysics.


  We present optical multi-colour photometry of V404 Cyg during the outburst
from December, 2015 to January, 2016 together with the simultaneous X-ray data.
This outburst occurred less than 6 months after the previous outburst in
June-July, 2015. These two outbursts in 2015 were of a slow rise and rapid
decay-type and showed large-amplitude ($\sim$2 mag) and short-term ($\sim$10
min-3 hours) optical variations even at low luminosity (0.01-0.1$L_{\rm Edd}$).
We found correlated optical and X-ray variations in two $\sim$1 hour time
intervals and performed Bayesian time delay estimations between them. In the
previous version, the observation times of X-ray light curves were measured at
the satellite and their system of times was Terrestrial Time (TT), while those
of optical light curves were measured at the Earth and their system of times
was Coordinated Universal Time (UTC). In this version, we have corrected the
observation times and obtained a Bayesian estimate of an optical delay against
the X-ray emission, which is $\sim$30 s, during those two intervals. In
addition, the relationship between the optical and X-ray luminosity was $L_{\rm
opt} \propto L_{\rm X}^{0.25-0.29}$ at that time. These features can be
naturally explained by disc reprocessing.


  A method is proposed to use of the mixture of Uran oxide and non-active
matrix (e.g., NaCl) and also potassium and lanthanum for determining
Ge-detector efficiencies. The preparations containing of known amouts of the U
or K, or La were measured by means of the Ge-detector, which a efficiency curve
has been obtained through the reference solutions of 241Am, 109Cd, 57Co, 139Ce,
137Cs, 60Co. Results the measurements were compared the activities of the
preparations calculated from mass of 235U, 238U, 138La, 40K in the samples, its
natural abundance, half lives and intensities of gamma lines. Discrepancy of
the activities in the energy range between 163 and 1461 keV does not exeed 7 %.
For correct comparison of the activities the coefficients {\omega} were
calculated, which took into consideration a varied sorption of gamma-rays in
water and in mixture of the Uran oxide and matrix.


  We apply two non-parametric methods to test further the hypothesis that
log-periodicity characterizes the detrended price trajectory of large financial
indices prior to financial crashes or strong corrections. The analysis using
the so-called (H,q)-derivative is applied to seven time series ending with the
October 1987 crash, the October 1997 correction and the April 2000 crash of the
Dow Jones Industrial Average (DJIA), the Standard & Poor 500 and Nasdaq
indices. The Hilbert transform is applied to two detrended price time series in
terms of the ln(t_c-t) variable, where t_c is the time of the crash. Taking all
results together, we find strong evidence for a universal fundamental
log-frequency $f = 1.02 \pm 0.05$ corresponding to the scaling ratio $\lambda =
2.67 \pm 0.12$. These values are in very good agreement with those obtained in
past works with different parametric techniques.


  Motivated by recent experiment on the Na$_4$Ir$_3$O$_8$ compound we study the
Hubbard model on the "hyper-kagome lattice", which forms a three-dimensional
network of corner sharing triangles, using dynamical cluster approximation
(DCA) method with $N_c$=12 combined with the continuous-time quantum Monte
Carlo (CT QMC) method. The system undergoes a Mott transition if the Hubbard
interaction $U/W$ ($W$ is the bandwidth) exceeds the value of 1.2 for $T$=0.1
and displays reentrant behavior due to competition between the magnetic
correlation and the kinetic energy of electrons due to the geometrical
frustration. We observe a "critical slowing down" of the double occupancy which
shows evidence of a continuous transition. The nearest-neighbor and next
nearest-neighbor spin-spin correlations indicate a paramagnetic metallic state
in the weak-coupling regime and an antiferromagnetic (AF) Mott insulator in the
strong-coupling regime within the temperature range which we can access with
our numerical tools.


  The Vliegenthart-Lekkerkerker relation for the second virial coefficient
value at the critical temperature found in [G. A. Vliegenthart and H. N. W.
Lekkerkerker, J. Chem. Phys. \textbf{112} 5364 (2000)] is discussed in
connection with the scale invariant mean-field approach proposed in [V. L.
Kulinskii and L. A. Bulavin, J. Chem. Phys. \textbf{133} 134101 (2010)]. We
study the case of the Mie-class potentials which is widely used in simulations
of the phase equilibrium of the fluids. It is shown that due to the homogeneity
property of the $Mie$-class potentials it is possible to connect the loci of
the fluids with these model potentials in different dimensions.


  Acute lymphoblastic leukemia (ALL) and chronic lymphocytic leukemia (CLL) are
two major forms of leukemia that arise from lymphoid cells (LCs). ALL occurs
mostly in children and CLL occurs mainly in old people. However, the
Philadelphia-chromosome-positive ALL (Ph+-ALL) and the Ph-like ALL occur in
both children and adults. To understand childhood leukemia/lymphoma, we have
recently proposed two hypotheses on the causes and the mechanism of cell
transformation of a LC. Hypothesis A is: repeated bone-remodeling during
bone-growth and bone-repair may be a source of cell injuries of marrow cells
including hematopoietic stem cells (HSCs), myeloid cells, and LCs. Hypothesis B
is: a LC may have three pathways on transformation: a slow, a rapid, and an
accelerated. We discuss in the present paper the developing mechanisms of ALL
and CLL by these hypotheses. Having a peak incidence in young children, ALL may
develop mainly as a result of rapid cell transformation of a lymphoblast (or
pro-lymphocyte). Differently, Ph+-ALL and Ph-like ALL may develop as results of
transformation of a lymphoblast via accelerated pathway. Occurring mainly in
adults, CLL may be a result of transformation of a memory B-cell via slow
pathway. By causing cell injuries of HSCs and LCs, repeated bone-remodeling
during bone-growth and bone-repair may be related to the cell transformation of
a LC. In conclusion, ALL may develop as a result of cell transformation of a
lymphoblast via rapid or accelerated pathway; and repeated bone-remodeling
during bone-growth may be a trigger for the cell transformation of a
lymphoblast in a child.


  Let $G$ be a countable discrete group. We give a necessary and sufficient
condition for a transitive $G$-system to be disjoint with all minimal
$G$-systems, which implies that if a transitive $G$-system is disjoint with all
minimal $G$-systems, then it is $\infty$-transitive, i.e. $(X^k,G)$ is
transitive for all $k\in\N$, and has dense minimal points. In addition, we show
that any $\infty$-transitive $G$-system with dense distal points are disjoint
with all minimal $G$-systems.


  Solvable supersymmetric algebraic model for descriptions of the spherical to
gama unstable shape- phase transition in even and odd mass nuclei is proposed.
This model is based on dual algebraic structure and Richardson - Gaudin method,
where the duality relations between the unitary and quasispin algebraic
structures for the boson and fermion systems are extended to mixed boson-
fermion system. The structure of two type of nuclear supersymmetry schemes,
based on the U(6/2) and U(6/4) supergroups, is discussed. We investigate the
change in level structure induced by the phase transition by doing a quantal
analysis. By using the generalized quasispin algebra, it is shown that the
nuclear supersymmetry concept can be also used for transitional regions in
addition to dynamical symmetry limits. Experimental evidence for the U(5)-O(6)
transition in Ru-Rh and Zn- Cu supermultiplets is presented. The low-states
energy spectra and B(E2)values for these nuclei have been calculated and
compared with the experimental data.


  The one-loop effective action for a generic set of quantum fields is
calculared as a nonlocal expansion in powers of the curvatures (field
strengths). This expansion is obtained to third order in the curvature. It is
stressed that the covariant vertices are finite. The trace anomaly in four
dimensions is obtained directly by varying the effective action. The nonlocal
terms in the action, producing the anomaly, contain non-trivial functions of
three operator arguments. The trace anomaly is derived also by making the
conformal transformation in the heat kernel.


  The advent of large language models trained on code (code LLMs) has led to
significant progress in language-to-code generation. State-of-the-art
approaches in this area combine LLM decoding with sample pruning and reranking
using test cases or heuristics based on the execution results. However, it is
challenging to obtain test cases for many real-world language-to-code
applications, and heuristics cannot well capture the semantic features of the
execution results, such as data type and value range, which often indicates the
correctness of the program. In this work, we propose LEVER, a simple approach
to improve language-to-code generation by learning to verify the generated
programs with their execution results. Specifically, we train verifiers to
determine whether a program sampled from the LLMs is correct or not based on
the natural language input, the program itself and its execution results. The
sampled programs are reranked by combining the verification score with the LLM
generation probability, and marginalizing over programs with the same execution
results. On four datasets across the domains of table QA, math QA and basic
Python programming, LEVER consistently improves over the base code LLMs(4.6% to
10.9% with code-davinci-002) and achieves new state-of-the-art results on all
of them.


  The Kronig-Penney model, an exactly solvable one-dimensional model of crystal
in solid physics, shows how the allowed and forbidden bands are formed in
solids. In this paper, we study this model in the presence of both strong
spin-orbit coupling and the Zeeman field. We analytically obtain four
transcendental equations that represent an implicit relation between the energy
and the Bloch wavevector. Solving these four transcendental equations, we
obtain the spin-orbital bands exactly. In addition to the usual band gap opened
at the boundary of the Brillouin zone, a much larger spin-orbital band gap is
also opened at some special sites inside the Brillouin zone. The $x$-component
of the spin-polarization vector is an even function of the Bloch wavevector,
while the $z$-component of the spin-polarization vector is an odd function of
the Bloch wavevector. At the band edges, the optical transition rates between
adjacent bands are nonzero.


  This paper focuses on the data-insufficiency problem in multi-task learning
within an episodic training setup. Specifically, we explore the potential of
heterogeneous information across tasks and meta-knowledge among episodes to
effectively tackle each task with limited data. Existing meta-learning methods
often fail to take advantage of crucial heterogeneous information in a single
episode, while multi-task learning models neglect reusing experience from
earlier episodes. To address the problem of insufficient data, we develop
Heterogeneous Neural Processes (HNPs) for the episodic multi-task setup. Within
the framework of hierarchical Bayes, HNPs effectively capitalize on prior
experiences as meta-knowledge and capture task-relatedness among heterogeneous
tasks, mitigating data-insufficiency. Meanwhile, transformer-structured
inference modules are designed to enable efficient inferences toward
meta-knowledge and task-relatedness. In this way, HNPs can learn more powerful
functional priors for adapting to novel heterogeneous tasks in each meta-test
episode. Experimental results show the superior performance of the proposed
HNPs over typical baselines, and ablation studies verify the effectiveness of
the designed inference modules.


  The majority of planetary nebulae (PNe) are not spherical, and current
single-star models cannot adequately explain all the morphologies we observe.
This has led to the Binary Hypothesis, which states that PNe are preferentially
formed by binary systems. This hypothesis can be corroborated or disproved by
comparing the estimated binary fraction of all PNe central stars (CS) to that
of the supposed progenitor population. One way to quantify the rate of CS
binarity is to detect near infra-red (IR) excess indicative of a low-mass main
sequence companion. In this paper, a sample of known PNe within data release 2
of the ongoing VPHAS+ are investigated. We give details of the method used to
calibrate VPHAS+ photometry, and present the expected colours of CS and main
sequence stars within the survey. Objects were scrutinized to remove PN mimics
from our sample and identify true CS. Within our final sample of 7 CS, 6 had
previously either not been identified or confirmed. We detected an $i$ band
excess indicative of a low-mass companion star in 3 CS, including one known
binary, leading us to to conclude that VPHAS+ provides the precise photometry
required for the IR excess method presented here, and will likely improve as
the survey completes and the calibration process finalised. Given the promising
results from this trial sample, the entire VPHAS+ catalogue should be used to
study PNe and extend the IR excess-tested CS sample.


  Many applications require linking individuals, firms, or locations across
datasets. Most widely used methods, especially in social science, do not employ
deep learning, with record linkage commonly approached using string matching
techniques. Moreover, existing methods do not exploit the inherently multimodal
nature of documents. In historical record linkage applications, documents are
typically noisily transcribed by optical character recognition (OCR). Linkage
with just OCR'ed texts may fail due to noise, whereas linkage with just image
crops may also fail because vision models lack language understanding (e.g., of
abbreviations or other different ways of writing firm names). To leverage
multimodal learning, this study develops CLIPPINGS (Contrastively LInking
Pooled Pre-trained Embeddings). CLIPPINGS aligns symmetric vision and language
bi-encoders, through contrastive language-image pre-training on document images
and their corresponding OCR'ed texts. It then contrastively learns a metric
space where the pooled image-text embedding for a given instance is close to
embeddings in the same class (e.g., the same firm or location) and distant from
embeddings of a different class. Data are linked by treating linkage as a
nearest neighbor retrieval problem with the multimodal embeddings. CLIPPINGS
outperforms widely used string matching methods by a wide margin in linking
mid-20th century Japanese firms across financial documents. A purely
self-supervised model - trained only by aligning the embeddings for the image
crop of a firm name and its corresponding OCR'ed text - also outperforms
popular string matching methods. Fascinatingly, a multimodally pre-trained
vision-only encoder outperforms a unimodally pre-trained vision-only encoder,
illustrating the power of multimodal pre-training even if only one modality is
available for linking at inference time.


  Grothendieck proved that any locally free sheaf on a projective line over a
field (uniquely) decomposes into a direct sum of line bundles. Ishii and Uehara
construct an analogue of Grothendieck's theorem for pure sheaves on the
fundamental cycle of the Kleinian singularity $A_n$. We first study the
analogue for the other Kleinian singularities except for $A_n$. We also study
the classification of rigid pure sheaves on the reduced scheme of the
fundamental cycles. The classification is related to the classification of
spherical objects in a certain Calabi-Yau $2$-dimensional category.


  Higher-derivative corrections to cosmological effective actions in string
theory are largely constrained by T-duality, but have been computed hitherto
only to the first few orders in the string scale $\alpha'$. The functional
renormalization group, in conjunction with the strong constraints imposed by
T-duality, allows to derive cosmological effective actions to all orders in
$\alpha'$ while avoiding "truncations" of the theory space. We show that the
resulting higher-derivative $\alpha'$-corrections forbid the existence of de
Sitter vacua, at least in regimes where string-loop corrections can be
neglected. Our findings thus support the implications of the no-de Sitter
swampland conjecture in the presence of all-order effects in $\alpha'$.


  Deployed supervised machine learning models make predictions that interact
with and influence the world. This phenomenon is called performative prediction
by Perdomo et al. (ICML 2020). It is an ongoing challenge to understand the
influence of such predictions as well as design tools so as to control that
influence. We propose a theoretical framework where the response of a target
population to the deployed classifier is modeled as a function of the
classifier and the current state (distribution) of the population. We show
necessary and sufficient conditions for convergence to an equilibrium of two
retraining algorithms, repeated risk minimization and a lazier variant.
Furthermore, convergence is near an optimal classifier. We thus generalize
results of Perdomo et al., whose performativity framework does not assume any
dependence on the state of the target population. A particular phenomenon
captured by our model is that of distinct groups that acquire information and
resources at different rates to be able to respond to the latest deployed
classifier. We study this phenomenon theoretically and empirically.


  This paper presents the AToMiC (Authoring Tools for Multimedia Content)
dataset, designed to advance research in image/text cross-modal retrieval.
While vision-language pretrained transformers have led to significant
improvements in retrieval effectiveness, existing research has relied on
image-caption datasets that feature only simplistic image-text relationships
and underspecified user models of retrieval tasks. To address the gap between
these oversimplified settings and real-world applications for multimedia
content creation, we introduce a new approach for building retrieval test
collections. We leverage hierarchical structures and diverse domains of texts,
styles, and types of images, as well as large-scale image-document associations
embedded in Wikipedia. We formulate two tasks based on a realistic user model
and validate our dataset through retrieval experiments using baseline models.
AToMiC offers a testbed for scalable, diverse, and reproducible multimedia
retrieval research. Finally, the dataset provides the basis for a dedicated
track at the 2023 Text Retrieval Conference (TREC), and is publicly available
at https://github.com/TREC-AToMiC/AToMiC.


  This paper proposes a Deep Learning based edge detector, which is inspired on
both HED (Holistically-Nested Edge Detection) and Xception networks. The
proposed approach generates thin edge-maps that are plausible for human eyes;
it can be used in any edge detection task without previous training or fine
tuning process. As a second contribution, a large dataset with carefully
annotated edges has been generated. This dataset has been used for training the
proposed approach as well the state-of-the-art algorithms for comparisons.
Quantitative and qualitative evaluations have been performed on different
benchmarks showing improvements with the proposed method when F-measure of ODS
and OIS are considered.


  In this paper, we analyze the clustering of galaxies using a modified
Newtonian potential. This modification of the Newtonian potential occurs due to
the existence of extra dimensions in brane world models. We will analyze a
system of galaxies interacting with each other through this modified Newtonian
potential. The partition function for this system of galaxies will be
calculated, and this partition function will be used to calculate the free
energy of this system of galaxies. The entropy and the chemical potential for
this system will also be calculated. We will derive explicit expression for the
clustering parameter for this system. This parameter will determine the
behavior of this system, and we will be able to express various thermodynamic
quantities using this clustering parameter. Thus, we will be able to explicitly
analyze the effect that modifying the Newtonian potential can have on the
clustering of galaxies. We also analyze the effect of extra dimensions on the
two-point functions between galaxies.


  Let F : X --> X be a morphism of a variety defined over a number field K, let
V be a K-subvariety of X, and let O_F(P)= {F^n(P) :n=0,1,2,...} be the orbit of
a point P in X(K). We describe a local-global principle for the intersection of
V and O_F(P). This principle may be viewed as a dynamical analog of the
Brauer-Manin obstruction. We show that the rational points of V(K) are
Brauer--Manin unobstructed for power maps on P^2 in two cases: (1) V is a
translate of a torus. (2) V is a line and P has a preperiodic coordinate. A key
tool in the proofs is the classical Bang-Zsigmondy theorem on primitive
divisors in sequences. We also prove analogous local-global results for
dynamical systems associated to endomoprhisms of abelian varieties.


  The weight distribution of the binary self-dual $[128,64]$ code being the
extended code $C^{*}$ of the code $C$ spanned by the incidence vectors of the
blocks of the polarity design in $PG(6,2)$ [11] is computed. It is shown also
that $R(3,7)$ and $C^{*}$ have no self-dual $[128,64,d]$ neighbor with $d \in
\{ 20, 24 \}$.


  We consider a mobile edge computing problem, in which mobile users offload
their computation tasks to computing nodes (e.g., base stations) at the network
edge. The edge nodes compute the requested functions and communicate the
computed results to the users via wireless links. For this problem, we propose
a Universal Coded Edge Computing (UCEC) scheme for linear functions to
simultaneously minimize the load of computation at the edge nodes, and maximize
the physical-layer communication efficiency towards the mobile users. In the
proposed UCEC scheme, edge nodes create coded inputs of the users, from which
they compute coded output results. Then, the edge nodes utilize the computed
coded results to create communication messages that zero-force all the
interference signals over the air at each user. Specifically, the proposed
scheme is universal since the coded computations performed at the edge nodes
are oblivious of the channel states during the communication process from the
edge nodes to the users.


  We measure simultaneously the properties of the energy spectra and the
frequencies of the kilohertz quasi-periodic oscillations (QPOs) in fifteen low
mass X-ray binaries covering a wide range of X-ray luminosities. In each source
the QPO frequencies cover the same range of approximately 300 Hz to 1300 Hz,
though the sources differ by two orders of magnitude in their X-ray
luminosities (as measured from the unabsorbed 2-50 keV flux). So the X-ray
luminosity does not uniquely determine the QPO frequency. This is difficult to
understand since the evidence from individual sources indicates that the
frequency and luminosity are very well correlated at least over short
timescales. Perhaps beaming effects or bolometric corrections change the
observed luminosities, or perhaps part of the energy in mass accretion is used
to power outflows reducing the energy emitted in X-rays. It is also possible
that the parameters of a QPO model are tuned in such a way that the same range
of frequencies appears in all sources. Different modes of accretion may be
involved for example (disk and radial) or multiple parameters may conspire to
yield the same frequencies.


  This paper deals with different concepts for characterizing the size of
mathematical objects. A game theoretic investigation and generalization of two
size concepts, which can both be formulated in topological terms, is provided:
the so called "Baire category" and the "$\sigma $-category". This is mainly
done by means of (generalized) Banach-Mazur games using the Axiom of
determinacy (the inconsistency of AC and AD is reflected in the beginning and a
weaker form of AC is chosen for proofs). Analogue versions of Cantor-Bendixson
and Heine-Borel are proofed as well as some definability results.
  Such size concepts are established f.i. in measure and integration theory,
set theory and topology often leading to mathematically precise formulations of
"fuzziness". In measure and integration theory f.i. one defines for a "measure
space" $(\Omega, \underline{A}, \mu)$ - i.e. $\Omega$ is a non empty set,
$\underline{A}$ a $\sigma$-algebra on $\Omega$ and $\mu$ a measure on
$(\Omega,\underline{A})$ - and a property $E \subset \Omega$ of elements of
$\Omega$, that the property $E$ is valid in a set $A\in\underline{A}$
"$\mu$-almost everywhere", if $E$ is true in $A$ up to a "$\mu$-null set" -
i.e. $\exists N\in\underline{A}{ } (\mu(N)=0 \wedge A\cap N^\complement \subset
E)$. This is crucial for the formulation of uniqueness statements in measure
and integration theory as its theorems usually only apply up to "small"
($\mu$-null) sets.
  Key words: Axiom of choice AC, Axiom of determinacy AD, Baire category
theorem, Baire property, Baire space, Banach-Mazur games, Borel hierachy,
Cantor-Bendixson, definability, Gale-Stewart, Heine-Borel, Lusin hierarchy,
meager sets, perfect set property, polish spaces, projective hierarchy, sigma
bounded sets, sigma compact sets, superperfect sets, topological games, winning
strategy


  We determine the two loop corrections to the Green's function of a quark
current inserted in a quark 2-point function at the symmetric subtraction
point. The amplitudes for the scalar, vector and tensor currents are presented
in both the MSbar and RI'/SMOM renormalization schemes. The RI'/SMOM scheme two
loop renormalization for the scalar and tensor cases agree with previous work.
The vector current renormalization requires special treatment as it must be
consistent with the Slavnov-Taylor identity which we demonstrate. We also
discuss the possibility of an alternative definition of the RI'/SMOM scheme in
the case of the tensor current.


  Let a simple random walk run inside a torus of dimension three or higher for
a number of steps which is a constant proportion of the volume. We examine
geometric properties of the range, the random subgraph induced by the set of
vertices visited by the walk. Distance and mixing bounds for the typical range
are proven that are a $k$-iterated log factor from those on the full torus for
arbitrary $k$. The proof uses hierarchical renormalization and techniques that
can possibly be applied to other random processes in the Euclidean lattice. We
use the same technique to bound the heat kernel of a random walk on random
interlacements.


  We have started a survey of M 33 in order to find variable stars and Cepheids
in particular. We have obtained more than 30 epochs of g'r'i' data with the
CFHT and the one-square-degree camera MegaCam. We present first results from
this survey, including the search for variable objects and a basic
characterization of the various groups of variable stars.


  Polymer rheology profoundly influences the intricate dynamics of material
extrusion in Fused Filament Fabrication (FFF). This numerical study, which uses
the Giesekus model fed with a full rheometric experimental data set,
meticulously examines the molten flow patterns inside the printing nozzle
during FFF. Our findings reveal new insights into the interplay between elastic
stresses and complex flow patterns, highlighting their substantial role in
forming upstream vortices. The parametric map $\alpha$-$\lambda$ from the
Giesekus model allowed us to sort the materials and connect the polymer
rheology with the FFF nozzle flow dynamics. The identification of elastic
instabilities, the characterization of flow types, and the correlation between
fluid rheology and pressure drop variations mark significant advancements in
understanding FFF processes. These insights pave the way for tailored nozzle
designs, promising enhanced efficiency and reliability in FFF-based additive
manufacturing


  It is believed that large-scale horseshoe-like brightness asymmetries found
in dozens of transitional protoplanetary discs are caused by anticyclonic
vortices. These vortices can play a key role in planet formation, as mm-sized
dust -- the building blocks of planets -- can be accumulated inside them.
Anticyclonic vortices are formed by the Rossby wave instability, which can be
excited at the gap edges opened by a giant planet or at sharp viscosity
transitions of accretionally inactive regions. It is known that vortices are
prone to stretching and subsequent dissolution due to disc self-gravity for
canonical disc masses in the isothermal approximation. To improve the
hydrodynamic model of protoplanetary discs, we include the disc thermodynamics
in our model. In this paper, we present our results on the evolution of the
vortices formed at the outer edge of an accretionally inactive region (dead
zone) assuming an ideal equation of state and taking $PdV$ work, disc cooling
in the $\beta$-approximation, and disc self-gravity into account.
Thermodynamics affects the offset and the mode number (referring to the number
of small vortices at the early phase) of the RWI excitation, as well as the
strength, shape, and lifetime of the large-scale vortex formed through merging
of the initial small vortices. We found that the inclusion of gas
thermodynamics results in stronger, however decreased lifetime vortices. Our
results suggest that a hypothetical vortex-aided planet formation scenario
favours effectively cooling discs.


  We study the influence of the electromagnetic vacuum force on the behaviour
of a model device based on materials, like germanium tellurides, that undergo
fast and reversible metal-insulator transitions on passing from the crystalline
to the amorphous phase. The calculations are performed at finite temperature
and fully accounting for the behaviour of the material dielectric functions.
The results show that the transition can be exploited to extend the distance
and energy ranges under which the device can be operated without undergoing
stiction phenomena. We discuss the approximation involved in adopting the
Casimir expression in simulating nano- and micro- devices at finite
temperature.


  We investigate conditioning Galton-Watson trees on general recursive-type
events, such as the event that the tree survives until a specific level. It
turns out that the conditioned tree is again a type of Galton-Watson tree, with
different types of offspring and a level-dependent offspring distribution,
which will all be given explicitly. As an interesting application of these
results, we will calculate the expected cost of searching a tree until reaching
a given level.


  For a quasi-split connected reductive group $G$ over a local field $F$ we
define a compact abelian group $\tilde\pi_1(G)$ and an extension $1 \to
\tilde\pi_1(G) \to G(F)_\infty \to G(F) \to 1$ of topological groups equipped
with a splitting over $G_\textrm{sc}(F)$. Any character $x : \tilde\pi_1(G) \to
\mu_n(\mathbb{C})$ leads to an $n$-fold cover $G(F)_x$ of $G(F)$ via pushout.
We define an $L$-group $^LG_x$ for this cover that is generally a non-split
extension of $\textrm{Gal}(F^s/F)$ by $\hat G$. We prove a refined local
Langlands correspondence for $G(F)_x$, assuming it is known for connected
reductive groups with the same adjoint group as $G$.
  Motivation for this construction comes from considerations of Langlands'
functoriality conjecture, where subgroups $\mathcal{H} \subset {^LG}$ of the
$L$-group of $G$ arise that need not be $L$-groups of other reductive groups.
If such a subgroup is full and intersects $\hat G$ in a connected reductive
subgroup of maximal rank, we construct a natural triple $(H,x,\xi)$ consisting
of a quasi-split connected reductive group $H$, a double cover $H(F)_x$, and an
$L$-embedding $\xi : {^LH}_x \to {^LG}$ that is an isomorphism onto
$\mathcal{H}$. We expect that genuine representations of $H(F)_x$ transfer
functorially to representations of $G(F)$.
  In the special case of endoscopy, we show that the construction of transfer
factors simplifies when the natural double cover $H(F)_x$ of the endoscopic
group is used. The transfer factor becomes the product of two natural
invariants that do not depend on auxiliary choices. One of them is closely
related to Kottwitz's work on transfer factors for Lie algebras. The other one
is not specific to the case of endoscopy, and will likely play a role in
general functoriality questions. Our work is motivated by work of Adams and
Vogan over the real numbers.


  Programmable packet-processing devices such as programmable switches and
network interface cards are becoming mainstream. These devices are configured
in a domain-specific language such as P4, using a compiler to translate
packet-processing programs into instructions for different targets. As networks
with programmable devices become widespread, it is critical that these
compilers be dependable.
  This paper considers the problem of finding bugs in compilers for packet
processing in the context of P4-16. We introduce domain-specific techniques to
induce both abnormal termination of the compiler (crash bugs) and
miscompilation (semantic bugs). We apply these techniques to (1) the
open-source P4 compiler (P4C) infrastructure, which serves as a common base for
different P4 back ends; (2) the P4 back end for the P4 reference software
switch; and (3) the P4 back end for the Barefoot Tofino switch.
  Across the 3 platforms, over 8 months of bug finding, our tool Gauntlet
detected 96 new and distinct bugs (62 crash and 34 semantic), which we
confirmed with the respective compiler developers. 54 have been fixed (31 crash
and 23 semantic); the remaining have been assigned to a developer. Our
bug-finding efforts also led to 6 P4 specification changes. We have open
sourced Gauntlet at p4gauntlet.github.io and it now runs within P4C's
continuous integration pipeline.


  Extensive research works demonstrate that the attention mechanism in
convolutional neural networks (CNNs) effectively improves accuracy.
Nevertheless, few works design attention mechanisms using large receptive
fields. In this work, we propose a novel attention method named Rega-net to
increase CNN accuracy by enlarging the receptive field. Inspired by the
mechanism of the human retina, we design convolutional kernels to resemble the
non-uniformly distributed structure of the human retina. Then, we sample
variable-resolution values in the Gabor function distribution and fill these
values in retina-like kernels. This distribution allows essential features to
be more visible in the center position of the receptive field. We further
design an attention module including these retina-like kernels. Experiments
demonstrate that our Rega-Net achieves 79.96% top-1 accuracy on ImageNet-1K
classification and 43.1% mAP on COCO2017 object detection. The mAP of the
Rega-Net increased by up to 3.5% compared to baseline networks.


  This thesis is concerned with studying the properties of gradings on several
examples of cluster algebras, primarily of infinite type.
  We first consider two finite type cases: $B_n$ and $C_n$, completing a
classification by Grabowski for coefficient-free finite type cluster algebras.
  We then consider gradings arising from $3 \times 3$ skew-symmetric matrices.
We show that the mutation-cyclic matrices give rise to gradings in which all
degrees are positive and have only finitely many associated cluster variables
(excepting one particular case). For the mutation-acyclic matrices, we prove
that all occurring degrees have infinitely many variables.
  We provide a sufficient condition for a graded cluster algebra generated by a
quiver to have infinitely many degrees, based on the presence of a subquiver in
its mutation class. We use this to show that the cluster algebras for (quantum)
coordinate rings of matrices and Grassmannians contain cluster variables of all
degrees in $\mathbb{N}$.
  Next we consider the list (given by Felikson, Shapiro & Tumarkin) of
mutation-finite quivers that do not correspond to triangulations of marked
surfaces. We show that $X_7$ gives rise to only two degrees, both with
infinitely many variables, and that $\widetilde{E}_6$, $\widetilde{E}_7$ and
$\widetilde{E}_8$ give rise to infinitely many variables in some degrees.
  Finally, we study gradings arising from marked surfaces (see Fomin, Shapiro &
Thurston). We adapt a definition by Muller to define the space of valuation
functions on such a surface and prove combinatorially that it is isomorphic to
the space of gradings on the associated cluster algebra. We illustrate this
theory by applying it to the annulus with $n+m$ marked points. We show that the
standard grading is of mixed type. We also give an alternative grading in which
all degrees have infinitely many cluster variables.


  The plane-of-satellites problem is one of the most severe small-scale
challenges for the standard $\Lambda$CDM cosmological model: several dwarf
galaxies around the Milky Way and Andromeda co-orbit in thin, planar
structures. A similar case has been identified around the nearby elliptical
galaxy Centaurus A (Cen A). In this Letter, we study the satellite system of
Cen A adding twelve new galaxies with line-of-sight velocities from VLT/MUSE
observations. We find 21 out of 28 dwarf galaxies with measured velocities
share a coherent motion. Similarly flattened and coherently moving structures
are found only in 0.2% of Cen A analogs in the Illustris-TNG100 cosmological
simulation, independently of whether we use its dark-matter-only or
hydrodynamical run. These analogs are not co-orbiting, and arise only by chance
projection, thus they are short-lived structures in such simulations. Our
findings indicate that the observed co-rotating planes of satellites are a
persistent challenge for $\Lambda$CDM, which is largely independent from baryon
physics.


  In his book "Differential Geometry of Spray and Finsler spaces", page 177,
Zhongmin Shen asks "wether or not there always exist non-trivial Funk functions
on a spray space". In this note, we will prove that the answer is negative for
the geodesic spray of a finslerian function of non-vanishing scalar flag
curvature.


  In the standard DNA brick set-up, distinct 32-nucleotide strands of
single-stranded DNA are each designed to bind specifically to four other such
molecules. Experimentally, it has been demonstrated that the overall yield is
increased if certain bricks which occur on the outer faces of target structures
are merged with adjacent bricks. However, it is not well understood by what
mechanism such `boundary bricks' increase the yield, as they likely influence
both the nucleation process and the final stability of the target structure.
Here, we use Monte Carlo simulations with a patchy particle model of DNA bricks
to investigate the role of boundary bricks in the self-assembly of complex
multicomponent target structures. We demonstrate that boundary bricks lower the
free-energy barrier to nucleation and that boundary bricks on edges stabilize
the final structure. However, boundary bricks are also more prone to
aggregation, as they can stabilize partially assembled intermediates. We
explore some design strategies that permit us to benefit from the stabilizing
role of boundary bricks whilst minimizing their ability to hinder assembly; in
particular, we show that maximizing the total number of boundary bricks is not
an optimal strategy.


  We have examined some basic properties of damped Ly$\alpha$ systems(DLAs) by
semi-analytic model. We assume that DLA hosts are disk galaxies whose mass
function is generated by Press-Schechter formulism at redshift 3. Star
formation and chemical evolution undergo in the disc. We select modelled DLAs
according to their observational criterion by Monte Carlo simulation using
random line of sights and disk inclinations. The DLA ages are set to be 1 to 3
Gyr. By best-fitting the predicted metallicity distribution to the observed
ones, we get the effective yield for DLAs about $0.25Z_{\odot}$. On the basis
of this constrain, we further compared our model predictions with observations
at redshift 3 in the following items: number density; gas content; HI frequency
distribution; star formation rate density; relationship between metallicity and
HI column density. We found that the predicted number density at redshift 3
agree well with the observed value, but the gas content $\Omega_{DLA}$ is about
3 times larger than observed since our model predicts more DLA systems with
higher column density. The frequency distribution at higher HI column density
is quite consistent with observation while some difference exists at lower HI
end. The predicted star formation rate density contributed by DLAs is
consistent with the most recent observations. Meanwhile, the connection between
DLAs and Lyman Break galaxies(LBGs) is discussed by comparing their UV
luminosity functions which shows that the DLAs host galaxies are much fainter
than LBGs. However, there is a discrepancy between model prediction and
observation in the correlation between metallicity and HI column density for
DLAs. Further investigations are needed for the star formation mode at high
redshift environments.


  I reproduce a rather simple formal derivation of the Heaps' law from the
generalized Zipf's law, which I previously published in Russian.


  We have realized an integer quantum Hall system with superconducting contacts
by connecting graphene to niobium electrodes. Below their upper critical field
of 4 tesla, an integer quantum Hall effect coexists with superconductivity in
the leads, but with a plateau conductance that is larger than in the normal
state. We ascribe this enhanced quantum Hall plateau conductance to Andreev
processes at the graphene-superconductor interface leading to the formation of
so-called Andreev edge-states. The enhancement depends strongly on the
filling-factor, and is less pronounced on the first plateau, due to the special
nature of the zero energy Landau level in monolayer graphene.


  We present the full public release of all data from the Illustris simulation
project. Illustris is a suite of large volume, cosmological hydrodynamical
simulations run with the moving-mesh code Arepo and including a comprehensive
set of physical models critical for following the formation and evolution of
galaxies across cosmic time. Each simulates a volume of (106.5 Mpc)^3 and
self-consistently evolves five different types of resolution elements from a
starting redshift of z=127 to the present day, z=0. These components are: dark
matter particles, gas cells, passive gas tracers, stars and stellar wind
particles, and supermassive black holes. This data release includes the
snapshots at all 136 available redshifts, halo and subhalo catalogs at each
snapshot, and two distinct merger trees. Six primary realizations of the
Illustris volume are released, including the flagship Illustris-1 run. These
include three resolution levels with the fiducial "full" baryonic physics
model, and a dark matter only analog for each. In addition, we provide four
distinct, high time resolution, smaller volume "subboxes". The total data
volume is ~265 TB, including ~800 full volume snapshots and ~30,000 subbox
snapshots. We describe the released data products as well as tools we have
developed for their analysis. All data may be directly downloaded in its native
HDF5 format. Additionally, we release a comprehensive, web-based API which
allows programmatic access to search and data processing tasks. In both cases
we provide example scripts and a getting-started guide in several languages:
currently, IDL, Python, and Matlab. This paper addresses scientific issues
relevant for the interpretation of the simulations, serves as a pointer to
published and on-line documentation of the project, describes planned future
additional data releases, and discusses technical aspects of the release.