  Geometry of the fluid container plays a key role in the shape of acoustic
streaming patterns. Inadvertent vortices can be troublesome in some cases, but
if treated properly, the problem turns into a very useful parameter in acoustic
tweezing or micromixing applications. In this paper, the effects of sinusoidal
boundaries of a microchannel on acoustic streaming patterns are studied.
Results show that while top and bottom sinusoidal walls are vertically actuated
at the resonance frequency of basic hypothetical rectangular microchannel, some
repetitive acoustic streaming patterns are recognized in classifiable cases.
Such patterns can never be produced in rectangular geometry with flat
boundaries. Relations between geometrical parameters and emerging acoustic
streaming patterns lead us to propose formulas in order to predict more cases.
Such results and formulations were not trivial at a glance.


  Adversarial examples have been shown to be the severe threat to deep neural
networks (DNNs). One of the most effective adversarial defense methods is
adversarial training (AT) through minimizing the adversarial risk $R_{adv}$,
which encourages both the benign example $x$ and its adversarially perturbed
neighborhoods within the $\ell_{p}$-ball to be predicted as the ground-truth
label. In this work, we propose a novel defense method, the robust training
(RT), by jointly minimizing two separated risks ($R_{stand}$ and $R_{rob}$),
which is with respect to the benign example and its neighborhoods respectively.
The motivation is to explicitly and jointly enhance the accuracy and the
adversarial robustness. We prove that $R_{adv}$ is upper-bounded by $R_{stand}
+ R_{rob}$, which implies that RT has similar effect as AT. Intuitively,
minimizing the standard risk enforces the benign example to be correctly
predicted, and the robust risk minimization encourages the predictions of the
neighbor examples to be consistent with the prediction of the benign example.
Besides, since $R_{rob}$ is independent of the ground-truth label, RT is
naturally extended to the semi-supervised mode ($i.e.$, SRT), to further
enhance the adversarial robustness. Moreover, we extend the $\ell_{p}$-bounded
neighborhood to a general case, which covers different types of perturbations,
such as the pixel-wise ($i.e.$, $x + \delta$) or the spatial perturbation
($i.e.$, $ AX + b$). Extensive experiments on benchmark datasets not only
verify the superiority of the proposed SRT method to state-of-the-art methods
for defensing pixel-wise or spatial perturbations separately, but also
demonstrate its robustness to both perturbations simultaneously. The code for
reproducing main results is available at
\url{https://github.com/THUYimingLi/Semi-supervised_Robust_Training}.


  The Mitrinovi\'c-Cusa inequality states that for x\in(0,{\pi}/2) (cos
x)^{1/3}<((sin x)/x)<((2+cos x)/3) hold. In this paper, we prove that (cos
x)^{1/3}<(cos px)^{1/(3p^{2})}<((sin x)/x)<(cos qx)^{1/(3q^{2})}<((2+cos x)/3)
hold for x\in(0,{\pi}/2) if and only if p\in[p_{1},1) and q\in(0,1/\surd5],
where p_{1}=0.45346830977067.... And the function p\mapsto(cos px)^{1/(3p^{2})}
is decreasing on (0,1]. Our results greatly refine the Mitrinovi\'c-Cusa
inequality.


  Starting from Montgomery's conjecture, there has been a substantial interest
on the connections of random matrix theory and the theory of L-functions. In
particular, moments of characteristic polynomials of random matrices have been
considered in various works to estimate the asymptotics of moments of
L-function families. In this paper, we first consider joint moments of the
characteristic polynomial of a symplectic random matrix and its second
derivative. We obtain the asymptotics, along with a representation of the
leading order coefficient in terms of the solution of a Painleve equation. This
gives us the conjectural asymptotics of the corresponding joint moments over
families of Dirichlet L-functions. In doing so, we compute the asymptotics of a
certain additive Jacobi statistic, which could be of independent interest in
random matrix theory. Finally, we consider a slightly different type of joint
moment that is the analogue of an average considered over the unitary group in
various works before. We obtain the asymptotics and the leading order
coefficient explicitly.


  In this paper, we derive a simplified formula of electric dipole moments
(EDMs) of a fermion. In the Standard Model, it is well-known that non-trivial
cancellations between some rainbow-type diagrams induced by $W$ boson exchanges
occur in the calculation of the neutron EDM at the two-loop level due to the
gauge symmetry. The fermion self-energy and the vertex correction are related
through the Ward-Takahashi identity, and this relation causes the exact
cancellation of the EDM. We derive EDM formulas for a more general setup by
introducing the form factors for the fermion self-energy and the vertex
correction so that the derived formulas can be applicable to a larger class of
models. We conclude that the non-zero EDM contributions are induced from
rainbow-type diagrams with the chirality flipping effects for internal
fermions. We also discuss the other possible generalization of the EDM
calculation which is applicable to the other classes of models.


  Two models with $SU(3)_C\otimes SU(3)_L\otimes U(1)_N$ gauge symmetry are
considered. We show that the masslessness of the photon does not prevent the
neutrinos from acquiring Majorana masses. That is, there is no relation between
the VEVs of Higgs fields and the electromagnetic gauge invariance contrary to
what has been claimed recently.


  We perform direct numerical simulations (DNS) of an advected scalar field
which diffuses and reacts according to a nonlinear reaction law. The objective
is to study how the bulk burning rate of the reaction is affected by an imposed
flow. In particular, we are interested in comparing the numerical results with
recently predicted analytical upper and lower bounds. We focus on reaction
enhancement and quenching phenomena for two classes of imposed model flows with
different geometries: periodic shear flow and cellular flow. We are primarily
interested in the fast advection regime. We find that the bulk burning rate v
in a shear flow satisfies v ~ a*U+b where U is the typical flow velocity and a
is a constant depending on the relationship between the oscillation length
scale of the flow and laminar front thickness. For cellular flow, we obtain v ~
U^{1/4}. We also study flame extinction (quenching) for an ignition-type
reaction law and compactly supported initial data for the scalar field. We find
that in a shear flow the flame of the size W can be typically quenched by a
flow with amplitude U ~ alpha*W. The constant alpha depends on the geometry of
the flow and tends to infinity if the flow profile has a plateau larger than a
critical size. In a cellular flow, we find that the advection strength required
for quenching is U ~ W^4 if the cell size is smaller than a critical value.


  We formulate a version of Baum-Connes' conjecture for a discrete quantum
group, building on our earlier work (\cite{GK}). Given such a quantum group
$\cla$, we construct a directed family $\{\cle_F \}$ of $C^*$-algebras ($F$
varying over some suitable index set), borrowing the ideas of \cite{cuntz},
such that there is a natural action of $\cla$ on each $\cle_F$ satisfying the
assumptions of \cite{GK}, which makes it possible to define the "analytical
assembly map", say $\mu^{r,F}_i$, $i=0,1,$ as in \cite{GK}, from the
$\cla$-equivariant $K$-homolgy groups of $\cle_F$ to the $K$-theory groups of
the "reduced" dual $\hat{\cla_r}$ (c.f. \cite{GK} and the references therein
for more details). As a result, we can define the Baum-Connes' maps $\mu^r_i :
\stackrel{\rm lim}{\longrightarrow} KK_i^\cla(\cle_F,\IC) \raro
K_i(\hat{\cla_r}),$ and in the classical case, i.e. when $\cla$ is $C_0(G)$ for
a discrete group, the isomorphism of the above maps for $i=0,1$ is equivalent
to the Baum-Connes' conjecture. Furthermore, we verify its truth for an
arbitrary finite dimensional quantum group and obtain partial results for the
dual of $SU_q(2).$


  The following paper proposes a new target localization system design using an
architecture based on reconfigurable intelligent surfaces (RISs) and passive
radars (PRs) for integrated sensing and communications systems. The preamble of
the communication signal is exploited in order to perform target sensing tasks,
which involve detection and localization. The RIS in this case can aid the PR
in sensing targets that are otherwise not seen by the PR itself, due to the
many obstacles encountered within the propagation channel. Therefore, this work
proposes a localization algorithm tailored for the integrated sensing and
communications RIS-aided architecture, which is capable of uniquely positioning
targets within the scene. The algorithm is capable of detecting the number of
targets along with estimating the position of targets via angles and times of
arrival. Our simulation results demonstrate the performance of the localization
method in terms of different localization and detection metrics and for
increasing RIS sizes.


  The charge and spin diffusion equations taking into account spin-flip and
spin-transfer torque were numerically solved using a finite element method in
complex non-collinear geometry. This approach was used to study the
spin-dependent transport in giant magnetoresistance metallic pillars sandwiched
between extended electrodes as in magnetoresistive heads for hard disk drives.
The charge current crowding around the boundaries between the electrodes and
the pillar has a quite significant influence on the spin current.


  Community detection is the problem of identifying natural divisions in
networks. Efficient parallel algorithms for identifying such divisions is
critical in a number of applications, where the size of datasets have reached
significant scales. This technical report presents one of the most efficient
implementations of the Leiden algorithm, a high quality community detection
method. On a server equipped with dual 16-core Intel Xeon Gold 6226R
processors, our Leiden implementation, which we term as GVE-Leiden, outperforms
the original Leiden, igraph Leiden, NetworKit Leiden, and cuGraph Leiden
(running on NVIDIA A100 GPU) by 436x, 104x, 8.2x, and 3.0x respectively -
achieving a processing rate of 403M edges/s on a 3.8B edge graph. In addition,
GVE-Leiden improves performance at an average rate of 1.6x for every doubling
of threads.


  In a local Fermi liquid (LFL), we show that there is a line of weak first
order phase transitions between the ferromagnetic and paramagnetic phases due
to purely quantum fluctuations. We predict that an instability towards
superconductivity is only possible in the ferromagnetic state. At T=0 we find a
point on the phase diagram where all three phases meet and we call this a
quantum triple point (QTP). A simple application of the Gibbs phase rule shows
that only these three phases can meet at the QTP. This provides a natural
explanation of the absence of superconductivity at this point coming from the
paramagnetic side of the phase diagram, as observed in the recently discovered
ferromagnetic superconductor, $UGe_{2}$.


  In this paper, we study phase diagrams of the extended Bose-Hubbard model
(EBHM) in one dimension by means of the quantum Monte-Carlo (QMC) simulation
using the stochastic-series expansion (SSE).In the EBHM, there exists a
nearest-neighbor repulsion as well as the on-site repulsion. In the SSE-QMC
simulation, the highest particle number at each site, $n_c$, is also a
controllable parameter, and we found that the phase diagrams depend on the
value of $n_c$. It is shown that in addition to the Mott insulator, superfluid,
density wave, the phase so-called Haldane insulator and supersolid appear in
the phase diagrams, and their locations in the phase diagrams are clarified.


  Due to sphaleron processes in the high-temperature symmetric phase of the
standard model the cosmological baryon asymmetry is related to neutrino
properties. For hierarchical neutrino masses, with $B-L$ broken at the
unification scale $\Lambda_{GUT}\sim 10^{16} $GeV, the observed baryon
asymmetry $n_B/s \sim 10^{-10}$ can be naturally explained by the decay of
heavy Majorana neutrinos. We illustrate this mechanism with two models of
neutrino masses, consistent with the solar and atmospheric neutrino anomalies,
which are based on the two symmetry groups $SU(5)\times U(1)_F$ and
$SU(3)_c\times SU(3)_L\times SU(3)_R\times U(1)_F$.
  We also review related cosmological bounds on Majorana neutrino masses and
the use of Boltzmann equations.


  A rigid-plastic Cosserat model has been used to study dense, fully developed
flow of granular materials through a vertical channel. Frictional models based
on the classical continuum do not predict the occurrence of shear layers, at
variance with experimental observations. This feature has been attributed to
the absence of a material length scale in their constitutive equations. The
present model incorporates such a material length scale by treating the
granular material as a Cosserat continuum. Thus localised couple stresses exist
and the stress tensor is asymmetric. The velocity profiles predicted by the
model are in close agreement with available experimental data. The predicted
dependence of the shear layer thickness on the width of the channel is in
reasonable agreement with data. In the limit of the ratio of the particle
diameter to the half-width of the channel being small, the model predicts that
the shear layer thickness scaled by the particle diameter grows.


  From a theoretical point of view, we propose an experimental method to
determine the pairing symmetry of iron pnictides. We focus on two kinds of
pairing symmetries, $s_{+-}$ and $s_{++}$, which are strong candidates for the
pairing symmetry of iron pnictides. For each of these two symmetries, we
calculate both the density and spin response functions by using the two-band
BCS model within the one-loop approximation. As a result, a clear difference is
found between the $s_{+-}$- and $s_{++}$-wave states in the temperature
dependence of the response functions at nesting vector $\bf{Q}$, which connects
the hole and electron Fermi surfaces. We point out that this difference comes
from the coherence effect in the two-band superconductor. We suggest that the
pairing symmetry could be clarified by observing the temperature dependence of
both the density and spin structure factors at the nesting vector $\bf{Q}$ in
neutron scattering measurements.


  We address the question of how well the density profile of galaxy clusters
can be determined by combining strong lensing and velocity dispersion data. We
use cosmological dark matter simulations of clusters to test the reliability of
the method, producing mock catalogues of tangential and radial gravitational
arcs and simulating the radial velocity dispersion profile of the cluster
brightest central galaxy. The density profiles of the simulated clusters
closely follow the NFW form, but we find that the recovered values of the inner
slope are systematically underestimated, by about 0.4 in the mean, if the lens
is assumed to be axially symmetric. However, if the ellipticity and orientation
of the iso-contours of the cluster lensing potential are taken into account,
then the inner slopes can be recovered quite accurately for a significant
subset of the clusters whose central surface density profiles appear the most
regular. These have lensing potentials with ellipticities in the range
0.15-0.4. Further simulations projecting one cluster along many random
lines-of-sight show that, even for lower ellipticities, the central slopes are
underestimated by $\sim 10-35%$. These simulations closely mimic past
observations (see e.g. Sand et al., 2004), suggesting that existing estimates
of the central slopes may be biased towards low values. For the remaining
clusters, where the lensing potential is strongly perturbed by active merging
or by substructure, the correct determination of the inner slope requires a
more accurate model for the lens. When the halo profile is modelled by a
generalised NFW profile, we find that the inferred scale radius and
characteristic density, unlike the inner slope, are generally poorly
constrained, since there is a strong degeneracy between these two parameters.


  Label estimation is an important component in an unsupervised person
re-identification (re-ID) system. This paper focuses on cross-camera label
estimation, which can be subsequently used in feature learning to learn robust
re-ID models. Specifically, we propose to construct a graph for samples in each
camera, and then graph matching scheme is introduced for cross-camera labeling
association. While labels directly output from existing graph matching methods
may be noisy and inaccurate due to significant cross-camera variations, this
paper proposes a dynamic graph matching (DGM) method. DGM iteratively updates
the image graph and the label estimation process by learning a better feature
space with intermediate estimated labels. DGM is advantageous in two aspects:
1) the accuracy of estimated labels is improved significantly with the
iterations; 2) DGM is robust to noisy initial training data. Extensive
experiments conducted on three benchmarks including the large-scale MARS
dataset show that DGM yields competitive performance to fully supervised
baselines, and outperforms competing unsupervised learning methods.


  We have used the diffusion quantum Monte Carlo method to calculate the energy
band of the two-dimensional homogeneous electron gas (HEG), and hence we have
obtained the quasiparticle effective mass and the occupied bandwidth. We find
that the effective mass in the paramagnetic HEG increases significantly when
the density is lowered, whereas it decreases in the fully ferromagnetic HEG.
Our calculations therefore support the conclusions of recent experimental
studies [Y.-W. Tan et al., Phys. Rev. Lett. 94, 016405 (2005); M. Padmanabhan
et al., Phys. Rev. Lett. 101, 026402 (2008); T. Gokmen et al., Phys. Rev. B 79,
195311 (2009)]. We compare our calculated effective masses with other
theoretical results and experimental measurements in the literature.


  From tiny pacemaker chips to aircraft collision avoidance systems, the
state-of-the-art Cyber-Physical Systems (CPS) have increasingly started to rely
on Deep Neural Networks (DNNs). However, as concluded in various studies, DNNs
are highly susceptible to security threats, including adversarial attacks. In
this paper, we first discuss different vulnerabilities that can be exploited
for generating security attacks for neural network-based systems. We then
provide an overview of existing adversarial and fault-injection-based attacks
on DNNs. We also present a brief analysis to highlight different challenges in
the practical implementation of adversarial attacks. Finally, we also discuss
various prospective ways to develop robust DNN-based systems that are resilient
to adversarial and fault-injection attacks.


  In this paper, we consider a spherically curved symmetric spacetime to exact
solving the orbit equation of a massive particle by using Jacobi's elliptic
functions. Generally, the solution of the orbit equation provides the
relativistic effects on the massive particle, absents in Newtonian mechanics.
Besides, we investigate the additional physical information introduced by the
exact solution to the orbit equation that is not visible in the approximate
solutions traditionally presented in literature. Here, we exactly solve the
problem by the use an analytical methodology step by step in order to provide
detailed solutions as well as demonstrate with mathematical rigour the geodesic
solution in terms of Jacobi's elliptic functions. We find oscillatory movements
of the orbit of the massive particle at the expected regimes without to
consider any heuristic argument. Bound regions to the solution of the equation
of motion is presented, finding the aspect of the geodesic when the massive
particle is trapped in the gravitational field of the source.


  This note investigates the controllability of two unstable second-order
systems that are coupled through a common input. These dynamics occur for
different types of inverted-pendulum systems. Controllability is quantified by
the volume of the state-space that can be reached with unit energy, provided
that the system starts and ends at the origin. It is shown that controllability
is maximized when the ratio between the time constants amounts to the silver
ratio.


  We provide several applications of Optimistic Mirror Descent, an online
learning algorithm based on the idea of predictable sequences. First, we
recover the Mirror Prox algorithm for offline optimization, prove an extension
to Holder-smooth functions, and apply the results to saddle-point type
problems. Next, we prove that a version of Optimistic Mirror Descent (which has
a close relation to the Exponential Weights algorithm) can be used by two
strongly-uncoupled players in a finite zero-sum matrix game to converge to the
minimax equilibrium at the rate of O((log T)/T). This addresses a question of
Daskalakis et al 2011. Further, we consider a partial information version of
the problem. We then apply the results to convex programming and exhibit a
simple algorithm for the approximate Max Flow problem.


  To recognize textures many methods have been developed along the years.
However, texture datasets may be hard to be classified due to artefacts such as
a variety of scale, illumination and noise. This paper proposes the application
of binary distance transform on the original dataset to add information to
texture representation and consequently improve recognition. Texture images,
usually in grayscale, suffers a binarization prior to distance transform and
one of the resulted images are combined with original texture to improve the
amount of information. Four datasets are used to evaluate our approach. For
Outex dataset, for instance, the proposal outperforms all rates, improvements
of an up to 10\%, compared to traditional approach where descriptors are
applied on the original dataset, showing the importance of this approach.


  We present a modern ephemeris and modern light curve of the first-discovered
Cepheid variable in M31, Edwin Hubble's M31-V1. Observers of the American
Association of Variable Star Observers undertook these observations during the
latter half of 2010. The observations were in support of an outreach program by
the Space Telescope Science Institute's Hubble Heritage project, but the
resulting data are the first concentrated observations of M31-V1 made in modern
times. AAVSO observers obtained 214 V-band, Rc-band, and unfiltered
observations from which a current ephemeris was derived. The ephemeris derived
from these observations is JD(Max) = 2455430.5(+/-0.5) + 31.4 (+/-0.1) E. The
period derived from the 2010 data are in agreement with the historic values of
the period, but the single season of data precludes a more precise
determination of the period or measurement of the period change using these
data alone. However, using an ephemeris based upon the period derived by Baade
and Swope we are able to fit all of the observed data acceptably well.
Continued observations in the modern era will be very valuable in linking these
modern data with data from the 1920s-30s and 1950s, and will enable us to
measure period change in this historic Cepheid. In particular, we strongly
encourage intensive observations of this star around predicted times of maximum
to constrain the date of maximum to better than 0.5 days.


  The distribution of household income is a central concern of modern economic
policy due to its strong influence on life quality. Yet, non-expert audiences
are unaware of the relationship between these two factors. To effectively
communicate the effect of income inequality on the quality of life and among
the strata, we have designed a novel technique for visualizing income
distribution and inequality over time by using the U.S. household income
microdata from the Current Population Survey. The result is a striking dynamic
animation of income distribution over time, drawing public attention and
further investigating economic inequality. Detailed implementation of this
project is available at https://github.com/sangttruong/incomevis.


  We propose a new class of semiparametric regression models of mean residual
life for censored outcome data. The models, which enable us to estimate the
expected remaining survival time and generalize commonly used mean residual
life models, also conduct covariate dimension reduction. Using the geometric
approaches in semiparametrics literature and the martingale properties with
survival data, we propose a flexible inference procedure that relaxes the
parametric assumptions on the dependence of mean residual life on covariates
and how long a patient has lived. We show that the estimators for the covariate
effects are root-$n$ consistent, asymptotically normal, and semiparametrically
efficient. With the unspecified mean residual life function, we provide a
nonparametric estimator for predicting the residual life of a given subject,
and establish the root-$n$ consistency and asymptotic normality for this
estimator. Numerical experiments are conducted to illustrate the feasibility of
the proposed estimators. We apply the method to analyze a national kidney
transplantation dataset to further demonstrate the utility of the work.


  We present Chandra X-ray observations of 14 radio-loud quasars at redshifts
$3 < z < 4$, selected from a well-defined sample. All quasars are detected in
the 0.5-7.0 keV energy band, and resolved X-ray features are detected in five
of the objects at distances of 1-12" from the quasar core. The X-ray features
are spatially coincident with known radio features for four of the five
quasars. This indicates that these systems contain X-ray jets. X-ray fluxes and
luminosities are measured, and jet-to-core X-ray flux ratios are estimated. The
flux ratios are consistent with those observed for nearby jet systems,
suggesting that the observed X-ray emission mechanism is independent of
redshift. For quasars with undetected jets, an upper limit on the average X-ray
jet intensity is estimated using a stacked image analysis. Emission spectra of
the quasar cores are extracted and modeled to obtain best-fit photon indices,
and an Fe K emission line is detected from one quasar in our sample. We compare
X-ray spectral properties with optical and radio emission in the context of
both our sample and other quasar surveys.


  Given a group $G$ acting geometrically on a systolic complex $X$ and a
hyperbolic isometry $h \in G$, we study the associated action of $h$ on the
systolic boundary $\partial X$. We show that $h$ has a canonical pair of fixed
points on the boundary and that it acts trivially on the boundary if and only
if it is virtually central. The key tool that we use to study the action of $h$
on $\partial X$ is the notion of a $K$-displacement set of $h$, which
generalises the classical minimal displacement set of $h$. We also prove that
systolic complexes equipped with a geometric action of a group are almost
extendable.


  We introduce an harmonic analysis for iterated function systems (IFS) (X, mu)
which is based on a Markov process on certain paths. The probabilities are
determined by a weight function W on X. From W we define a transition operator
R_W acting on functions on X, and a corresponding class of R_W-harmonic
functions. The properties of these functions determine the spectral theory of
L^2(mu). For affine IFSs we establish orthogonal bases in L^2(mu). These bases
are generated by paths with infinite repetition of finite words. We use this in
the last section to analyze tiles in R^d.


  In this paper, we propose a novel deep architecture tailored for 3D point
cloud applications, named as SPE-Net. The embedded ``Selective Position
Encoding (SPE)'' procedure relies on an attention mechanism that can
effectively attend to the underlying rotation condition of the input. Such
encoded rotation condition then determines which part of the network parameters
to be focused on, and is shown to efficiently help reduce the degree of freedom
of the optimization during training. This mechanism henceforth can better
leverage the rotation augmentations through reduced training difficulties,
making SPE-Net robust against rotated data both during training and testing.
The new findings in our paper also urge us to rethink the relationship between
the extracted rotation information and the actual test accuracy. Intriguingly,
we reveal evidences that by locally encoding the rotation information through
SPE-Net, the rotation-invariant features are still of critical importance in
benefiting the test samples without any actual global rotation. We empirically
demonstrate the merits of the SPE-Net and the associated hypothesis on four
benchmarks, showing evident improvements on both rotated and unrotated test
data over SOTA methods. Source code is available at
https://github.com/ZhaofanQiu/SPE-Net.


  With this report we provide users of an easy manual to facilitate the proper
download and use of a sophisticated, high precision, few-body code originally
developed by S. Mikkola, and later largely improved and implemented to treat a
variety of cases. The code download can be done via the link
https://drive.google.com/file/d/16FkVVR4Tk8eKhKMju2vQ9rlWI4Mpv01W/view
  The use of the code is free upon proper citation. The work is in progress and
users are invited to help the authors to improve both the code and the user
handbook.


  Some differences between theoretical, numerical and observational
determinations of spectral slopes of solar wind turbulence are interpreted in
the thermodynamical sense. Confirmations of turbulent Kolmogorov slopes in
solar wind magnetic turbulence and magnetohydrodynamic simulations exhibit tiny
differences. These are used to infer about entropy generation in the turbulent
cascade and to infer about the anomalous turbulent collision frequency in the
dissipative range as well as the average energy input in solar wind turbulence.
Anomalous turbulent collision frequencies are obtained of the order of v < 200
Hz. The corresponding stationary solar wind magnetic energy input into magnetic
turbulence in the Kolmogorov inertial range is obtained to be of the order of
50 eV/s. Its thermal fate is discussed.


  The fully two-dimensional Peierls barrier map of screw dislocations in BCC
iron has been calculated using the first principles method to identify the
migration path of a dislocation core. An efficient method to correct the effect
of the finite size cell used in the first principles method on the energy of a
lattice defect was devised to determine the accurate barrier profile. We find
that the migration path is close to a straight line which is confined in a
$\{110\}$ plane and the Peierls barrier profile is single-humped. This result
clarifies a reason that the existing empirical potentials of BCC iron fail to
predict the correct mobility path. A line tension model, incorporating these
first principles calculation results, is used to predict the kink activation
energy to be 0.73 eV in agreement with experiment.


  Due to several issues arising in the rapidly-expanding Halal industry, among
them the production of non-genuine or contaminated products and meats, there is
a need to develop effective solutions for ensuring authenticity and quality.
This paper proposes the specification of a formalized supply chain framework
for the production and monitoring of food and products. The latter enforces
high-level quality of automated monitoring as well as shorter production cycles
through enhanced coordination between the actors and organizations involved.
Our proposal is guided by business process support to ensure quality and
efficiency of product development and delivery. It moreover meets the
requirements of industrial standards by adopting the Capability Maturity Model
Integration highest process maturity level through establishing quantitative
process-improvement objectives, proposing the integrated support of engineering
processes, enforcing synchronization and coordination, drastic monitoring and
exception handling. We then delve into some of the important technologies from
the implementation point-of-view and align it with the formalized Halal
framework. An Information Technology support instantiation is proposed leading
to a use case scenario with technology identification.


  The stability under small time perturbations of the dilatonic black hole
solution near the determinant curvature singularity is proved. This fact gives
the additional arguments that the investigated topological configuration can
realise in nature. In the frames of this model primordial black hole remnants
are examined as time stable objects, which can form an significant part of a
dark matter in the Universe.


  It is well known that the spectral gap of the down-up walk over an
$n$-partite simplicial complex (also known as Glauber dynamics) cannot be
better than $O(1/n)$ due to natural obstructions such as coboundaries. We study
an alternative random walk over partite simplicial complexes known as the
sequential sweep or the systematic scan Glauber dynamics: Whereas the down-up
walk at each step selects a random coordinate and updates it based on the
remaining coordinates, the sequential sweep goes through each of the
coordinates one by one in a deterministic order and applies the same update
operation. It is natural, thus, to compare $n$-steps of the down-up walk with a
single step of the sequential sweep. Interestingly, while the spectral gap of
the $n$-th power of the down-up walk is still bounded from above by a constant,
under a strong enough local spectral assumption (in the sense of Gur,
Lifschitz, Liu, STOC 2022) we can show that the spectral gap of this walk can
be arbitrarily close to 1. We also study other isoperimetric inequalities for
these walks, and show that under the assumptions of local entropy contraction
(related to the considerations of Gur, Lifschitz, Liu), these walks satisfy an
entropy contraction inequality.


  We present the first large-scale effort of creating composite spectra of
high-redshift type Ia supernovae (SNe Ia) and comparing them to low-redshift
counterparts. Through the ESSENCE project, we have obtained 107 spectra of 88
high-redshift SNe Ia with excellent light-curve information. In addition, we
have obtained 397 spectra of low-redshift SNe through a multiple-decade effort
at Lick and Keck Observatories, and we have used 45 UV spectra obtained by
HST/IUE. The low-redshift spectra act as a control sample when comparing to the
ESSENCE spectra. In all instances, the ESSENCE and Lick composite spectra
appear very similar. The addition of galaxy light to the Lick composite spectra
allows a nearly perfect match of the overall spectral-energy distribution with
the ESSENCE composite spectra, indicating that the high-redshift SNe are more
contaminated with host-galaxy light than their low-redshift counterparts. This
is caused by observing objects at all redshifts with the same slit width, which
corresponds to different projected distances. After correcting for the
galaxy-light contamination, subtle differences in the spectra remain. We have
estimated the systematic errors when using current spectral templates for
K-corrections to be ~0.02 mag. The variance in the composite spectra give an
estimate of the intrinsic variance in low-redshift maximum-light SN spectra of
~3% in the optical and growing toward the UV. The difference between the
maximum light low and high-redshift spectra constrain SN evolution between our
samples to be < 10% in the rest-frame optical.


  We calculate the interplanetary magnetic field path lengths traveled by
electrons in solar electron events detected by the WIND 3DP instrument from
$1994$ to $2016$. The velocity dispersion analysis method is applied for
electrons at energies of $\sim$ $27$ keV to $310$ keV. Previous velocity
dispersion analyses employ the onset times, which are often affected by
instrumental effects and the pre-existing background flux, leading to large
uncertainties. We propose a new method here. Instead of using the peak or onset
time, we apply the velocity dispersion analysis to the times that correspond to
the rising phase of the fluxes that are a fraction, $\eta$, of the peak flux.
We perform statistical analysis on selected events whose calculated path
lengths have uncertainties smaller than $0.1$ AU. The mean and standard
deviation, ($\mu$, $\sigma$), of the calculated path lengths corresponding to
$\eta=$ $3/4$, $1/2$, and $1/3$ of the peak flux is ($1.17$ AU, $0.17$ AU),
($1.11$ AU, $0.14$ AU), and ($1.06$ AU, $0.15$ AU). The distribution of the
calculated path lengths is also well fitted by a Gaussian distribution for the
$\eta=3/4$ and $1/3$ cases. These results suggest that in these electron events
the interplanetary magnetic field topology is close to the nominal Parker
spiral with little field line meandering. Our results have important
implications for particles' perpendicular diffusion.


  We demonstrate that both Wigner's form of Bell's inequalities as well as a
form of the second law of thermodynamics, as manifest in Carath\'{e}odory's
principle, can be derived from the same simple experimental and statistical
mechanical assumptions combined with the trivial behavior of integers. This
suggests that Bell's theorem is merely a well-disguised statement of the second
law. It also suggests that entanglement is necessary for quantum theory to be
in full accord with the second law and thus builds on the results of Wiesniak,
Vedral, and Brukner \cite{Marcin-Wiesniak:2008fv} who showed it was necessary
for consistency with the third law.


  In this paper, we study the construction of low-degree robust finite element
schemes for planar linear elasticity on general triangulations.
  Firstly, we present a low-degree nonconforming Helling-Reissner finite
element scheme. For the stress tensor space, the piecewise polynomial shape
function space is $$ {\rm span}\left\{\left(\begin{array}{cc}1&0\\ 0 &
0\end{array}\right),\left(\begin{array}{cc}0&1\\ 1 &
0\end{array}\right),\left(\begin{array}{cc}0&0\\ 0 &
1\end{array}\right),\left(\begin{array}{cc}0&x\\ x &
0\end{array}\right),\left(\begin{array}{cc}0&y\\ y &
0\end{array}\right),\left(\begin{array}{cc}0&x^2-y^2\\ x^2-y^2 &
0\end{array}\right)\right\}, $$ the dimension of the total space is
asymptotically 8 times of the number of vertices, and the supports of the basis
functions are each a patch of an edge. The piecewise rigid body space is used
for the displacement. Robust error estimations in $\mathbb{L}^2$ and broken
$\mathbf{H}({\rm div})$ norms are presented.
  Secondly, we investigate the theoretical construction of schemes with
lowest-degree polynomial shape function spaces. Specifically, a
Hellinger-Reissner finite element scheme is constructed, with the local shape
function space for the stress tensor being 5-dimensional which is of the lowest
degree for the local approximation of $\mathbf{H}({\rm div};\mathbb{S})$, and
the space for the displacement is piecewise constants. Robust error estimations
in $\mathbb{L}^2$ and broken $\mathbf{H}({\rm div})$ norms are presented for
regular solutions and data.


  We explain how the axioms of Conformal Field Theory are used to make
predictions about critical exponents of continuous phase transitions in three
dimensions, via a procedure called the conformal bootstrap. The method assumes
conformal invariance of correlation functions, and imposes some relations
between correlation functions of different orders. Numerical analysis shows
that these conditions are incompatible unless the critical exponents take
particular values, or more precisely that they must belong to a small island in
the parameter space.


  This announcement considers the following problem. We produce a bounded mean
oscillation theorem for small distorted diffeomorphisms from $\mathbb R^D$ to
$\mathbb R^D$. A revision of this announcement is in the memoir preprint:
arXiv:2103.09748, [1], submitted for consideration for publication.


  One field of application of Big Data and Artificial Intelligence that is
receiving increasing attention is the biomedical domain. The huge volume of
data that is customary generated by hospitals and pharmaceutical companies all
over the world could potentially enable a plethora of new applications. Yet,
due to the complexity of such data, this comes at a high cost. We here review
the activities of the research group composed by people of the Universidad
Polit\'ecnica de Madrid and the Hospital Universitario Puerta de Hierro de
Majadahonda, Spain; discuss their activities within two European projects,
IASIS and BigMedilytics; and present some initial results.


  We study the nonlinear dynamics of the splitting of a doubly quantized vortex
in a trapped condensate. The dynamics is studied in detail by solving the
Gross-Pitaevskii equation. The main dynamical features are explained in terms
of a nonlinear three-level system. We find an analytical solution for the
characteristics of the dynamics. It is concluded that the time scale for the
splitting is mainly determined by the instability of the linearized system, and
nonlinear effects contribute logarithmically.


  We report a neutron scattering study on the tetragonal compound
Sr_2Cu_3O_4Cl_2, which has two-dimensional (2D) interpenetrating Cu_I and
Cu_{II} subsystems, each forming a S=1/2 square lattice quantum Heisenberg
antiferromagnet (SLQHA). The mean-field ground state is degenerate, since the
inter-subsystem interactions are geometrically frustrated. Magnetic neutron
scattering experiments show that quantum fluctuations lift the degeneracy and
cause a 2D Ising ordering of the Cu_{II} subsystem. Due to quantum fluctuations
a dramatic increase of the Cu_I out-of-plane spin-wave gap is also observed.
The temperature dependence and the dispersion of the spin-wave energy are
quantitatively explained by spin-wave calculations which include quantum
fluctuations explicitly. The values for the nearest-neighbor superexchange
interactions between the Cu_I and Cu_{II} ions and between the Cu_{II} ions are
determined experimentally to be J_{I-II} = -10(2)meV and J_{II}= 10.5(5)meV,
respectively. Due to its small exchange interaction, J_{II}, the 2D dispersion
of the Cu_{II} SLQHA can be measured over the whole Brillouin zone with thermal
neutrons, and a novel dispersion at the zone boundary, predicted by theory, is
confirmed. The instantaneous magnetic correlation length of the Cu_{II} SLQHA
is obtained up to a very high temperature, T/J_{II}\approx 0.75. This result is
compared with several theoretical predictions as well as recent experiments on
the S=1/2 SLQHA.


  First-ascent red giants with strong and very strong Li lines have just been
discovered in globular clusters. Using the stellar internal prompt 7Li
enrichment - mass loss scenario, we explore the possibility of 7Li enrichment
in the interstellar matter of the globular cluster M3 produced by these Li-rich
giants. We found that enrichment as large as 70% or more compared to the
initial 7Li content of M3 can be obtained during the entire life of this
cluster. However, due to the several crossings of M3 into the Galactic plane,
the new 7Li will be very probably removed by ram pressure into the disk.
Globular clusters appear then as possible new sources of 7Li in the galactic
disk. It is also suggested that the known Na/Al variations in stars of globular
clusters could be somehow related to the 7Li variations and that the cool
bottom mixing mechanism acting in the case of 7Li could also play a role in the
case of Na and Al surface enrichments.


  Most of the DNA that composes a complex organism is non-coding and defined as
junk. Even the coding part is composed of genes that affect the phenotype
differently. Therefore, a random mutation has an effect on the specimen fitness
that strongly depends on the DNA region where it occurs. Such heterogeneous
composition should be linked to the evolutionary process. However, the way is
still unknown.
  Here, we study a minimal model for the evolution of an ecosystem where two
antagonist species struggle for survival on a lattice. Each specimen possesses
a toy genome, encoding for its phenotype. The gene pool of populations changes
in time due to the effect of random mutations on genes (entropic force) and of
interactions with the environment and between individuals (natural selection).
  We prove that the relevance of each gene in the manifestation of the
phenotype is a key feature for evolution. In the presence of a uniform gene
relevance, a mutational meltdown is observed. Natural selection acts quenching
the ecosystem in a non-equilibriumstate that slowly drifts, decreasing the
fitness and leading to the extinction of the species. Conversely, if a specimen
is provided with a heterogeneous gene relevance, natural selection wins against
entropic forces, and the species evolves increasing its fitness. We finally
show that heterogeneity together with spatial correlations is responsible for
spontaneous sympatric speciation.


  Non-convex gradient descent is a common approach for estimating a low-rank
$n\times n$ ground truth matrix from noisy measurements, because it has
per-iteration costs as low as $O(n)$ time, and is in theory capable of
converging to a minimax optimal estimate. However, the practitioner is often
constrained to just tens to hundreds of iterations, and the slow and/or
inconsistent convergence of non-convex gradient descent can prevent a
high-quality estimate from being obtained. Recently, the technique of
preconditioning was shown to be highly effective at accelerating the local
convergence of non-convex gradient descent when the measurements are noiseless.
In this paper, we describe how preconditioning should be done for noisy
measurements to accelerate local convergence to minimax optimality. For the
symmetric matrix sensing problem, our proposed preconditioned method is
guaranteed to locally converge to minimax error at a linear rate that is immune
to ill-conditioning and/or over-parameterization. Using our proposed
preconditioned method, we perform a 60 megapixel medical image denoising task,
and observe significantly reduced noise levels compared to previous approaches.


  The linear finite irreducible representations of the algebra of the 1D
$N$-Extended Supersymmetric Quantum Mechanics are discussed in terms of their
"connectivity" (a symbol encoding information on the graphs associated to the
irreps). The classification of the irreducible representations with the same
fields content and different connectivity is presented up to $N\leq 8$.


  We study Cox rings of crepant resolutions of quotient singularities
$\mathbb{C}^3/G$ where $G$ is a finite subgroup of $SL(3,\mathbb{C})$. We use
them to obtain information on the geometric structure of these resolutions,
number of different resolutions and relations between them. In particular, we
treat explicitly several examples where $G$ contains elements of age 2.


  These notes present a brief introduction to Hot Big Bang cosmology and Cosmic
Inflation, together with a selection of some recent attempts to embed inflation
into string theory. They provide a partial description of lectures presented in
courses at Dubrovnik in August 2006, at CERN in January 2007 and at Cargese in
August 2007. They are aimed at graduate students with a working knowledge of
quantum field theory, but who are unfamiliar with the details of cosmology or
of string theory.


  Scientific datasets and analysis pipelines are increasingly being shared
publicly in the interest of open science. However, mechanisms are lacking to
reliably identify which pipelines and datasets can appropriately be used
together. Given the increasing number of high-quality public datasets and
pipelines, this lack of clear compatibility threatens the findability and
reusability of these resources. We investigate the feasibility of a
collaborative filtering system to recommend pipelines and datasets based on
provenance records from previous executions. We evaluate our system using
datasets and pipelines extracted from the Canadian Open Neuroscience Platform,
a national initiative for open neuroscience. The recommendations provided by
our system (AUC$=0.83$) are significantly better than chance and outperform
recommendations made by domain experts using their previous knowledge as well
as pipeline and dataset descriptions (AUC$=0.63$). In particular, domain
experts often neglect low-level technical aspects of a pipeline-dataset
interaction, such as the level of pre-processing, which are captured by a
provenance-based system. We conclude that provenance-based pipeline and dataset
recommenders are feasible and beneficial to the sharing and usage of
open-science resources. Future work will focus on the collection of more
comprehensive provenance traces, and on deploying the system in production.


  One of the biggest problems we can encounter while dealing with the
limb-darkening coefficients for stellar atmospheric models with spherical
symmetry is the difficulty of adjusting both the limb and the central parts
simultaneously. In particular, the regions near the drop-offs are not well
reproduced for most models, depending on Teff, log g, or wavelength. Even if
the law with four terms is used, these disagreements still persist. Here we
introduce a new method that considerably improves the description of both the
limb and the central parts and that will allow users to test models of stellar
atmospheres with spherical symmetry more accurately in environments such as
exoplanetary transits, eclipsing binaries, etc.
  The method introduced here is simple. Instead of considering all the $\mu $
points in the adjustment, as is traditional, we consider only the points until
the drop-off ($\mu_{cri}$) of each model. From this point, we impose a
condition ${I(\mu)}/{I (1)} = 0$. All calculations were performed by adopting
the least-squares method.
  The resulting coefficients using this new method reproduce the intensity
distribution of the PHOENIX spherical models (COND and DRIFT) quite well for
the photometric systems of the space missions {{\sc TESS}}, {{\sc KEPLER}},
{{\sc COROT}}, and {{\sc MOST}}. The calculations cover the following ranges of
local gravity and effective temperatures:
  2.5 $\leq$ log g $\leq$ 6.0 and 1500 K $\leq$ T$_{\rm eff}$
  $\leq$ 12000 K. The new spherical coefficients can easily be adapted to the
most commonly used light curve synthesis codes.


  The Milky Way (MW) dwarf system presents two exceptional features, namely it
forms a thick plane called the Vast Polar Structure (VPOS), and the two biggest
dwarves, the Magellanic Clouds (MCs), are irregular galaxies that are almost
never seen at such a proximity from a luminous, L* galaxy. Investigating from
our modelling of M31 as a result of a former gas-rich major merger, we find
that one of the expected tidal tail produced during the event may have reached
the MW. Such a coincidence may appear quite exceptional, but the MW indeed lies
within the small volume delineated by the tidal tail at the present epoch. In
our scenario, most of the MW dwarves, including the MCs, may have been formed
within a tidal tail formed during the former merger in the Local Group. It
leads to a fair reproduction of the VPOS as well as to a simple explanation of
the MCs proximity to the MW, i.e. accounting for both exceptional features of
the MW dwarf distributions. However this scenario predicts dark-matter free MW
dwarves, which is in apparent contradiction with their intrinsically large
velocity dispersions. To be established or discarded, this requires to further
investigate their detailed interactions with the MW potential.


  We investigate the superfluid behavior of a Bose-Einstein condensate of
$^6$Li molecules. In the experiment by Weimer et al., Phys. Rev. Lett. 114,
095301 (2015) a condensate is stirred by a weak, red-detuned laser beam along a
circular path around the trap center. The rate of induced heating increases
steeply above a velocity $v_c$, which we define as the critical velocity. Below
this velocity, the moving beam creates almost no heating. In this paper, we
demonstrate a quantitative understanding of the critical velocity. Using both
numerical and analytical methods, we identify the non-zero temperature, the
circular motion of the stirrer, and the density profile of the cloud as key
factors influencing the magnitude of $v_c$. A direct comparison to the
experimental data shows excellent agreement.


  Based on magnitudes and Petrosian radii from the Sloan Digital Sky Survey
(SDSS, data release 7) at low redhift (z <0.2), we developed a test of
galaxy-size evolution. For this first quantitative size analysis using SDSS
data, several possible sources of systematic errors had to be considered. The
Malmquist bias is excluded by volume-limited samples. A correction for seeing
has been developed and applied. We compare different methods to perform the
K-correction, and avoid selection effects due to different filters. It is found
that apparent average galaxy size slightly decreases with redshift z,
corresponding to a growth in time. The effect is smaller for a lower H0, and at
the same time less pronounced at higher redshifts, but persists in both cases.
Although there is no systematic variation with galaxy luminosity, we took into
account the recently discovered luminosity evolution with redshift. Assuming
this effect of unknown origin to be real, we find a slight increase of galaxy
size with z. The relative change of average size with z usually amounts to less
than one half of the respective increase of wavelengths due to the cosmological
redshift, making a cosmological interpretation difficult. While the effect
shows clear statistical significance, unknown systematics cannot be excluded.
In any case, the enigmatic observations of size and luminosity evolution need
to be analysed together. To facilitate further investigations, a complete
Mathematica code and instructions for data download are provided.


  The fast reconstruction of charged particle tracks with high efficiency and
track quality is an essential part of the online data selection for the ATLAS
experiment at the High-Luminosity LHC. Dedicated custom designed hardware
boards and software simulations have been developed to assess the feasibility
of a Hardware Tracking Trigger (HTT) system. The Pattern Recognition Mezzanine
(PRM), as part of the HTT system, has been designed to recognize track
candidates in silicon detectors with Associative Memory ASICs and to select and
reconstruct tracks using linearized algorithms implemented in an Intel Stratix
10 MX FPGA. The highly parallelized FPGA design makes extensive use of the
integrated High-Bandwidth-Memory. In this paper, the FPGA design for the PRM
board is presented. Its functionalities have been verified in both simulations
and hardware tests on an Intel Stratix 10 MX development kit.


  The SCUBA-2 Ultra Deep Imaging EAO Survey (STUDIES) is a three-year JCMT
Large Program aiming at reaching the 450 $\mu$m confusion limit in the
COSMOS-CANDELS region, to study a representative sample of the high-redshift
far-infrared galaxy population that gives rise to the bulk of the far-infrared
background. We present the first-year data from STUDIES. We have reached a 450
$\mu$m noise level of 0.91~mJy for point sources at the map center, covered an
area of 151 arcmin$^2$, and detected 98 and 141 sources at 4.0 and 3.5
$\sigma$, respectively. Our derived counts are best constrained in the 3.5-25
mJy regime using directly detected sources. Below the detection limits, our
fluctuation analysis further constrains the slope of the counts down to 1 mJy.
The resulting counts at 1-25 mJy are consistent with a power law having a slope
of $-2.59$ ($\pm0.10$ for 3.5-25 mJy, and $^{+0.4}_{-0.7}$ for 1-3.5 mJy).
There is no evidence of a faint-end termination or turn-over of the counts in
this flux density range. Our counts are also consistent with previous SCUBA-2
blank-field and lensing cluster surveys. The integrated surface brightness from
our counts down to 1 mJy is $90.0\pm17.2$ Jy deg$^{-2}$, which can account for
up to $83^{+15}_{-16}\%$ of the COBE 450 $\mu$m background. We show that
Herschel counts at 350 and 500 $\mu$m are significantly higher than our 450
$\mu$m counts, likely caused by its large beam and source clustering.
High-angular resolution instruments like SCUBA-2 at 450 $\mu$m are therefore
highly beneficial for measuring the luminosity and spatial density of
high-redshift dusty galaxies.


  It is argued that the Rindler quantization is not a correct approach to study
the effects of acceleration on quantum fields. First, the "particle"-detector
approach based on the Minkowski quantization is not equivalent to the approach
based on the Rindler quantization. Second, the event horizon, which plays the
essential role in the Rindler quantization, cannot play any physical role for a
local noninertial observer.


  Here we show that the B-site cation (Fe/Mo) ordering in the double-perovskite
magnetoresistor, Sr2FeMoO6, is controlled by either kinetics or thermal
equilibrium depending on the temperature range. In order to enhance the
ordering, long synthesis periods at moderate temperatures are thus required.
Employment of a special oxygen-getter-controlled low-O2-pressure encapsulation
technique for the sample synthesis enabled us to use long heating periods
without evident evaporation of Mo, and thereby reach the thermal equilibrium
state and a high degree of B-site cation order. For samples fired at 1150C for
long periods (> 36 hours), record-high Ms values of 3.7 ~ 3.9 muB were
obtained.


  When two Bose-Einstein condensates (BEC's) collide with high collisional
energy, the celebrated matter wave interference pattern results. For lower
collisional energies the repulsive interaction energy becomes significant, and
the interference pattern evolves into an array of grey solitons. The lowest
collisional energy, producing a single pair of solitons, has not been probed.
We use density engineering on the healing length scale to produce such a pair
of solitons. These solitons then evolve periodically between vortex rings and
solitons, which we image in-situ on the healing length scale. The stable,
periodic evolution is in sharp contrast to the behavior of previous
experiments, in which the solitons decay irreversibly into vortex rings via the
snake instability. The evolution can be understood in terms of conservation of
mass and energy in a narrow condensate. The periodic oscillation between two
qualitatively different forms seems to be a rare phenomenon in nature.


  Handling various objects with different colors is a significant challenge for
image colorization techniques. Thus, for complex real-world scenes, the
existing image colorization algorithms often fail to maintain color
consistency. In this work, we attempt to integrate textual descriptions as an
auxiliary condition, along with the grayscale image that is to be colorized, to
improve the fidelity of the colorization process. To do so, we have proposed a
deep network that takes two inputs (grayscale image and the respective encoded
text description) and tries to predict the relevant color components. Also, we
have predicted each object in the image and have colorized them with their
individual description to incorporate their specific attributes in the
colorization process. After that, a fusion model fuses all the image objects
(segments) to generate the final colorized image. As the respective textual
descriptions contain color information of the objects present in the image,
text encoding helps to improve the overall quality of predicted colors. In
terms of performance, the proposed method outperforms existing colorization
techniques in terms of LPIPS, PSNR and SSIM metrics.


  The gravity models has been studied to analyze interaction between two
objects such as trade amount between a pair of countries, human migration
between a pair of countries and traffic flow between two cities. Particularly
in the international trade, predicting trade amount is instrumental to industry
and government in business decision making and determining economic policies.
Whereas the gravity models well captures such interaction between objects, the
model simplifies the interaction to extract essential relationships or needs
handcrafted features to drive the models. Recent studies indicate the
connection between graph neural networks (GNNs) and the gravity models in
international trade. However, to our best knowledge, hardly any previous
studies in the this domain directly predicts trade amount by GNNs. We propose
GGAE (Gravity-informed Graph Auto-encoder) and its surrogate model, which is
inspired by the gravity model, showing trade amount prediction by the gravity
model can be formulated as an edge weight prediction problem in GNNs and solved
by GGAE and its surrogate model. Furthermore, we conducted experiments to
indicate GGAE with GNNs can improve trade amount prediction compared to the
traditional gravity model by considering complex relationships.


  This paper surveys the connection between the elliptic curve
  E_D: x^3 + y^3 = D
  and a certain metaplectic form on the cubic cover of GL(3) which has the
property that its m,n^{th} Whittaker--Fourier coefficient is essentially the
L--series of the curve E_{m^2n}. One may obtain information about the
collective behavior the curves E_D by exploiting this connection; for example,
one can prove:
  Theorem: Fix any prime p \ne 3, and any congruence class c mod p. Then there
are infinitely many D congruent to c mod p such that the curve E_D has no
rational solutions.
  This paper is fairly self-contained; no prior knowledge of algebraic number
theory, analytic number theory or metaplectic forms is assumed. On the other
hand, this paper is a survey, no proofs are included.


  The Structural Similarity Index (SSIM) is generally considered to be a
milestone in the recent history of Image Quality Assessment (IQA). Alas, SSIM's
accepted development from the product of three heuristic factors continues to
obscure it's real underlying simplicity. Starting instead from a
symmetric-antisymmetric reformulation we first show SSIM to be a contrast or
visibility function in the classic sense. Furthermore, the previously enigmatic
structural covariance is revealed to be the difference of variances. The second
step, eliminating the intrinsic quadratic nature of SSIM, allows a near linear
correlation with human observer scores, and without invoking the usual, but
arbitrary, sigmoid model fitting. We conclude that SSIM can be re-interpreted
in terms of perceptual masking: it is essentially equivalent to a normalised
error or noise visibility function (NVF), and, furthermore, the NVF alone
explains it success in modelling perceptual image quality. We use the term
Dissimilarity Quotient (DQ) for the specifically anti/symmetric SSIM derived
NVF. It seems that IQA researchers may now have two choices: 1) Continue to use
the complex SSIM formula, but noting that SSIM only works coincidentally since
the covariance term is actually the mean square error (MSE) in disguise. 2) Use
the simplest of all perceptually-masked image quality metrics, namely NVF or
DQ. On this choice Occam is clear: in the absence of differences in predictive
ability, the fewer assumptions that are made, the better.


  Liquid crystal layers sandwiched between a reference plate and a
photosensitive substrate were investigated. We focused on the reverse geometry,
where the cell was illuminated by a laser beam from the reference side. In
planar cells instabilities occurred, static and dynamic ones, depending on the
angle between the laser polarization and the director orientation on the
reference plate. In cells where the molecules were aligned along the normal of
the reference plate, dynamic pattern was observed at all angles of
polarization. A simple model based on a photo-induced surface torque gives
account of the findings. Light scattering studies revealed some basic
properties of the instabilities.


  Filamentary structures identified in far-infrared observations of molecular
clouds are typically found to have full-widths at half-maximum $\sim\!0.1$ pc.
However, the physical explanation for this phenomenon is currently uncertain.
We use hydrodynamic simulations of cylindrically-symmetric converging flows to
show that the full-width at half-maximum of the resulting filament's surface
density profile, FWHM$_{\Sigma}$, is closely related to the location of the
accretion shock, where the inflow meets the boundary of the filament. For
inflow Mach Number, ${\cal M}$, between 1 and 5, filament FWHM$_{\Sigma}$s fall
in the range $0.03$ pc $\lesssim$ FWHM$_{\Sigma} \lesssim 0.3$ pc, with higher
${\cal M}$ resulting in narrower filaments. A large sample of filaments, seen
at different evolutionary stages and with different values of ${\cal M}$,
naturally results in a peaked distribution of FWHM$_{\Sigma}$s similar in shape
to that obtained from far-infrared observations of molecular clouds. However,
unless the converging flows are limited to ${\cal M} \lesssim 3$, the peak of
the distribution of FWHM$_{\Sigma}$s is below the observed $\sim 0.1$ pc.


  The yielding of concentrated cohesive suspensions can be deformation-rate
dependent. One consquence of this is that a single suspension can present in
one several different ways, depending upon how it is tested, or more generally,
how it is caused to flow. We have seen variously Herschel-Bulkley flow, highly
non-monotonic flow curves and highly erratic or chaotic yield, all in one
suspension. In controlled-rate testing one sees a systematic effect of
deformation rate. In controlled stress testing, matters are more subtle.
Whereas step-stress creep testing will elicit reproducible behaviour, any
attempt to determine a flow curve by, e.g. stepping up or sweeping stress at an
inappropriate rate can lead to highly irreproducible behaviour.


  In a series of papers by Henkel, Roger and Unterberger,
Schr\"{o}dinger-Virasoro algebras and their deformations were introduced and
investigated. In the present paper we determine the 2-cocycles of a class of
deformative Schr\"{o}dinger-Virasoro algebras.


  In this project, we aim to classify the speech taken as one of the four
emotions namely, sadness, anger, fear and happiness. The samples that have been
taken to complete this project are taken from Linguistic Data Consortium (LDC)
and UGA database. The important characteristics determined from the samples are
energy, pitch, MFCC coefficients, LPCC coefficients and speaker rate. The
classifier used to classify these emotional states is Support Vector Machine
(SVM) and this is done using two classification strategies: One against All
(OAA) and Gender Dependent Classification. Furthermore, a comparative analysis
has been conducted between the two and LPCC and MFCC algorithms as well.


  We study the propagation of sound in a homogeneous dipolar gas at zero
temperature, known as zero sound. We find that undamped sound propagation is
possible only in a range of solid angles around the direction of polarization
of the dipoles. Above a critical dipole moment, we find an unstable mode, by
which the gas collapses locally perpendicular to the dipoles' direction.


  Optomechanical structures are well suited to study photon-phonon
interactions, and they also turn out to be potential building blocks for
phononic circuits and quantum computing. In phononic circuits, in which
information is carried and processed by phonons, optomechanical structures
could be used as interfaces to photons and electrons thanks to their excellent
coupling efficiency. Among the components required for phononic circuits, such
structures could be used to create coherent phonon sources and detectors.
Complex functions other than emission or detection remain challenging and
addressing a single structure in a full network proves a formidable challenge.
Here, we propose and demonstrate a way to modulate the coherent emission from
optomechanical crystals by external optical pumping, effectively creating a
phonon switch working at ambient conditions of pressure and temperature and the
working speed of which (5 MHz) is only limited by the mechanical motion of the
optomechanical structure. We additionally demonstrate two other switching
schemes: harmonic switching in which the mechanical mode remains active but
different harmonics of the optical force are used, and switching to- and from
the chaotic regime. Furthermore, the method presented here allows to select any
single structure without affecting its surroundings, which is an important step
towards freely controllable networks of optomechanical phonon emitters.


  Deep radio observations of a wide region centred on the Hubble Deep Field
South have been performed, providing one of the most sensitive set of radio
observations acquired on the Australia Telescope Compact Array to date. A
central rms of ~10 microJy is reached at four frequencies (1.4, 2.5, 5.2 and
8.7 GHz). In this paper the full source catalogues from the 2.5, 5.2 and 8.7
GHz observations are presented to complement Paper II, along with a detailed
analysis of image quality and noise. We produce a consolidated catalogue by
matching sources across all four frequencies of our survey. Radio spectral
indices are used to investigate the nature of the radio sources and identify a
number of sources with flat or inverted radio spectra, which indicates AGN
activity. We also find several other interesting sources, including a broadline
emitting radio galaxy, a giant radio galaxy and three Gigahertz Peaked Spectrum
sources.


  We theoretically study noncoplanar spin textures in polar magnetic
conductors. Starting from the Kondo lattice model with the Rashba spin-orbit
coupling, we derive an effective spin model with generalized
Ruderman-Kittel-Kasuya-Yosida interactions including the anisotropic and
antisymmetric exchange interactions. By performing simulated annealing for the
effective model, we find that a vortex crystal of N\'eel type is stabilized
even in the absence of a magnetic field. Moreover, we demonstrate that a
Bloch-type vortex crystal, which is usually associated with the Dresselhaus
spin-orbit coupling, can also be realized in our Rashba-based model. A magnetic
field turns the vortex crystals into N\'eel- and Bloch-type skyrmion-like
crystals. Our results underscore that the interplay between the spin-orbit
coupling and itinerant magnetism brings fertile possibilities of noncoplanar
magnetic orderings.


  Basis set convergence of correlation effects on molecular atomization
energies beyond the CCSD (coupled cluster with singles and doubles)
approximation has been studied near the one-particle basis set limit.
Quasiperturbative connected triple excitations, (T), converge more rapidly than
$L^{-3}$ (where $L$ is the highest angular momentum represented in the basis
set), while higher-order connected triples, $T_3-(T)$, converge more slowly --
empirically, $\propto L^{-5/2}$. Quasiperturbative connected quadruple
excitations, (Q), converge smoothly as $\propto L^{-3}$ starting with the
cc-pVTZ basis set, while the cc-pVDZ basis set causes overshooting of the
contribution in highly polar systems. Higher-order connected quadruples display
only weak, but somewhat erratic, basis set dependence. Connected quintuple
excitations converge very rapidly with the basis set, to the point where even
an unpolarized double-zeta basis set yields useful numbers. In cases where
fully iterative CCSDTQ5 (coupled cluster up to connected quintuples)
calculations are not an option, CCSDTQ(5) (i.e., coupled cluster up to
connected quadruples plus a quasiperturbative connected quintuples correction)
cannot be relied upon in the presence of significant nondynamical correlation,
whereas CCSDTQ(5)$_\Lambda$ represents a viable alternative. Connected
quadruples corrections to the core-valence contribution are thermochemically
significant in some systems. [...] We conclude that ``$3\sigma\leq 1$ kJ/mol''
thermochemistry is feasible with current technology, but that the more
ambitious goal of $\pm$10 cm$^{-1}$ accuracy is illusory, at least for
atomization energies.


  At present, cryptocurrencies have become a global phenomenon in financial
sectors as it is one of the most traded financial instruments worldwide.
Cryptocurrency is not only one of the most complicated and abstruse fields
among financial instruments, but it is also deemed as a perplexing problem in
finance due to its high volatility. This paper makes an attempt to apply
machine learning techniques on the index and constituents of cryptocurrency
with a goal to predict and forecast prices thereof. In particular, the purpose
of this paper is to predict and forecast the close (closing) price of the
cryptocurrency index 30 and nine constituents of cryptocurrencies using machine
learning algorithms and models so that, it becomes easier for people to trade
these currencies. We have used several machine learning techniques and
algorithms and compared the models with each other to get the best output. We
believe that our work will help reduce the challenges and difficulties faced by
people, who invest in cryptocurrencies. Moreover, the obtained results can play
a major role in cryptocurrency portfolio management and in observing the
fluctuations in the prices of constituents of cryptocurrency market. We have
also compared our approach with similar state of the art works from the
literature, where machine learning approaches are considered for predicting and
forecasting the prices of these currencies. In the sequel, we have found that
our best approach presents better and competitive results than the best works
from the literature thereby advancing the state of the art. Using such
prediction and forecasting methods, people can easily understand the trend and
it would be even easier for them to trade in a difficult and challenging
financial instrument like cryptocurrency.


  We present a system for generating novel lyrics lines conditioned on music
audio. A bimodal neural network model learns to generate lines conditioned on
any given short audio clip. The model consists of a spectrogram variational
autoencoder (VAE) and a text VAE. Both automatic and human evaluations
demonstrate effectiveness of our model in generating lines that have an
emotional impact matching a given audio clip. The system is intended to serve
as a creativity tool for songwriters.


  We fit various colour-magnitude diagrams (CMDs) of the Galactic globular
clusters NGC\,6397 and NGC\,6809 (M55) by isochrones from the Dartmouth Stellar
Evolution Database (DSED) and Bag of Stellar Tracks and Isochrones (BaSTI) for
$\alpha$-enhanced [$\alpha$/Fe]$=+0.4$. For the CMDs, we use data sets from
{\it HST}, {\it Gaia}, VISTA, and other sources utilizing 32 and 23 photometric
filters for NGC\,6397 and NGC\,6809, respectively, from the ultraviolet to
mid-infrared. We obtain the following characteristics for NGC\,6397 and
NGC\,6809, respectively: metallicities [Fe/H]$=-1.84\pm0.02\pm0.1$ and
$-1.78\pm0.02\pm0.1$ (statistic and systematic uncertainties); distances
$2.45\pm0.02\pm0.06$ and $5.24\pm0.02\pm0.18$ kpc; ages $12.9\pm0.1\pm0.8$ and
$13.0\pm0.1\pm0.8$ Gyr; reddenings $E(B-V)=0.178\pm0.006\pm0.01$ and
$0.118\pm0.004\pm0.01$ mag; extinctions $A_\mathrm{V}=0.59\pm0.01\pm0.02$ and
$0.37\pm0.01\pm0.04$ mag; extinction-to-reddening ratio
$R_\mathrm{V}=3.32^{+0.32}_{-0.28}$ and $3.16^{+0.66}_{-0.56}$. Our estimates
agree with most estimates from the literature. BaSTI gives systematically
higher [Fe/H] and lower reddenings than DSED. Despite nearly the same
metallicity, age, and helium enrichment, these clusters show a considerable
horizontal branch (HB) morphology difference, which must therefore be described
by another parameter. This parameter must predominantly explain why the least
massive HB stars (0.58-0.63 solar masses) are only found within NGC 6809.
Probably they have been lost by the core-collapse cluster NGC\,6397 during its
dynamical evolution and mass segregation. In contrast, NGC\,6809 has a very low
central concentration and, hence, did not undergo this process.


  In recent years, there has been increasing recognition of the benefits of
having services provide auditable logs of data, as demonstrated by the
deployment of Certificate Transparency and the development of other
transparency projects. Most proposed systems, however, rely on a gossip
protocol by which users can be assured that they have the same view of the log,
but the few gossip protocols that do exist today are not suited for near-term
deployment. Furthermore, they assume the presence of global sets of auditors,
who must be blindly trusted to correctly perform their roles, in order to
achieve their stated transparency goals. In this paper, we address both of
these issues by proposing a gossip protocol and a verifiable registry, Mog, in
which users can perform their own auditing themselves. We prove the security of
our protocols and demonstrate via experimental evaluations that they are
performant in a variety of potential near-term deployments.


  Motivated by growing concerns over ensuring privacy on social networks, we
develop new algorithms and impossibility results for fitting complex
statistical models to network data subject to rigorous privacy guarantees. We
consider the so-called node-differentially private algorithms, which compute
information about a graph or network while provably revealing almost no
information about the presence or absence of a particular node in the graph.
  We provide new algorithms for node-differentially private estimation for a
popular and expressive family of network models: stochastic block models and
their generalization, graphons. Our algorithms improve on prior work, reducing
their error quadratically and matching, in many regimes, the optimal nonprivate
algorithm. We also show that for the simplest random graph models ($G(n,p)$ and
$G(n,m)$), node-private algorithms can be qualitatively more accurate than for
more complex models---converging at a rate of $\frac{1}{\epsilon^2 n^{3}}$
instead of $\frac{1}{\epsilon^2 n^2}$. This result uses a new extension lemma
for differentially private algorithms that we hope will be broadly useful.


  Exploiting symmetry in dynamical systems is a powerful way to improve the
generalization of deep learning. The model learns to be invariant to
transformation and hence is more robust to distribution shift. Data
augmentation and equivariant networks are two major approaches to injecting
symmetry into learning. However, their exact role in improving generalization
is not well understood. In this work, we derive the generalization bounds for
data augmentation and equivariant networks, characterizing their effect on
learning in a unified framework. Unlike most prior theories for the i.i.d.
setting, we focus on non-stationary dynamics forecasting with complex temporal
dependencies.


  When analyzing complex networks a key target is to uncover their modular
structure, which means searching for a family of modules, namely node subsets
spanning each a subnetwork more densely connected than the average. This work
proposes a novel type of objective function for graph clustering, in the form
of a multilinear polynomial whose coefficients are determined by network
topology. It may be thought of as a potential function, to be maximized, taking
its values on fuzzy clusterings or families of fuzzy subsets of nodes over
which every node distributes a unit membership. When suitably parametrized,
this potential is shown to attain its maximum when every node concentrates its
all unit membership on some module. The output thus is a partition, while the
original discrete optimization problem is turned into a continuous version
allowing to conceive alternative search strategies. The instance of the problem
being a pseudo-Boolean function assigning real-valued cluster scores to node
subsets, modularity maximization is employed to exemplify a so-called quadratic
form, in that the scores of singletons and pairs also fully determine the
scores of larger clusters, while the resulting multilinear polynomial potential
function has degree 2. After considering further quadratic instances, different
from modularity and obtained by interpreting network topology in alternative
manners, a greedy local-search strategy for the continuous framework is
analytically compared with an existing greedy agglomerative procedure for the
discrete case. Overlapping is finally discussed in terms of multiple runs, i.e.
several local searches with different initializations.


  The recently constructed Hubble diagram using a combined sample of SNLS and
SDSS-II Type Ia SNe, and an application of the Alcock-Paczynski (AP) test using
model-independent Baryon Acoustic Oscillation data, have suggested that the
principal constraint underlying the cosmic expansion is the total
equation-of-state of the cosmic fluid, rather than that of its dark energy.
These studies have focused on the critical redshift range (0 < z < 2) within
which the transition from decelerated to accelerated expansion is thought to
have occurred, and they suggest that the cosmic fluid has zero active mass,
consistent with a constant expansion rate. The evident impact of this
conclusion on cosmological theory calls for an independent confirmation. In
this paper, we carry out this crucial one-on-one comparison between the R_h=ct
Universe (an FRW cosmology with zero active mass) and wCDM/LCDM, using the
latest high-z measurements of H(z). Whereas the Type Ia SNe yield the
integrated luminosity distance, while the AP diagnostic tests the geometry of
the Universe, the Hubble parameter directly samples the expansion rate itself.
We find that the model-independent cosmic chronometer data prefer R_h}=ct over
wCDM/LCDM with a BIC likelihood of ~95% versus only ~5%, in strong support of
the earlier SNeIa and AP results. This contrasts with a recent analysis of H(z)
data based solely on BAO measurements which, however, strongly depend on the
assumed cosmology. We discuss why the latter approach is inappropriate for
model comparisons, and emphasize again the need for truly model-independent
observations to be used in cosmological tests.


  We consider a gravitating system consisting of a scalar field minimally
coupled to gravity with a self-interacting potential and a U(1) nonlinear
electromagnetic field. Solving analytically and numerically the coupled system
for both power-law and Born-Infeld type electrodynamics, we find charged hairy
black hole solutions. Then, we study the thermodynamics of these solutions and
we find that at a low temperature the topological charged black hole with
scalar hair is thermodynamically preferred, whereas the topological charged
black hole without scalar hair is thermodynamically preferred at a high
temperature for power-law electrodynamics. Interestingly enough, these phase
transitions occur at a fixed critical temperature and do not depend on the
exponent $p$ of the nonlinearity electrodynamics.


  To establish the presence and orientation of the proposed striped phase in
ultra-high mobility 2D electron systems at filling factor 9/2, current path
transport properties are determined by varying the separation and allignment of
current and voltage contacts. Contacts alligned orthogonal to the proposed
intrinsic striped phase produce voltages consistent with current spreading
along the stripes; current driven along the proposed stripe direction results
in voltages consistent with channeling along the stripes. Direct comparison is
made to current spreading/channeling properties of artificially induced 1D
charge modulated systems, which indicates the 9/2 direction.


  By introducing electromagnetic formfactors in the spacelike region we extend
an effective, gauge invariant Lagrangian model considering Born terms, baryon
resonances up to 1.7 GeV and vector meson contributions (Rho, Omega) to
calculate electroproduction of Pi-mesons. This model forms the basis for
predictions of pion induced dilepton production on the nucleon. Therefore, the
implemented formfactors are constructed in such a way that their analytic
continuation into the timelike region is possible. It is shown that the seagull
term and the N*(1520) resonance play a dominant role in the dilepton
production.


  A Hausdorff topological space X is van der Waerden if for every sequence
(x_n)_n in X there is a converging subsequence (x_n)_{n in A} where subset A of
omega contains arithmetic progressions of all finite lengths. A Hausdorff
topological space X is Hindman if for every sequence (x_n)_n in X there is an
IP-converging subsequence (x_n)_{n in FS(B)} for some infinite subset B of
omega. We show that the continuum hypothesis implies the existence of a van der
Waerden space which is not Hindman.


  Let $G$ be a graph and $S, T \subseteq V(G)$ be (possibly overlapping) sets
of terminals, $|S|=|T|=k$. We are interested in computing a vertex sparsifier
for terminal cuts in $G$, i.e., a graph $H$ on a smallest possible number of
vertices, where $S \cup T \subseteq V(H)$ and such that for every $A \subseteq
S$ and $B \subseteq T$ the size of a minimum $(A,B)$-vertex cut is the same in
$G$ as in $H$. We assume that our graphs are unweighted and that terminals may
be part of the min-cut. In previous work, Kratsch and Wahlstr\"om (FOCS
2012/JACM 2020) used connections to matroid theory to show that a vertex
sparsifier $H$ with $O(k^3)$ vertices can be computed in randomized polynomial
time, even for arbitrary digraphs $G$. However, since then, no improvements on
the size $O(k^3)$ have been shown.
  In this paper, we draw inspiration from the renowned Bollob\'as's
Two-Families Theorem in extremal combinatorics and introduce the use of total
orderings into Kratsch and Wahlstr\"om's methods. This new perspective allows
us to construct a sparsifier $H$ of $\Theta(k^2)$ vertices for the case that
$G$ is a DAG. We also show how to compute $H$ in time near-linear in the size
of $G$, improving on the previous $O(n^{\omega+1})$. Furthermore, $H$ recovers
the closest min-cut in $G$ for every partition $(A,B)$, which was not
previously known. Finally, we show that a sparsifier of size $\Omega(k^2)$ is
required, both for DAGs and for undirected edge cuts.


  We investigate the Dirac equation in Kerr-Newman space-time, using horizon
penetrating coordinates (Eddington-Finkelstein-Coordinates) and the
Newman-Penrose formalism to separate the equation into radial and angular
systems of ordinary differential equations, and deriving the asymptotics of the
radial solutions at infinity and at the Cauchy horizon.


  The purpose of this paper is to discuss the validity of the assumptions (W)
and (S) stated in a previous work, about the torsion in the modular l-adic
cohomology of Deligne-Lusztig varieties associated to Coxeter elements. We
prove that both (W) and (S) hold except for groups of type E_7 or E_8.


  We give a surface integral derivation of the leading-order evolution
equations for the spin and energy of a relativistic body interacting with other
bodies in the post-Newtonian expansion scheme. The bodies can be arbitrarily
shaped and can be strongly self-gravitating. The effects of all mass and
current multipoles are taken into account. As part of the computation one of
the 2PN potentials parametrizing the metric is obtained. The formulae obtained
here for spin and energy evolution coincide with those obtained by Damour,
Soffel and Xu for the case of weakly self-gravitating bodies. By combining an
Einstein-Infeld-Hoffman-type surface integral approach with multipolar
expansions we extend the domain of validity of these evolution equations to a
wide class of strongly self-gravitating bodies. This paper completes in a
self-contained way a previous work by Racine and Flanagan on translational
equations of motion for compact objects.


  We introduce the concept of selective quantum state tomography or SQST, a
tomographic scheme that enables a user to estimate arbitrary elements of an
unknown quantum state using a fixed measurement record. We demonstrate how this
may be done with the following notable advantages (i) a number of state copies
that depends only on the desired precision of the estimation, rather than the
dimension of the unknown state; (ii) a similar reduction in the requisite
classical memory and computational cost; (iii) an approach to state tomography
using $O(\epsilon^{-2}\log d)$ state copies for maximum norm error $\epsilon$,
as well as achieving nearly optimal bounds for full tomography with independent
measurements. As an immediate extension to this technique we proceed to show
that SQST can be used to generate an universal data sample, of fixed and
dimension independent size, from which one can extract the mean values from a
continuous class of operators on demand.


  We revisit the association of unidentified Galactic plane EGRET sources with
tracers of recent massive star formation and death. Up-to-date catalogs of OB
associations, SNRs, young pulsars, HII regions and young open clusters were
used in finding counterparts for a recent list of EGRET sources. It has been
argued for some time that EGRET source positions are correlated with SNRs and
OB associations as a class; we extend such analyses by finding additional
counterparts and assessing the probability of individual source
identifications. Among the several scenarios relating EGRET sources to massive
stars, we focus on young neutron stars as the origin of the gamma-ray emission.
The characteristics of the candidate identifications are compared to the known
gamma-ray pulsar sample and to detailed Galactic population syntheses using our
outer gap pulsar model of gamma-ray emission. Both the spatial distribution and
luminosity function of the candidates are in good agreement with the model
predictions; we infer that young pulsars can account for the bulk of the excess
low latitude EGRET sources. We show that with this identification, the
gamma-ray point sources provide an important new window into the history of
recent massive star death in the solar neighborhood.


  In this study, the ducted propeller has been numerically investigated under
oblique flow, which is crucial and challenging for the design and safe
operation of thruster driven vessel and dynamic positioning (DP) system. A
Reynolds-Averaged Navier-Stokes (RANS) model has been first evaluated in the
quasi-steady investigation on a single ducted propeller operating in open water
condition, and then a hybrid RANS/LES model is adapted for the transient
sliding mesh computations. A representative test geometry considered here is a
marine model thruster which is discretized with structured hexahedral cells,
and the gap between the blade tip and nozzle is carefully meshed to capture the
flow dynamics. The computational results are assessed by a systematic grid
convergence study and compared with the available experimental data. As a part
of novel contribution, multiple incidence angles from $15^\circ$ to $60^\circ$
have been analyzed with varying advance coefficients. The main emphasis has
been placed on the hydrodynamic loads that act on the propeller blades and
nozzle as well as their variation with different configurations. The results
reveal that while the nozzle absorbs much effort from the oblique flow, the
imbalance between blades at different positions is still noticeable. Such
unbalance flow dynamics on the blades and the nozzle has a direct implication
on the variation of thrust and torque of a marine thruster.


  Noncommutative spaces of geodesics provide an alternative way of introducing
noncommutative relativistic kinematics endowed with quantum group symmetry. In
this paper we present explicitly the seven noncommutative spaces of time-,
space- and light-like geodesics that can be constructed from the time-, space-
and light- versions of the $\kappa$-Poincar\'e quantum symmetry in (3+1)
dimensions. Remarkably enough, only for the light-like (or null-plane)
$\kappa$-Poincar\'e deformation the three types of noncommutative spaces of
geodesics can be constructed, while for the time-like and space-like
deformations both the quantum time-like and space-like geodesics can be
defined, but not the light-like one. This obstruction comes from the constraint
imposed by the coisotropy condition for the corresponding deformation with
respect to the isotropy subalgebra associated to the given space of geodesics,
since all these quantum spaces are constructed as quantizations of the
corresponding classical coisotropic Poisson homogeneous spaces. The known
quantum space of geodesics on the light cone is given by a five-dimensional
homogeneous quadratic algebra, and the six nocommutative spaces of time-like
and space-like geodesics are explicitly obtained as six-dimensional nonlinear
algebras. Five out of these six spaces are here presented for the first time,
and Darboux generators for all of them are found, thus showing that the quantum
deformation parameter $\kappa^{-1}$ plays exactly the same algebraic role on
quantum geodesics as the Planck constant $\hbar$ plays in the usual phase space
description of quantum mechanics.


  We study entanglement witness and present a construction of entanglement
witnesses in terms of the mutually unbiased measurements (MUMs). These
witnesses include the entanglement witnesses constructed from mutually unbiased
bases (MUBs) as a special case. Comparing with the dimension dependence of
MUBs, the witnesses can be always constructed from a complete set of $d+1$ MUMs
for any dimension $d$. We show that our witness can detect entanglement better
than previous separability criterion given also by MUMs. And the approach can
be experimentally implemented.


  Intelligent Transport Systems (ITS) constitute a core representative of a
paradigm shift in the transport sector. The extent to which the transport
sector has adapted itself to this digital era relies considerably on the
availability of suitable and reliable data. Currently, several data-related
limitations, such as the scarcity of available datasets, hinder the deployment
of ITS services. Such limitations may be overcome with the deployment of
properly designed data exchange platforms that enable a seamless life-cycle of
data harvesting, processing, and sharing. The European Union recognizing the
potential benefits of such platforms has, through the relevant Delegated
Regulations, proposed the development of a National Access Point (NAP) by each
individual Member State. This paper aims to ascertain the role of a NAP within
the ITS ecosystem, to investigate methodologies used in designing such
platforms, and, through the drafting of an extended use case, showcase a NAP
operational process and associate possible benefits with specific steps of it.


  This paper presents an approach to modeling progressive event-history data
when the overall objective is prediction based on time-dependent covariates.
This approach does not model the hazard function directly. Instead, it models
the process of the state indicators of the event history so that the
time-dependent covariates can be incorporated and predictors of the future
events easily formulated. Our model can be applied to a range of real-world
problems in medical and agricultural science.


  The use of fluorescent molecules to create long sequences of low-density,
diffraction-limited images enables highly-precise molecule localization.
However, this methodology requires lengthy imaging times, which limits the
ability to view dynamic interactions of live cells on short time scales. Many
techniques have been developed to reduce the number of frames needed for
localization, from classic iterative optimization to deep neural networks.
Particularly, deep algorithm unrolling utilizes both the structure of iterative
sparse recovery algorithms and the performance gains of supervised deep
learning. However, the robustness of this approach is highly dependant on
having sufficient training data. In this paper we introduce deep unrolled
self-supervised learning, which alleviates the need for such data by training a
sequence-specific, model-based autoencoder that learns only from given
measurements. Our proposed method exceeds the performance of its supervised
counterparts, thus allowing for robust, dynamic imaging well below the
diffraction limit without any labeled training samples. Furthermore, the
suggested model-based autoencoder scheme can be utilized to enhance
generalization in any sparse recovery framework, without the need for external
training data.


  $QCD_2$ with fermions in the adjoint representation is invariant under
$SU(N)/Z_N$ and thereby is endowed with a non-trivial vacuum structure
(k-sectors). The static potential between adjoint charges, in the limit of
infinite mass, can be therefore obtained by computing Wilson loops in the pure
Yang-Mills theory with the same non-trivial structure. When the (Euclidean)
space-time is compactified on a sphere $S^2$, Wilson loops can be exactly
expressed in terms of an infinite series of topological excitations
(instantons). The presence of k-sectors modifies the energy spectrum of the
theory and its instanton content. For the exact solution, in the limit in which
the sphere is decompactified, a k-sector can be mimicked by the presence of
k-fundamental charges at $\infty$, according to a Witten's suggestion. However
this property neither holds before decompactification nor for the genuine
perturbative solution which corresponds to the zero-instanton contribution on
$S^2$.


  While keyphrase extraction has received considerable attention in recent
years, relatively few studies exist on extracting keyphrases from social media
platforms such as Twitter, and even fewer for extracting disaster-related
keyphrases from such sources. During a disaster, keyphrases can be extremely
useful for filtering relevant tweets that can enhance situational awareness.
Previously, joint training of two different layers of a stacked Recurrent
Neural Network for keyword discovery and keyphrase extraction had been shown to
be effective in extracting keyphrases from general Twitter data. We improve the
model's performance on both general Twitter data and disaster-related Twitter
data by incorporating contextual word embeddings, POS-tags, phonetics, and
phonological features. Moreover, we discuss the shortcomings of the often used
F1-measure for evaluating the quality of predicted keyphrases with respect to
the ground truth annotations. Instead of the F1-measure, we propose the use of
embedding-based metrics to better capture the correctness of the predicted
keyphrases. In addition, we also present a novel extension of an
embedding-based metric. The extension allows one to better control the penalty
for the difference in the number of ground-truth and predicted keyphrases