  Weblogs, comprised of records detailing user activities on any website, offer
valuable insights into user preferences, behavior, and interests. Numerous
recommendation algorithms, employing strategies such as collaborative
filtering, content-based filtering, and hybrid methods, leverage the data mined
through these weblogs to provide personalized recommendations to users. Despite
the abundance of information available in these weblogs, identifying and
extracting pertinent information and key features from them necessitate
extensive engineering endeavors. The intricate nature of the data also poses a
challenge for interpretation, especially for non-experts. In this study, we
introduce a sophisticated and interactive recommendation framework denoted as
InteraRec, which diverges from conventional approaches that exclusively depend
on weblogs for recommendation generation. InteraRec framework captures
high-frequency screenshots of web pages as users navigate through a website.
Leveraging state-of-the-art multimodal large language models (MLLMs), it
extracts valuable insights into user preferences from these screenshots by
generating a textual summary based on predefined keywords. Subsequently, an
LLM-integrated optimization setup utilizes this summary to generate tailored
recommendations. Through our experiments, we demonstrate the effectiveness of
InteraRec in providing users with valuable and personalized offerings.
Furthermore, we explore the integration of session-based recommendation systems
into the InteraRec framework, aiming to enhance its overall performance.
Finally, we curate a new dataset comprising of screenshots from product web
pages on the Amazon website for the validation of the InteraRec framework.
Detailed experiments demonstrate the efficacy of the InteraRec framework in
delivering valuable and personalized recommendations tailored to individual
user preferences.


  In 1929 Lanczos showed how to derive Dirac's equation from a more fundamental
system that predicted that spin 1/2 particles should come in pairs. Today,
these pairs can unambiguously be interpreted as isospin doublets. From the same
fundamental equation, Lanczos derived also the correct form of the wave
equation of massive spin 1 particles that would be rediscovered in 1936 by
Proca.
  Lanczos's fundamental system was put in Lagrangian form and generalized in
1933 by Einstein and Mayer, who used the semivector instead of the quaternion
formalism. Although they not did study all possible solutions, Einstein and
Mayer showed that the doublets consisted of particles with different mass and
charge. In fact, there are two main classes of doublets: proton/neutron and
electron/neutrino pairs.


  The distributed Kaczmarz algorithm is an adaptation of the standard Kaczmarz
algorithm to the situation in which data is distributed throughout a network
represented by a tree. We isolate substructures of the network and study
convergence of the distributed Kazmarz algorithm for relatively large
relaxation parameters associated to these substructures. If the system is
consistent, then the algorithm converges to the solution of minimal norm;
however, if the system is inconsistent, then the algorithm converges to an
approximated least-squares solution that is dependent on the parameters and the
network topology. We show that the relaxation parameters may be larger than the
standard upper-bound in literature in this context and provide numerical
experiments to support our results.


  Transformer has achieved competitive performance against state-of-the-art
end-to-end models in automatic speech recognition (ASR), and requires
significantly less training time than RNN-based models. The original
Transformer, with encoder-decoder architecture, is only suitable for offline
ASR. It relies on an attention mechanism to learn alignments, and encodes input
audio bidirectionally. The high computation cost of Transformer decoding also
limits its use in production streaming systems. To make Transformer suitable
for streaming ASR, we explore Transducer framework as a streamable way to learn
alignments. For audio encoding, we apply unidirectional Transformer with
interleaved convolution layers. The interleaved convolution layers are used for
modeling future context which is important to performance. To reduce
computation cost, we gradually downsample acoustic input, also with the
interleaved convolution layers. Moreover, we limit the length of history
context in self-attention to maintain constant computation cost for each
decoding step. We show that this architecture, named Conv-Transformer
Transducer, achieves competitive performance on LibriSpeech dataset (3.6\% WER
on test-clean) without external language models. The performance is comparable
to previously published streamable Transformer Transducer and strong hybrid
streaming ASR systems, and is achieved with smaller look-ahead window (140~ms),
fewer parameters and lower frame rate.


  We measure the properties of optical emission lines in multiple locations
across the Large Magellanic Cloud (LMC) using the Australian National
University 2.3-metre telescope and the WiFeS integral field spectrograph. From
these measurements we interpolate maps of the gas phase metallicity,
extinction, Halpha radial velocity, and Halpha velocity dispersion across the
LMC. The LMC metallicity maps show a complex structure that cannot be explained
by a simple radial gradient. The bright HII region 30 Doradus stands out as a
region of high extinction. The Halpha and HI gas radial velocities are mostly
consistent except for a region to the south and east of the LMC centre. The
Halpha velocity dispersion is almost always higher than the HI velocity
dispersion, except in the region that shows the divergence in radial velocity,
where the HI velocity dispersion is greater than the Halpha velocity
dispersion. This suggests that the HI gas is diverging from the stellar radial
velocity, perhaps as a result of inflow or outflow of HI gas. The study of
dwarf galaxies like the LMC is important as they are the building blocks of
larger galaxies like our own Milky Way. The maps provided in this work show
details not accessible in the study of more distant dwarf galaxies.


  We report a multiband transport study of bilayer graphene at high carrier
densities. Employing a poly(ethylene)oxide-CsClO$_4$ solid polymer electrolyte
gate we demonstrate the filling of the high energy subbands in bilayer graphene
samples at carrier densities $|n|\geq2.4\times 10^{13}$ cm$^{-2}$. We observe a
sudden increase of resistance and the onset of a second family of Shubnikov de
Haas (SdH) oscillations as these high energy subbands are populated. From
simultaneous Hall and magnetoresistance measurements together with SdH
oscillations in the multiband conduction regime, we deduce the carrier
densities and mobilities for the higher energy bands separately and find the
mobilities to be at least a factor of two higher than those in the low energy
bands.


  In this paper, we study divergence properties of Fourier series on
Cantor-type fractal measure, also called Mock Fourier series. We give a
sufficient condition under which the Mock Fourier series for doubling spectral
measure is divergent on non-zero set. In particularly, there exists an example
of the quarter Cantor measure whose Mock Fourier sums is not almost everywhere
convergent.


  We propose a phenomenological model where the gravitational interaction
between dark matter and baryons is suppressed on small, subgalactic scales. We
describe the gravitational force by adding a Yukawa contribution to the
standard Newtonian potential and show that this interaction scheme is
effectively suggested by the available observations of the inner rotation
curves of small mass galaxies. Besides helping in interpreting the cuspy
profile of dark matter halos observed in N-body simulations, this potential
regulates the quantity of baryons within halos of different masses.


  High energy resolution photoelectron spectroscopy of conduction electrons in
the vicinity of the Fermi-edge in Al and Au at the excitation energy of 880 and
7940 eV was carried out using synchrotron radiation. For the excitation energy
of 7940 eV, the observed Fermi energy of Al shows a remarkable shift to higher
binding energy as compared with that of Au, with accompanying broadening. This
is due to the recoil effect of the emitted photoelectrons. The observed spectra
are well reproduced by a simple model of Bloch electrons based on the isotropic
Debye model.


  Recently, many AI researchers and practitioners have embarked on research
visions that involve doing AI for "Good". This is part of a general drive
towards infusing AI research and practice with ethical thinking. One frequent
theme in current ethical guidelines is the requirement that AI be good for all,
or: contribute to the Common Good. But what is the Common Good, and is it
enough to want to be good? Via four lead questions, I will illustrate
challenges and pitfalls when determining, from an AI point of view, what the
Common Good is and how it can be enhanced by AI. The questions are: What is the
problem / What is a problem?, Who defines the problem?, What is the role of
knowledge?, and What are important side effects and dynamics? The illustration
will use an example from the domain of "AI for Social Good", more specifically
"Data Science for Social Good". Even if the importance of these questions may
be known at an abstract level, they do not get asked sufficiently in practice,
as shown by an exploratory study of 99 contributions to recent conferences in
the field. Turning these challenges and pitfalls into a positive
recommendation, as a conclusion I will draw on another characteristic of
computer-science thinking and practice to make these impediments visible and
attenuate them: "attacks" as a method for improving design. This results in the
proposal of ethics pen-testing as a method for helping AI designs to better
contribute to the Common Good.


  The IP-theorem of the Kohn-Sham (KS) density functional theory (DFT) states
that the energy of the highest occupied molecular orbital (HOMO)
$\epsilon_{HOMO}$ equals the negative of the first ionization potential (IP),
thus ascribing a physical meaning to one of the eigenvalues of the KS
hamiltonian. We scrutinize the fact that the validity of the IP-theorem relies
critically on the electron density $n({\bf r})$, far from the system, to be
determined by HOMO only, behaving as $n({\bf r}) \underset{r\to\infty}{\sim}
e^{- 2 \sqrt{-2 \epsilon_{HOMO}} r}$. While this behavior always holds for
finite systems, it does not hold for mesoscopic ones, such as
quasi-two-dimensional (Q2D) electron gas or Q2D crystals. We show that this
leads to the violation of the IP-theorem for the latter class of systems. This
finding has a strong bearing on the role of the KS valence band with respect to
the work-function problem in the mesoscopic case. Based on our results, we
introduce a concept of the IP band structure as an observable alternative to
its unphysical KS counterpart. A practical method of the determination of IP
band structure in terms of DFT quantities is provided.


  In this work we compute the spectra, waveforms and total scalar energy
radiated during the radial infall of a small test particle coupled to a scalar
field into a $d$-dimensional Schwarzschild-anti-de Sitter black hole. We focus
on $d=4, 5$ and 7, extending the analysis we have done for $d=3$. For small
black holes, the spectra peaks strongly at a frequency $\omega \sim d-1$, which
is the lowest pure anti-de Sitter (AdS) mode. The waveform vanishes
exponentially as $t \to \infty$, and this exponential decay is governed
entirely by the lowest quasinormal frequency. This collision process is
interesting from the point of view of the dynamics itself in relation to the
possibility of manufacturing black holes at LHC within the brane world
scenario, and from the point of view of the AdS/CFT conjecture, since the
scalar field can represent the string theory dilaton, and 4, 5, 7 are
dimensions of interest for the AdS/CFT correspondence.


  Despite extensive researches on manganites owing to widespread use in modern
electronics, this class of metal oxides does not cease to surprise with its
unique properties and new phenomena. Here we have studied structural and
magnetic properties of non-Heisenberg manganite nanoparticles with a strong
spin-electron coupling. During transition from low temperature ferromagnetic to
high temperature paramagnetic state, the change in charge, valence and spin
(magnetic moment) with the localization of eg-electrons on the manganese ions
have been detected. With decrease in a temperature, the overstated effective
magnetic moment of Mn ions in paramagnetic phase is reduced dramatically
testifying to spin-dependent magnetism. The critical behavior of magnetization
with determination of critical parameters near second-order phase transition
has been studied comprehensively. Based on unusual behavior of temperature and
field dependences of magnetic entropy change under different magnetic field, an
additional influence of superparamagnetism of nanoparticles on the
magnetocaloric effect has been found.


  In this paper, the commensurate fractional-order variant of an Hopfield
neuronal network is analyzed. The system is integrated with the ABM method for
fractional-order equations. Beside the standard stability analysis of
equilibria, the divergence of fractional order is proposed to determine the
instability of the equilibria. The bifurcation diagrams versus the fractional
order, and versus one parameter, reveal a strange phenomenon suggesting that
the bifurcation branches generated by initial conditions outside neighborhoods
of unstable equilibria are spurious sets although they look similar with those
generated by initial conditions close to the equilibria. These spurious sets
look ``delayed'' in the considered bifurcation scenario. Once the integration
step-size is reduced, the spurious branches maintain their shapes but tend to
the branches obtained from initial condition within neighborhoods of
equilibria. While the spurious branches move once the integration step size
reduces, the branches generated by the initial conditions near the equilibria
maintain their positions in the considered bifurcation space. This phenomenon
does not depend on the integration-time interval, and repeats in the parameter
bifurcation space.


  A well-known conjecture of Tuza asserts that if a graph has at most $t$
pairwise edge-disjoint triangles, then it can be made triangle-free by removing
at most $2t$ edges. If true, the factor 2 would be best possible. In the
directed setting, also asked by Tuza, the analogous statement has recently been
proven, however, the factor 2 is not optimal. In this paper, we show that if an
$n$-vertex directed graph has at most $t$ pairwise arc-disjoint directed
triangles, then there exists a set of at most $1.8t+o(n^2)$ arcs that meets all
directed triangles. We complement our result by presenting two constructions of
large directed graphs with $t\in\Omega(n^2)$ whose smallest such set has
$1.5t-o(n^2)$ arcs.


  We discuss the linear power corrections to the electroweak production of top
quarks at the LHC using renormalon calculus. We show how such non-perturbative
corrections can be obtained using the Low-Burnett-Kroll theorem, which provides
the first subleading term to the expansion of the real-emission amplitudes
around the soft limit. We demonstrate that there are no linear power
corrections to the total cross sections of arbitrary processes of a single top
production type provided that these cross sections are expressed in terms of a
short-distance top quark mass. We also derive a universal formula for the
linear power corrections to generic observables that involve the top-quark
momentum.


  We summarize results on the asymptotics of the two-particle Green functions
of interacting electrons in one dimension. Below a critical value of the
chemical potential the Fermi surface vanishes, and the system can no longer be
described as a Luttinger liquid. Instead, the non-relativistic Fermi gas with
infinite point-like repulsion becomes the universal model for the
long-wavelength, low temperature physics of the one-dimensional electrons. This
model, which we call the impenetrable electron gas, allows for a rigorous
mathematical treatment. In particular, a so-called determinant representation
for the two particle Green function could be derived. This determinant
representation is related to an integrable classical evolution equation and to
a Riemann-Hilbert problem, that enable the exact calculation of the asymptotics
of the two-particle Green functions.


  The progenitors of Type IIP supernovae have an apparent upper limit to their
initial masses of about 20 solar masses, suggesting that the most massive red
supergiants evolve to warmer temperatures before their terminal explosion. But
very few post-red supergiants are known. We have identified a small group of
luminous stars in M31 and M33 that are candidates for post-red supergiant
evolution. These stars have A -- F-type supergiant absorption line spectra and
strong hydrogen emission. Their spectra are also distinguished by the Ca II
triplet and [Ca II] doublet in emission formed in a low density circumstellar
environment. They all have significant near- and mid-infrared excess radiation
due to free-free emission and thermal emission from dust. We estimate the
amount of mass they have shed and discuss their wind parameters and mass loss
rates which range from a few times$ 10^-6 to 10^-4 solar masses/yr. On an HR
Diagram, these stars will overlap the region of the LBVs at maximum light,
however the warm hypergiants are not LBVs. Their non-spherical winds are not
optically thick and they have not exhibited any significant variability. We
suggest, however, that the warm hypergiants may be the progenitors of the "less
luminous" LBVs such as R71 and even SN1987A.


  We describe a multi-scale resolution approach to analyzing problems in
Quantum Mechanics using Daubechies wavelet basis. The expansion of the
wavefunction of the quantum system in this basis allows a natural
interpretation of each basis function as a quantum fluctuation of a specific
resolution at a particular location. The Hamiltonian matrix constructed in this
basis describes couplings between different length scales and thus allows for
intuitive volume and resolution truncation. In quantum mechanical problems with
a natural length scale, one can get approximate solution of the problem through
simple matrix diagonalization. We illustrate this approach using the example of
the standard quantum mechanical simple harmonic oscillator.


  In this article studied the influence of various factors on the synthesis of
nano carbons from walnut shells, apricot kernels, methane, natural gas and
propane-butane fractions, and also checked the textural and sorption
characteristics of the obtained nanocarbon. The catalytic activity of a
catalyst containing (CuO)x*(CoO)y*(NiO)z*(Fe2O3)k*(MoO3)m/HSZ prepared based on
"sol-gel" technology for the implementation of processes was studied under
differential reactor conditions. The morphological composition of the samples
was performed by scanning electron microscopy on an LEO EVO 50 HVP instrument
equipped with a part of energy dispersive X-ray microanalysis.
Energy-dispersive X-ray spectra were recorded at a working distance of 10 mm at
20 kV. The microstructure of the samples was investigated by the method of a
glowing electron microscope on a Jem-2000 CX device. Using the BET method, the
specific surface area of the carbon nanotubes was measured. Statistical and
morphological characteristics of material porosity were calculated. The
specific surface area is 168.7 m2/g, the specific pore volume is 0.456 cm3/g,
and the average hole diameter is 2.58 nm. In the case of walnut shells, this
absorption band was observed at 1376 cm-1 and 1064 cm-1. When examining samples
based on apricot kernels in the infrared spectrum at various temperatures in an
inert nitrogen atmosphere, it can be seen that cellulose and lignin are
characterized by a strong absorption band, and the treatment decreases with
increasing temperature.


  We study dynamical ordering of rods. In this process, rod alignment via
pairwise interactions competes with diffusive wiggling. Under strong diffusion,
the system is disordered, but at weak diffusion, the system is ordered. We
present an exact steady-state solution for the nonlinear and nonlocal kinetic
theory of this process. We find the Fourier transform as a function of the
order parameter, and show that Fourier modes decay exponentially with the wave
number. We also obtain the order parameter in terms of the diffusion constant.
This solution is obtained using iterated partitions of the integer numbers.


  Image compression is a fundamental research field and many well-known
compression standards have been developed for many decades. Recently, learned
compression methods exhibit a fast development trend with promising results.
However, there is still a performance gap between learned compression
algorithms and reigning compression standards, especially in terms of widely
used PSNR metric. In this paper, we explore the remaining redundancy of recent
learned compression algorithms. We have found accurate entropy models for rate
estimation largely affect the optimization of network parameters and thus
affect the rate-distortion performance. Therefore, in this paper, we propose to
use discretized Gaussian Mixture Likelihoods to parameterize the distributions
of latent codes, which can achieve a more accurate and flexible entropy model.
Besides, we take advantage of recent attention modules and incorporate them
into network architecture to enhance the performance. Experimental results
demonstrate our proposed method achieves a state-of-the-art performance
compared to existing learned compression methods on both Kodak and
high-resolution datasets. To our knowledge our approach is the first work to
achieve comparable performance with latest compression standard Versatile Video
Coding (VVC) regarding PSNR. More importantly, our approach generates more
visually pleasant results when optimized by MS-SSIM. This project page is at
this https URL
https://github.com/ZhengxueCheng/Learned-Image-Compression-with-GMM-and-Attention


  The use of deep learning in physical sciences has recently boosted the
ability of researchers to tackle physical systems where little or no analytical
insight is available. Recently, the Physics-Informed Neural Networks (PINNs)
have been introduced as one of the most promising tools to solve systems of
differential equations guided by some physically grounded constraints. In the
quantum realm, such approach paves the way to a novel approach to solve the
Schroedinger equation for non-integrable systems. By following an unsupervised
learning approach, we apply the PINNs to the anharmonic oscillator in which an
interaction term proportional to the fourth power of the position coordinate is
present. We compute the eigenenergies and the corresponding eigenfunctions
while varying the weight of the quartic interaction. We bridge our solutions to
the regime where both the perturbative and the strong coupling theory work,
including the pure quartic oscillator. We investigate systems with real and
imaginary frequency, laying the foundation for novel numerical methods to
tackle problems emerging in quantum field theory.


  This chapter will go through the important nuclear reactions in stellar
evolution and explosions, passing through the individual stellar burning stages
and also explosive burning conditions. To follow the changes in the composition
of nuclear abundances requires the knowledge of the relevant nuclear reaction
rates. For light nuclei (entering in early stellar burning stages) the
resonance density is generally quite low and the reactions are determined by
individual resonances, which are best obtained from experiments. For
intermediate mass and heavy nuclei the level density is typically sufficient to
apply statistical model approaches. For this reason, while we discuss all
burning stages and explosive burning, focusing on the reactions of importance,
we will for light nuclei refer to the chapters by M. Wiescher, deBoer &
Reifarth (Experimental Nuclear Astrophysics) and P. Descouvement (Theoretical
Studies of Low-Energy Nuclear Reactions), which display many examples,
experimental methods utilized, and theoretical approaches how to predict
nuclear reaction rates for light nuclei. For nuclei with sufficiently high
level densities we discuss statistical model methods used in present
predictions of nuclear reaction cross sections and thermonuclear rates across
the nuclear chart, including also the application to nuclei far from stability
and fission modes.


  The mechanical complexity of flapping wings, their unsteady aerodynamic flow,
and challenge of making measurements at the scale of a sub-gram flapping-wing
flying insect robot (FIR) make its behavior hard to predict. Knowing the
precise mapping from voltage input to torque output, however, can be used to
improve their mechanical and flight controller design. To address this
challenge, we created a sensitive force-torque sensor based on a flexured
gimbal that only requires a standard motion capture system or accelerometer for
readout. Our device precisely and accurately measures pitch and roll torques
simultaneously, as well as thrust, on a tethered flapping-wing FIR in response
to changing voltage input signals. With it, we were able to measure cross-axis
coupling of both torque and thrust input commands on a 180 mg FIR, the UW
Robofly. We validated these measurements using free-flight experiments. Our
results showed that roll and pitch have maximum cross-axis coupling errors of
8.58% and 17.24%, respectively, relative to the range of torque that is
possible. Similarly, varying the pitch and roll commands resulted in up to a
5.78% deviation from the commanded thrust, across the entire commanded torque
range. Our system, the first to measure two torque axes simultaneously, shows
that torque commands have a negligible cross-axis coupling on both torque and
thrust.


  We point out that the null results of the hadronic electric dipole moment
(EDM) searches constrain orbifold grand unified theories (GUTs), where the GUT
symmetry and supersymmetry (SUSY) are both broken by boundary conditions in
extra dimensions and it leads to rich fermion and sfermion flavor structures. A
marginal chromoelectric dipole moment (CEDM) of the up quark is induced by the
misalignment between the CP violating left- and right-handed up-type squark
mixings, in contrast to the conventional four-dimensional SUSY GUTs. The up
quark CEDM constraint is found to be as strong as those from charged lepton
flavor violation (LFV) searches. The interplay between future EDM and LFV
experiments will probe the structures of the GUTs and the SUSY breaking
mediation mechanism.


  In this paper we analyze a method of to approximation for the weak solutions
of the incompressible magnetohydrodynamic equations (MHD) in unbounded domains.
In particular we describe an hyperbolic version of the so called artificial
compressibility method adapted to the MHD system. By exploiting the wave
equation structure of the approximating system we achieve the convergence of
the approximating sequences by means of dispersive estimate of Strichartz type.
We prove that the soleinoidal component of the approximating velocity and
magnetic fields is relatively compact and converges strongly to a weak solution
of the MHD equation.


  We experimentally demonstrate a quantum key distribution (QKD) protocol using
photon pairs entangled in orbit angular momentum (OAM). In our protocol, Alice
and Bob modulate their OAM states on each entangled pair with spatial light
modulators (SLMs), respectively. Alice uses a fixed phase hologram in her SLM,
while Bob designs $N$ different suitable phase holograms and uses them to
represent his $N$-based information in his SLM. With coincidences, Alice can
fully retrieve the key stream sent by Bob without information reconciliation or
privacy amplification. We report the experiment results with N=3 and the sector
states with OAM eigenmodes l=1 and l=-1. Our experiment shows that the
coincidence rates are in relatively distinct value regions for the three
different key elements. Alice could recover fully Bob's keys by the protocol.
Finally, we discuss the security of the protocol both form the light way and
against the general attacks.


  Consider an n x n Hermitian random matrix with, above the diagonal,
independent entries with alpha-stable symmetric distribution and 0 < alpha < 2.
We establish new bounds on the rate of convergence of the empirical spectral
distribution of this random matrix as n goes to infinity. When 1 < alpha < 2 we
give vanishing bounds on the Lp-norm of the eigenvectors normalized to have
unit L2-norm goes to 0. On the contrary, when 0 < alpha < 2/3, we prove that
these eigenvectors are localized.


  The intersection pattern of the translates of the limit set of a quasi-convex
subgroup of a hyperbolic group can be coded in a natural incidence graph, which
suggests connections with the splittings of the ambient group. A similar
incidence graph exists for any subgroup of a group. We show that the
disconnectedness of this graph for codimension one subgroups leads to
splittings. We also reprove some results of Peter Kropholler on splittings of
groups over malnormal subgroups and variants of them.


  Construction of tight confidence regions and intervals is central to
statistical inference and decision making. This paper develops new theory
showing minimum average volume confidence regions for categorical data. More
precisely, consider an empirical distribution $\widehat{\boldsymbol{p}}$
generated from $n$ iid realizations of a random variable that takes one of $k$
possible values according to an unknown distribution $\boldsymbol{p}$. This is
analogous to a single draw from a multinomial distribution. A confidence region
is a subset of the probability simplex that depends on
$\widehat{\boldsymbol{p}}$ and contains the unknown $\boldsymbol{p}$ with a
specified confidence. This paper shows how one can construct minimum average
volume confidence regions, answering a long standing question. We also show the
optimality of the regions directly translates to optimal confidence intervals
of linear functionals such as the mean, implying sample complexity and regret
improvements for adaptive machine learning algorithms.


  We investigate, by numerical simulations on a lattice, the
$\theta$-dependence of 2$d$ $CP^{N-1}$ models for a range of $N$ going from 9
to 31, combining imaginary $\theta$ and simulated tempering techniques to
improve the signal-to-noise ratio and alleviate the critical slowing down of
the topological modes. We provide continuum extrapolations for the second and
fourth order coefficients in the Taylor expansion in $\theta$ of the vacuum
energy of the theory, parameterized in terms of the topological susceptibility
$\chi$ and of the so-called $b_2$ coefficient. Those are then compared with
available analytic predictions obtained within the $1/N$ expansion, pointing
out that higher order corrections might be relevant in the explored range of
$N$, and that this fact might be related to the non-analytic behavior expected
for $N = 2$. We also consider sixth-order corrections in the $\theta$
expansion, parameterized in terms of the so-called $b_4$ coefficient: in this
case our present statistical accuracy permits to have reliable non-zero
continuum estimations only for $N \leq 11$, while for larger values we can only
set upper bounds. The sign and values obtained for $b_4$ are compared to
large-$N$ predictions, as well as to results obtained for $SU(N_c)$ Yang-Mills
theories, for which a first numerical determination is provided in this study
for the case $N_c = 2$.


  In this article we give a full description of the dynamics of the flat
anisotropic (4+1)-dimensional cosmological model in the presence of both
Gauss-Bonnet and Einstein contributions. This is the first complete description
of this model with both terms taken into account. Our data is obtained using
the numerical analysis, though, we use analytics to explain some features of
the results obtained, and the same analytics could be applied to
higher-dimensional models in higher-order Lovelock corrections. Firstly, we
investigate the vacuum model and give a description of all regimes; then, we
add a matter source in the form of perfect fluid and study the influence the
matter exerts upon the dynamics. Thus, we give a description of matter regimes
as well. Additionally, we demonstrate that the presence of matter not only
"improves" the situation with a smooth transition between the standard
singularity and the Kasner regime, but also brings additional regimes and even
partially "erases" the boundaries between different regimes inside the same
triplet. Finally, we discuss the numerical and analytical results obtained and
their generalization to the higher-order models.


  Using group theoretical methods, we enumerate possible chiral representations
in which hadron interpolating currents can be classified. We give simple
examples of currents in each representation, some of which are well known. The
classification enables one to find relations among current vacuum correlators
in a chirally and/or axial U(1) symmetric phase of QCD in a straightforward
way. Besides recovering many well-known relations among two-point correlation
functions, a number of novel relations are found.


  Multi-view face synthesis from a single image is an ill-posed problem and
often suffers from serious appearance distortion. Producing photo-realistic and
identity preserving multi-view results is still a not well defined synthesis
problem. This paper proposes Load Balanced Generative Adversarial Networks
(LB-GAN) to precisely rotate the yaw angle of an input face image to any
specified angle. LB-GAN decomposes the challenging synthesis problem into two
well constrained subtasks that correspond to a face normalizer and a face
editor respectively. The normalizer first frontalizes an input image, and then
the editor rotates the frontalized image to a desired pose guided by a remote
code. In order to generate photo-realistic local details, the normalizer and
the editor are trained in a two-stage manner and regulated by a conditional
self-cycle loss and an attention based L2 loss. Exhaustive experiments on
controlled and uncontrolled environments demonstrate that the proposed method
not only improves the visual realism of multi-view synthetic images, but also
preserves identity information well.


  In recent years, science simulations have become popular among educators due
to their educational usefulness, availability, and potential for increasing the
students' knowledge on scientific topics. In this paper, we introduce the
implementation of a user-friendly simulation based on Easy Java/JavaScript
Simulations (EJS) to study the problem of damped oscillations in U-tubes.
Furthermore, we illustrate various advantages associated with the capabilities
of EJS in terms of design and usability in order to encourage teachers to use
it as an educational supplement to physics laboratories.


  As a model of composite materials, we choose a bundle of fibers with
stochastically distributed breaking thresholds for the individual fibers. the
fibers are assumed to share the load equally and to obey Hookean elasticity
right up to the breaking point. We study the evolution of the fiber breaking
rate at a constant load in excess of the critical load. The analysis shows that
the breaking rate reaches a minimum when the system is half-way from its
complete collapse.


  A simple extension of existing models for protein crystallisation is
described, in which salt ions and charge neutrality are explicitly
incorporated. This provides a straightforward explanation for the shape of
protein crystallisation boundaries, the associated scaling properties seen for
lysozyme, and can also explain much of the salt dependence of the second virial
coefficient. The analysis has wider implications for the use of pair potentials
to understand protein crystallisation.


  We study a natural continuous time version of excited random walks,
introduced by Norris, Rogers and Williams about twenty years ago. We obtain a
necessary and sufficient condition for recurrence and for positive speed. This
is analogous to results for excited (or cookie) random walks.


  In this paper we make explicit the constants of Habegger and Pazuki's work
from 2017 on bounding the discriminant of cyclic Galois CM fields corresponding
to genus 2 curves with CM by them and potentially good reduction outside a
predefined set of primes. We also simplify some of the arguments.


  We determine the order of magnitude of the variance of the Fibonacci
partition function. The answer is different to the most naive guess. The proof
involves a diophantine system and an inhomogeneous linear recurrence.


  Matrix decomposition is a very important mathematical tool in numerical
linear algebra for data processing. In this paper, we introduce a new
randomized matrix decomposition algorithm, which is called randomized
approximate SVD based on Qatar Riyal decomposition (RCSVD-QR). Our method
utilize random sampling and the OR decomposition to address a serious bottlenck
associated with classical SVD. RCSVD-QR gives satisfactory convergence speed as
well as accuracy as compared to those state-of-the-art algorithms. In addition,
we provides an estimate for the expected approximation error in Frobenius norm.
Numerical experiments verify these claims.


  We compare the semiclassical description of NEMS within and beyond the
adiabatic approximation. We consider a NEMS model which contains a single
phonon (oscillator) mode linearly coupled to an electronic few-level system in
contact with external particle reservoirs (leads). Using Feynman-Vernon
influence functional theory, we derive a Langevin equation for the oscillator
trajectory that is non-perturbative in the system-leads coupling. A stationary
electronic current through the system generates nontrivial dynamical behavior
of the oscillator, even in the adiabatic regime. The 'backaction' of the
oscillator onto the current is studied as well. For the two simplest cases of
one and two coupled electronic levels, we discuss the differences between the
adiabatic and the non-adiabatic regime of the oscillator dynamics.


  In this work it is proposed a transformation which is useful in order to
simplify non-polynomial potentials given in the form of an exponential. As an
application, it is shown that the quantum Liouville field theory may be mapped
into a field theory with a polynomial interaction between two scalar fields and
a massive vector field.


  We show that every cross ratio preserving homeomorphism between boundaries of
Hadamard manifolds extends to a continuous map, called circumcenter extension,
provided that the manifolds satisfy certain visibility conditions. We show that
this map is a rough isometry, whenever the manifolds admit cocompact group
actions by isometries and we improve the quasi-isometry constants provided by
Biswas in the case of CAT(-1)} spaces. Finally, we provide a sufficient
condition for this map to be an isometry in the case of Hadamard surfaces.


  The aim of this paper is to discuss in some detail the two different quantum
schemes for duopoly problems. We investigate under what conditions one of the
schemes is more reasonable that the other one. Using the Cournot's duopoly
example we show that the current quantum schemes require a slight refinement so
that they output the classical game in a particular case. Then we show how the
amendment changes the way of studying the quantum games with respect to Nash
equilibria. Finally, we define another scheme for the Cournot's duopoly in
terms of quantum computation.


  We prove that the validity of the recently proposed dressed, asymptotic Bethe
ansatz for the planar AdS/CFT system is indeed limited at weak coupling by
operator wrapping effects. This is done by comparing the Bethe ansatz
predictions for the four-loop anomalous dimension of finite-spin twist-two
operators to BFKL constraints from high-energy scattering amplitudes in N=4
gauge theory. We find disagreement, which means that the ansatz breaks down for
length-two operators at four-loop order. Our method supplies precision tools
for multiple all-loop tests of the veracity of any yet-to-be constructed set of
exact spectral equations. Finally we present a conjecture for the exact
four-loop anomalous dimension of the family of twist-two operators, which
includes the Konishi field.


  We study quantum equivalents of non-commutative operators in quantum
mechanics. Any matrix "$B$" satisfying the non-commuting relation $[A,B]\neq 0$
with "$A$", can be used via $B^{-1} AB$ to reproduce eigenvalues of "$A$". This
universality relation is also equally valid for any matrix in any branch of
physical or social science and also any operator involving co-ordinate$(x)$ or
momentum$(p)$. Pictorially this is represented in fig. 1. Many interesting
models including logarithmic potential have been considered.


  Motivated by the connection between gauge field topology and the axial
anomaly in fermion currents, I use the fourth power of the naive Dirac operator
to define a local lattice measure of topological charge. For smooth gauge
fields this reduces to the usual topological density. For typical gauge field
configurations in a numerical simulation, however, quantum fluctuations
dominate, and the sum of this density over the system does not generally give
an integer winding. On cooling with respect to the Wilson gauge action,
instanton like structures do emerge. As cooling proceeds, these objects tend
shrink and finally "fall through the lattice." Modifying the action can block
the shrinking at the expense of a loss of reflection positivity. The cooling
procedure is highly sensitive to the details of the initial steps, suggesting
that quantum fluctuations induce a small but fundamental ambiguity in the
definition of topological susceptibility.


  We study the exact square chromatic number of subcubic planar graphs. An
exact square coloring of a graph G is a vertex-coloring in which any two
vertices at distance exactly 2 receive distinct colors. The smallest number of
colors used in such a coloring of G is its exact square chromatic number,
denoted $\chi^{\sharp 2}(G)$. This notion is related to other types of
distance-based colorings, as well as to injective coloring. Indeed, for
triangle-free graphs, exact square coloring and injective coloring coincide. We
prove tight bounds on special subclasses of planar graphs: subcubic bipartite
planar graphs and subcubic K 4-minor-free graphs have exact square chromatic
number at most 4. We then turn our attention to the class of fullerene graphs,
which are cubic planar graphs with face sizes 5 and 6. We characterize
fullerene graphs with exact square chromatic number 3. Furthermore, supporting
a conjecture of Chen, Hahn, Raspaud and Wang (that all subcubic planar graphs
are injectively 5-colorable) we prove that any induced subgraph of a fullerene
graph has exact square chromatic number at most 5. This is done by first
proving that a minimum counterexample has to be on at most 80 vertices and then
computationally verifying the claim for all such graphs.


  Black holes are thought to describe the geometry of massive, dark compact
objects in the universe. To further support and quantify this long-held belief
requires knowledge of possible, if exotic alternatives. Here, we wish to
understand how compact can self-gravitating solutions be. We discuss theories
with a well-posed initial value problem, consisting in either a single
self-interacting scalar, vector or both. We focus on spherically symmetric
solutions, investigating the influence of self-interacting potentials into the
compactness of the solutions, in particular those that allow for flat-spacetime
solutions. We are able to connect such stars to hairy black hole solutions,
which emerge as a zero-mass black hole. We show that such stars can have light
rings, but their compactness is never parametrically close to that of black
holes. The challenge of finding black hole mimickers to investigate full
numerical-relativity binary setups remains open.


  We present the open-source tool T2, the first public release from the
TERMINATOR project. T2 has been extended over the past decade to support
automatic temporal-logic proving techniques and to handle a general class of
user-provided liveness and safety properties. Input can be provided in a native
format and in C, via the support of the LLVM compiler framework. We briefly
discuss T2's architecture, its underlying techniques, and conclude with an
experimental illustration of its competitiveness and directions for future
extensions.


  We performed temperature dependent transient photovoltage and photocurrent
measurements on poly(3-hexylthiophene):[6,6]-phenyl-C61 butyric acid
methylester bulk heterojuction solar cells. We found a strongly charge carrier
concentration and temperature dependent Langevin recombination prefactor. The
observed recombination mechanism is discussed in terms of bimolecular
recombination. The experimental results were compared with charge carrier
extraction by linearly increasing voltage (photo-CELIV) measurements done on
the same blend system. We explain the charge carrier dynamics, following an
apparent order larger than two, by dynamic trapping of charges in the tail
states of the gaussian density of states.


  Feed-forward multilayer neural networks implementing random input-output
mappings develop characteristic correlations between the activity of their
hidden nodes which are important for the understanding of the storage and
generalization performance of the network. It is shown how these correlations
can be calculated from the joint probability distribution of the aligning
fields at the hidden units for arbitrary decoder function between hidden layer
and output. Explicit results are given for the parity-, and-, and
committee-machines with arbitrary number of hidden nodes near saturation.


  Popularity bias in music recommendation systems -- where artists and tracks
with the highest listen counts are recommended more often -- can also propagate
biases along demographic and cultural axes. In this work, we identify these
biases in recommendations for artists from underrepresented cultural groups in
prototype-based matrix factorization methods. Unlike traditional matrix
factorization methods, prototype-based approaches are interpretable. This
allows us to directly link the observed bias in recommendations for minority
artists (the effect) to specific properties of the embedding space (the cause).
We mitigate popularity bias in music recommendation through capturing both
users' and songs' cultural nuances in the embedding space. To address these
challenges while maintaining recommendation quality, we propose two novel
enhancements to the embedding space: i) we propose an approach to filter-out
the irrelevant prototypes used to represent each user and item to improve
generalizability, and ii) we introduce regularization techniques to reinforce a
more uniform distribution of prototypes within the embedding space. Our results
demonstrate significant improvements in reducing popularity bias and enhancing
demographic and cultural fairness in music recommendations while achieving
competitive -- if not better -- overall performance.


  The aim of this study is to analyze the feedback process between the magnetic
turbulence and the pressure gradients in LHD inward-shifted configurations as
well as its role in the transition between the soft-hard MHD regimes for
instabilities driven by the mode $1/2$ in the middle plasma. In the present
paper we summarize the results of two simulations with different Lundquist
numbers, $S = 2.5 \times 10^5$ and $10^6$, assuming a plasma in the slow
reconnection regime. The results for the high Lundquist number simulation shows
that the magnetic turbulence and the pressure gradient in the middle plasma
region of LHD are below the critical value to drive the transition to the hard
MHD regime, therefore only relaxations in the soft MHD limit are triggered
($1/2$ sawtooth like events) [Phys. Plasmas 19, 082512 (2012)]. In the case of
the simulation with low Lundquist number, the system reaches the hard MHD limit
and a plasma collapse is observed.


  We show that the contributions to the Gutzwiller formula with observable
associated to the iterates of a given elliptic nondegenerate periodic
trajectory $\gamma$ and to certain families of observables localized near
$\gamma$ determine the quantum Hamiltonian in a formal neighborhood of the
trajectory $\gamma$, that is the full Taylor expansion of its total symbol near
$\gamma$. We also treat the "bottom of a well" case both for general and
Schr\"odinger operators.


  We report a detailed analysis of the coronal abundance of 4 stars with
varying levels of activity and with accurately known photospheric abundances.
The coronal abundance is determined here using a line flux analysis and a full
determination of the differential emission measure. Photospheric abundance
values are taken from literature works. Previous coronal abundance
determinations have generally been compared to solar photospheric abundances;
from this a number of general properties have been inferred, such as the
presence of a coronal metal depletion with an inverse First Ionization
Potential correlated with activity level. Here we show that, when coronal
abundances are compared with real photospheric values for the individual stars,
the resulting pattern can be very different. Also, we present evidence that, in
some cases, the coronal metal abundance may not be uniform in the corona; in
particular it can vary with the temperature of the emitting plasma.


  Consider a system of particles performing nearest neighbor random walks on
the lattice $\ZZ$ under hard--core interaction. The rate for a jump over a
given bond is direction--independent and the inverse of the jump rates are
i.i.d. random variables belonging to the domain of attraction of an
$\a$--stable law, $0<\a<1$. This exclusion process models conduction in
strongly disordered one-dimensional media. We prove that, when varying over the
disorder and for a suitable slowly varying function $L$, under the
super-diffusive time scaling $N^{1 + 1/\alpha}L(N)$, the density profile
evolves as the solution of the random equation $\partial_t \rho = \mf L_W
\rho$, where $\mf L_W$ is the generalized second-order differential operator
$\frac d{du} \frac d{dW}$ in which $W$ is a double sided $\a$--stable
subordinator. This result follows from a quenched hydrodynamic limit in the
case that the i.i.d. jump rates are replaced by a suitable array $\{\xi_{N,x} :
x\in\bb Z\}$ having same distribution and fulfilling an a.s. invariance
principle. We also prove a law of large numbers for a tagged particle.


  Training deep neural networks requires gradient estimation from data batches
to update parameters. Gradients per parameter are averaged over a set of data
and this has been presumed to be safe for privacy-preserving training in joint,
collaborative, and federated learning applications. Prior work only showed the
possibility of recovering input data given gradients under very restrictive
conditions - a single input point, or a network with no non-linearities, or a
small 32x32 px input batch. Therefore, averaging gradients over larger batches
was thought to be safe. In this work, we introduce GradInversion, using which
input images from a larger batch (8 - 48 images) can also be recovered for
large networks such as ResNets (50 layers), on complex datasets such as
ImageNet (1000 classes, 224x224 px). We formulate an optimization task that
converts random noise into natural images, matching gradients while
regularizing image fidelity. We also propose an algorithm for target class
label recovery given gradients. We further propose a group consistency
regularization framework, where multiple agents starting from different random
seeds work together to find an enhanced reconstruction of original data batch.
We show that gradients encode a surprisingly large amount of information, such
that all the individual images can be recovered with high fidelity via
GradInversion, even for complex datasets, deep networks, and large batch sizes.


  Training the state-of-the-art speech-to-text (STT) models in mobile devices
is challenging due to its limited resources relative to a server environment.
In addition, these models are trained on generic datasets that are not
exhaustive in capturing user-specific characteristics. Recently, on-device
personalization techniques have been making strides in mitigating the problem.
Although many current works have already explored the effectiveness of
on-device personalization, the majority of their findings are limited to
simulation settings or a specific smartphone. In this paper, we develop and
provide a detailed explanation of our framework to train end-to-end models in
mobile phones. To make it simple, we considered a model based on connectionist
temporal classification (CTC) loss. We evaluated the framework on various
mobile phones from different brands and reported the results. We provide enough
evidence that fine-tuning the models and choosing the right hyperparameter
values is a trade-off between the lowest WER achievable, training time
on-device, and memory consumption. Hence, this is vital for a successful
deployment of on-device training onto a resource-limited environment like
mobile phones. We use training sets from speakers with different accents and
record a 7.6% decrease in average word error rate (WER). We also report the
associated computational cost measurements with respect to time, memory usage,
and cpu utilization in mobile phones in real-time.


  A finite non-commutative geometry consists of a fuzzy space together with a
Dirac operator satisfying the axioms of a real spectral triple. This paper
addreses the question of how to extract information about these geometries from
the spectrum of the Dirac operator. Since the Dirac operator is a
finite-dimensional matrix, the usual asymptotics of the eigenvalues makes no
sense and is replaced by measurements of the spectrum at a finite energy scale.
The spectral dimension of the square of the Dirac operator is improved to
provide a new spectral measure of the dimension of a space called the spectral
variance. Similarly, the volume of a space can be computed from the spectrum
once the dimension is known. Two methods of doing this are investigated: the
well-known Dixmier trace and a recent improvement due to Abel Stern. Finally,
the distance between two geometries is investigated by comparing the spectral
zeta functions using the method of Cornelissen and Kontogeorgis. All of these
techniques are tested on the explicit examples of the fuzzy spheres and fuzzy
tori, which can be regarded as approximations of the usual Riemannian sphere
and flat tori. Then they are applied to characterise some random fuzzy spaces
using data generated by a Monte Carlo simulation.


  We introduce a meshfree collocation framework to model the phase change from
liquid to vapor at or above the boiling point. While typical vaporization or
boiling simulations focus on the vaporization from the bulk of the fluid, here
we include the possibility of vaporization from the free surface, when a moving
fluid comes into contact with a superheated surface. We present a continuum,
one-fluid approach in which the liquid and vapor phases are modeled with the
same constitutive equations, with different material properties. The novelty
here is a monolithic approach without explicit modeling of the interface
between the phases, neither in a sharp nor diffuse sense. Furthermore, no
interface boundary conditions or source terms are needed between the liquid and
vapor phases. Instead, the phase transition is modeled only using material
properties varying with temperature. Towards this end, we also present an
enrichment of strong form meshfree generalized finite difference methods (GFDM)
to accurately capture derivatives in the presence of jumps in density,
viscosity, and other physical properties. The numerical results show a good
agreement with experimental results, and highlight the ability of our proposed
framework to model phase changes with large jumps.


  One factor determining the reliability of measurements of electron
temperature using a Thomson scattering (TS) system is transmittance of the
optical bandpass filters in polychromators. We investigate the system
performance as a function of electron temperature to determine reliable range
of measurements for a given set of the optical bandpass filters. We show that
such a reliability, i.e., both bias and random errors, can be obtained by
building a forward model of the KSTAR TS system to generate synthetic TS data
with the prescribed electron temperature and density profiles. The prescribed
profiles are compared with the estimated ones to quantify both bias and random
errors.


  Conventional tracking paradigm takes in instantaneous measurements such as
range and bearing, and produces object tracks across time. In applications such
as autonomous driving, lidar measurements in the form of point clouds are
usually passed through a "virtual sensor" realized by a deep learning model, to
produce "measurements" such as bounding boxes, which are in turn ingested by a
tracking module to produce object tracks. Very often multiple lidar sweeps are
accumulated in a buffer to merge and become the input to the virtual sensor. We
argue in this paper that such an input already contains temporal information,
and therefore the virtual sensor output should also contain temporal
information, not just instantaneous values for the time corresponding to the
end of the buffer. In particular, we present the deep learning model called
MULti-Sweep PAired Detector (MULSPAD) that produces, for each detected object,
a pair of bounding boxes at both the end time and the beginning time of the
input buffer. This is achieved with fairly straightforward changes in commonly
used lidar detection models, and with only marginal extra processing, but the
resulting symmetry is satisfying. Such paired detections make it possible not
only to construct rudimentary trackers fairly easily, but also to construct
more sophisticated trackers that can exploit the extra information conveyed by
the pair and be robust to choices of motion models and object birth/death
models. We have conducted preliminary training and experimentation using Waymo
Open Dataset, which shows the efficacy of our proposed method.


  In this paper, we present a novel Secured Outsourced Content Based Image
Retrieval solution, which allows looking for similar images stored into the
cloud in a homomorphically encrypted form. Its originality is fourfold. In a
first time, it extracts from a Paillier encrypted image a wavelet based global
image signature. In second, this signature is extracted in an encrypted form
and gives no clues about the image content. In a third time, its calculation
does not require the cloud to communicate with a trusted third party as usually
proposed by other existing schemes. More clearly, all computations required in
order to look for similar images are conducted by the cloud only with no
extra-communications. To make possible such a computation, we propose a new
fast way to compare encrypted data, these ones being encrypted by the same
public key or not, and using a recursive relationship in-between Paillier
random values when computing the different resolution levels of the image
wavelet transform. Experiments conducted in two distinct frameworks: medical
image retrieval with as purpose diagnosis aid support, and face recognition for
user authentication; indicate that the proposed SOCBIR does not change image
retrieval performance.


  The widely used nuclear norm heuristic for rank minimization problems
introduces a regularization parameter which is difficult to tune. We have
recently proposed a method to approximate the regularization path, i.e., the
optimal solution as a function of the parameter, which requires solving the
problem only for a sparse set of points. In this paper, we extend the algorithm
to provide error bounds for the singular values of the approximation. We
exemplify the algorithms on large scale benchmark examples in model order
reduction. Here, the order of a dynamical system is reduced by means of
constrained minimization of the nuclear norm of a Hankel matrix.


  The MEGA experiment, which searched for the muon- and electron-number
violating decay \mu -> e + \gamma, is described. The spectrometer system, the
calibrations, the data taking procedures, the data analysis, and the
sensitivity of the experiment are discussed. The most stringent upper limit on
the branching ratio of \mu -> e + \gamma) < 1.2 x 10^{-11} was obtained.


  We analyze recent results concerning the hypothesis of a privileged direction
in the space-time that is made by considering a background of the Lorentz
symmetry violation determined by a fixed spacelike vector field and the
analysis of quantum effects of this background on the interaction of a
nonrelativistic electron with a nonuniform electric field produced by a uniform
electric charge distribution. We show that the conclusions derived by the
authors are an artifact of the truncation of the Frobenius series by means of
the tree-term recurrence relation for the expansion coefficients. Thus, the
existence of allowed angular frequencies stemming from this procedure is
meaningless and unphysical.


  Contradictory results on the evolution of lenticular galaxies (S0s) at
intermediate redshift have been recently published. A careful analysis of the
used methodology shows that in order to gain insights on the evolution of the
morphological types it is necessary: (1) to use quantitative morphological
types, (2) to propagate morphological errors in the quantity used to measure
the evolution of the S0s and (3) to adopt the same morphological classes at
high as at low redshift, testing the correspondence with standard types. Some
published analysis fail to satisfy at least one of the above three conditions,
thus undermining the claim for a young age of S0s of intermediate redshift
clusters.


  Slow fluctuations of a qubit frequency are one of the major problems faced by
quantum computers. To understand their origin it is necessary to go beyond the
analysis of their spectra. We show that characteristic features of the
fluctuations can be revealed using comparatively short sequences of
periodically repeated Ramsey measurements, with the sequence duration smaller
than needed for the noise to approach the ergodic limit. The outcomes
distribution and its dependence on the sequence duration are sensitive to the
nature of noise. The time needed for quantum measurements to display
quasi-ergodic behavior can strongly depend on the measurement parameters.


  In this thesis I review cosmological and astrophysical exact models for
Randall-Sundrum-type braneworlds and their physical implications. I present new
insights and show their analogies with quantum theories via the holographic
idea. In astrophysics I study the two fundamental models of a spherically
symmetric static star and spherically symmetric collapsing objects. I show how
matching for the pressure of a static star encodes braneworld effects. In
addition I study the problem of the vacuum exterior conjecturing a uniqueness
theorem. Furthermore I show that a collapsing dust cloud in the braneworld has
a non-static exterior, in contrast to the General Relativistic case. This
non-static behaviour is linked to the presence of a "surplus potential energy"
that must be released, producing a non-zero flux of energy. Via holography this
can be connected with the Hawking process, giving an indirect measure of the
brane tension. In cosmology I investigate the generalization of the
Randall-Sundrum-type model obtained by introducing the Gauss-Bonnet combination
into the action. I elucidate the junction conditions necessary to study the
brane model and obtain the cosmological dynamics, showing that, even in the
thin shell limit for the brane, the Gauss-Bonnet term implies a non-trivial
internal structure for the matter and geometry distributions. Independently of
the gravitational theory used, I show how to derive the modified Friedman
equation and how it is related to the black hole solution of the theory. Via
holography I also show how to interpret quantum mechanically the mass of this
black hole from a four-dimensional perspective in the simplest
Randall-Sundrum-type scenario.


  In this paper we consider positive supersolutions of the nonlinear elliptic
equation \[- \Delta u = \rho(x) f(u)|\nabla u|^p, \qquad \hfill \mbox{ in }
\Omega,\] where $0\le p<1$, $ \Omega$ is an arbitrary domain (bounded or
unbounded) in $ \IR^N$ ($N\ge 2$), $f: [0,a_{f}) \rightarrow \Bbb{R}_{+}$ $(0 <
a_{f} \leqslant +\infty)$ is a non-decreasing continuous function and $\rho:
\Omega \rightarrow \IR$ is a positive function. Using the maximum principle we
give explicit estimates on positive supersolutions $u$ at each point
$x\in\Omega$ where $\nabla u\not\equiv0$ in a neighborhood of $x$. As
consequences, we discuss the dead core set of supersolutions on bounded
domains, and also obtain Liouville type results in unbounded domains $\Omega$
with the property that $\sup_{x\in\Omega}dist (x,\partial\Omega)=\infty$.


  A Rapid evolution of mobile technologies has led to the development of more
sophisticated mobile devices with better storage, processing and transmission
power. These factors enable support to many types of application but also give
rise to a necessity to find a model of service development. Actually, SOA
(Service Oriented Architecture) is a good option to support application
development. This paper presents a framework that allows the development of SOA
based application in mobile environment. The objective of the framework is to
give developers with tools for provision of services in this environment with
the necessary security characteristics.


  Compiling quantum circuits lends itself to an elegant formulation in the
language of rewriting systems on non commutative polynomial algebras $\mathbb
Q\langle X\rangle$. The alphabet $X$ is the set of the allowed hardware 2-qubit
gates. The set of gates that we wish to implement from $X$ are elements of a
free monoid $X^*$ (obtained by concatenating the letters of $X$). In this
setting, compiling an idealized gate is equivalent to computing its unique
normal form with respect to the rewriting system $\mathcal R\subset \mathbb
Q\langle X\rangle$ that encodes the hardware constraints and capabilities. This
system $\mathcal R$ is generated using two different mechanisms: 1) using the
Knuth-Bendix completion algorithm on the algebra $\mathbb Q\langle X\rangle$,
and 2) using the Buchberger algorithm on the shuffle algebra $\mathbb Q[L]$
where $L$ is the set of Lyndon words on $X$.


  We study the emergence of color superconductivity in the theory of the strong
interaction at supranuclear densities. To this end, we follow the
renormalization group (RG) flow of dense strong-interaction matter with two
massless quark flavors from the fundamental quark and gluon degrees of freedom
at high energies down to the non-perturbative low-energy regime which is found
to be governed by the dynamical formation of diquark states. With the strong
coupling at the initial RG scale as the only input parameter, we compute the
(chirally symmetric) scalar diquark condensate and analyze its scaling behavior
over a wide range of the quark chemical potential. Approximations entering our
computations are critically assessed. Since our approach naturally allows us to
study the scale dependence of couplings, we also monitor the strength of
couplings appearing in low-energy models of dense strong-interaction matter.
The observed dependence of these couplings on the quark chemical potential may
help to amend model studies in the future. Finally, we estimate the speed of
sound of dense QCD matter. Our results indicate that the speed of sound exceeds
the value of the noninteracting quark gas at high densities and even increases
as the density is decreased, across a wide range, suggesting the existence of a
maximum at supranuclear densities.


  We investigate the one-dimensional Schr\"{o}dinger equation for a harmonic
oscillator with a finite jump $a$ at the origin. The solution is constructed by
employing the ordinary matching-of-wavefunctions technique. For the special
choices of $a$, $a=4\ell$ ($\ell=1,2,\ldots$), the wavefunctions can be
expressed by the Hermite polynomials. Moreover, we explore isospectral
deformations of the potential via the Darboux transformation. In this context,
infinitely many isospectral Hamiltonians to the ordinary harmonic oscillator
are obtained.


  A path-integral approach is used to study the spectral properties of the
generators of the SO(2,1) symmetry of conformal quantum mechanics (CQM). In
particular, we consider the CQM version that corresponds to the weak-coupling
regime of the inverse square potential. We develop a general framework to
characterize a generic symmetry generator $G$ (linear combinations of the
Hamiltonian $H$, special conformal operator $K$, and dilation operator $D$),
from which the path-integral propagators follow, leading to a complete spectral
decomposition. This is done for the three classes of operators: elliptic,
parabolic, and hyperbolic. We also highlight novel results for the hyperbolic
operators, with a continuous spectrum, and their quantum-mechanical
interpretation. The spectral technique developed for the eigensystem of
continuous-spectrum operators can be generalized to other operator problems.


  In this paper, we revisit McFadden (1978)'s correction factor for sampling of
alternatives in multinomial logit (MNL) and mixed multinomial logit (MMNL)
models. McFadden (1978) proved that consistent parameter estimates are obtained
when estimating MNL models using a sampled subset of alternatives, including
the chosen alternative, in combination with a correction factor. We decompose
this correction factor into i) a correction for overestimating the MNL choice
probability due to using a smaller subset of alternatives, and ii) a correction
for which a subset of alternatives is contrasted through utility differences
and thereby the extent to which we learn about the parameters of interest in
MNL. Keane and Wasi (2016) proved that the overall expected positive
information divergence - comprising the above two elements - is minimised
between the true and sampled likelihood when applying a sampling protocol
satisfying uniform conditioning. We generalise their result to the case of
positive conditioning and show that whilst McFadden (1978)'s correction factor
may not minimise the overall expected information divergence, it does minimise
the expected information loss with respect to the parameters of interest. We
apply this result in the context of Bayesian analysis and show that McFadden
(1978)'s correction factor minimises the expected information loss regarding
the parameters of interest across the entire posterior density irrespective of
sample size. In other words, McFadden (1978)'s correction factor has desirable
small and large sample properties. We also show that our results for Bayesian
MNL models transfer to MMNL and that only McFadden (1978) correction factor is
sufficient to minimise the expected information loss in the parameters of
interest. Monte Carlo simulations illustrate the successful application of
sampling of alternatives in Bayesian MMNL models.


  Nowadays, social networks became essential in information exchange between
individuals. Indeed, as users of these networks, we can send messages to other
people according to the links connecting us. Moreover, given the large volume
of exchanged messages, detecting the true nature of the received message
becomes a challenge. For this purpose, it is interesting to consider this new
tendency with reasoning under uncertainty by using the theory of belief
functions. In this paper, we tried to model a social network as being a network
of fusion of information and determine the true nature of the received message
in a well-defined node by proposing a new model: the belief social network.


  We present Herschel PACS spectroscopy of the [O III] 88.4um fine-structure
line in the nearby WC8+O binary system gamma Vel to determine its oxygen
abundance. The critical density of this line corresponds to several 10^5 R*
such that it is spatially extended in PACS observations at the 336 pc distance
to gamma Vel. Two approaches are used, the first involving a detailed stellar
atmosphere analysis of gamma Vel using CMFGEN, extending to Ne ~ 10^0 cm^-3 in
order to fully sample the line formation region of [O III] 88.4um. The second
approach involves the analytical model introduced by Barlow et al. and revised
by Dessart et al, additionally exploiting ISO LWS spectroscopy of [O III]
51.8um. We obtain higher luminosities for the WR and O components of gamma Vel
with respect to De Marco et al, log L/L_sun = 5.31 and 5.56, respectively, due
to the revised (higher) interferometric distance. We obtain an oxygen mass
fraction of X_O = 1.0+/- 0.3% for an outer wind volume filling factor of f =
0.5+/-0.25, favouring either standard or slightly reduced Kunz et al. rates for
the ^12C(alpha, gamma)^16O reaction from comparison with BPASS binary
population synthesis models. We also revisit neon and sulphur abundances in the
outer wind of gamma Vel from ISO SWS spectroscopy of [S IV] 10.5um [Ne II]
12.8um and [Ne III] 15.5um. The inferred neon abundance X_Ne = 2.0-0.6+0.4%, is
in excellent agreement with BPASS predictions, while the.sulphur abundance of
X_S = 0.04 +/- 0.01% agrees with the solar abundance, as expected for
unprocessed elements.


  The scenario that some first-order phase transitions may have taken place in
the early Universe offers us one of the most intriguing and fascinating
questions in cosmology. Indeed, the role played by the latent "heat" or energy
released in the phase transition is highly nontrivial and may lead to some
surprising, important results. In this paper, we take the wisdom that the
cosmological QCD phase transition, which happened at a time between 10^(-5) sec
and 10^(-4) sec or at the temperature of about 150 MeV and accounts for
confinement of quarks and gluons to within hadrons, would be of first order. To
get the essence out of the scenario, it is sufficient to approximate the true
QCD vacuum as one of degenerate theta-vacua and when necessary we try to model
it effectively via a complex scalar field with spontaneous symmetry breaking.
We examine how and when "pasted" or "patched" domain walls are formed, how long
such walls evolve in the long run, and we believe that the significant portion
of dark matter could be accounted for in terms of such domain-wall structure
and its remnants. Of course, the cosmological QCD phase transition happened in
the way such that the false vacua associated with baryons and many other
color-singlet objects did not disappear (that is, using the bag-model language,
there are bags of radius 1.0 fermi for the baryons) - but the amount of the
energy remained in the false vacua is negligible. The latent energy released
due to the conversion of the false vacua to the true vacua, in the form of
"pasted" or "patched" domain walls in the short run and their numerous evolved
objects, should make the concept of the "radiation-dominated" epoch, or of the
"matter-dominated" epoch to be re-examined.


  Context. The high intensities and narrow bandwidths exhibited by some
astronomical masers make them ideal tools for studying star-forming giant
molecular clouds. The water maser transition $J_{K_{-1}K_{1}}=5_{32}-4_{41}$ at
620.701 GHz can only be observed from above Earth's strongly absorbing
atmosphere; its emission has recently been detected from space. Aims. We sought
to further characterize the star-forming environment of Orion KL by
investigating the linear polarisation of a source emitting a narrow 620.701 GHz
maser feature with the heterodyne spectrometer HIFI on board the Herschel Space
Observatory. Methods. High-resolution spectral datasets were collected over a
thirteen month period beginning in 2011 March, to establish not only the linear
polarisation but also the temporal variability of the source. Results. Within a
$3\sigma$ uncertainty, no polarisation was detected to an upper limit of
approximately 2%. These results are compared with coeval linear polarisation
measurements of the 22.235 GHz $J_{K_{-1}K_{1}}=6_{16}-5_{23}$ maser line from
the Effelsberg 100-m radio telescope, typically a much stronger maser
transition. Although strongly polarised emission is observed for one component
of the 22.235 GHz maser at 7.2 km s$^{-1}$, a weaker component at the same
velocity as the 620.701 GHz maser at 11.7 km s$^{-1}$ is much less polarised.


  The possible association of the blazar TXS 0506+056 with a high-energy
neutrino detected by IceCube holds the tantalizing potential to answer three
astrophysical questions: 1. Where do high-energy neutrinos originate? 2. Where
are cosmic rays produced and accelerated? 3. What radiation mechanisms produce
the high-energy {\gamma}-rays in blazars? The MeV gamma-ray band holds the key
to these questions, because it is an excellent proxy for photo-hadronic
processes in blazar jets, which also produce neutrino counterparts. Variability
in MeV gamma-rays sheds light on the physical conditions and mechanisms that
take place in the particle acceleration sites in blazar jets. In addition,
hadronic blazar models also predict a high level of polarization fraction in
the MeV band, which can unambiguously distinguish the radiation mechanism.
Future MeV missions with a large field of view, high sensitivity, and
polarization capabilities will play a central role in multi-messenger
astronomy, since pointed, high-resolution telescopes will follow neutrino
alerts only when triggered by an all-sky instrument.


  The paper revisits the performance evaluation of caching in a Named Data
Networking (NDN) router where the content store (CS) is supplemented by a
pending interest table (PIT). The PIT aggregates requests for a given content
that arrive within the download delay and thus brings an additional reduction
in upstream bandwidth usage beyond that due to CS hits. We extend prior work on
caching with non-zero download delay (non-ZDD) by proposing a novel
mathematical framework that is more easily applicable to general traffic models
and by considering alternative cache insertion policies. Specifically we
evaluate the use of an LRU filter to improve CS hit rate performance in this
non-ZDD context. We also consider the impact of time locality in demand due to
finite content lifetimes. The models are used to quantify the impact of the PIT
on upstream bandwidth reduction, demonstrating notably that this is significant
only for relatively small content catalogues or high average request rate per
content. We further explore how the effectiveness of the filter with finite
content lifetimes depends on catalogue size and traffic intensity.


  The stable systolic category of a closed manifold M indicates the complexity
in the sense of volume. This is a homotopy invariant, even though it is defined
by some relations between homological volumes on M. We show an equality of the
stable systolic category and the real cup-length for the product of arbitrary
finite dimensional real homology spheres. Also we prove the invariance of the
stable systolic category under the rational equivalences for orientable
0-universal manifolds.


  Modern social networks have become sources for vast quantities of data.
Having access to such big data can be very useful for various researchers and
data scientists. In this paper we describe Loklak, an open source distributed
peer to peer crawler and scraper for supporting such research on platforms like
Twitter, Weibo and other social networks. Social networks such as Twitter and
Weibo pose various limitations to the user on the rate at which one could
freely collect such data for research. Our crawler enables researchers to
continuously collect data while overcoming the barriers of authentication and
rate limits imposed to provide a repository of open data as a service.


  A Google search for a person's name, such as "Trevon Jones", may yield a
personalized ad for public records about Trevon that may be neutral, such as
"Looking for Trevon Jones?", or may be suggestive of an arrest record, such as
"Trevon Jones, Arrested?". This writing investigates the delivery of these
kinds of ads by Google AdSense using a sample of racially associated names and
finds statistically significant discrimination in ad delivery based on searches
of 2184 racially associated personal names across two websites. First names,
assigned at birth to more black or white babies, are found predictive of race
(88% black, 96% white), and those assigned primarily to black babies, such as
DeShawn, Darnell and Jermaine, generated ads suggestive of an arrest in 81 to
86 percent of name searches on one website and 92 to 95 percent on the other,
while those assigned at birth primarily to whites, such as Geoffrey, Jill and
Emma, generated more neutral copy: the word "arrest" appeared in 23 to 29
percent of name searches on one site and 0 to 60 percent on the other. On the
more ad trafficked website, a black-identifying name was 25% more likely to get
an ad suggestive of an arrest record. A few names did not follow these
patterns. All ads return results for actual individuals and ads appear
regardless of whether the name has an arrest record in the company's database.
The company maintains Google received the same ad text for groups of last names
(not first names), raising questions as to whether Google's technology exposes
racial bias.


  We show that the method of partial covariance is a very efficient way to
introduce constraints (such as the centrality selection) in data analysis in
ultra-relativistic nuclear collisions. The technique eliminates spurious
event-by-event fluctuations of physical quantities due to fluctuations of
control variables. Moreover, in the commonly used superposition approach to
particle production the method can be used to impose constraints on the initial
sources rather than on the finally produced particles, thus separating out the
trivial fluctuations from statistical hadronization or emission from sources
and focusing strictly on the initial-state physics. As illustration, we use
simulated data from hydrodynamics started on the wounded-quark event-by-event
initial conditions, followed with statistical hadronization, to show the
practicality of the approach in analyzing the forward-backward multiplicity
fluctuations. We mention generalizations to the case with several constraints
and other observables, such as the transverse momentum or eccentricity
correlations.


  In this paper we propose a fusion approach to continuous emotion recognition
that combines visual and auditory modalities in their representation spaces to
predict the arousal and valence levels. The proposed approach employs a
pre-trained convolution neural network and transfer learning to extract
features from video frames that capture the emotional content. For the auditory
content, a minimalistic set of parameters such as prosodic, excitation, vocal
tract, and spectral descriptors are used as features. The fusion of these two
modalities is carried out at a feature level, before training a single support
vector regressor (SVR) or at a prediction level, after training one SVR for
each modality. The proposed approach also includes preprocessing and
post-processing techniques which contribute favorably to improving the
concordance correlation coefficient (CCC). Experimental results for predicting
spontaneous and natural emotions on the RECOLA dataset have shown that the
proposed approach takes advantage of the complementary information of visual
and auditory modalities and provides CCCs of 0.749 and 0.565 for arousal and
valence, respectively.


  We study multi-field tunneling using exact solutions for additive potentials.
We introduce a binomial potential with non-integer powers that could be
considered a generalization of the $4D$ Fubini instanton potential. Using
scaling arguments, we show that for multi-field potentials taller and wider
barriers may still lead to a smaller bounce action.


  The evolutionary Prisoner's Dilemma Game (PDG) and the Snowdrift Game (SG)
with preferential learning mechanism are studied in the Barab\'asi-Albert
network. Simulation results demonstrate that the preferential learning of
individuals remarkably promotes the cooperative behavior for both two games
over a wide range of payoffs. To understand the effect of preferential learning
on the evolution of the systems, we investigate the time series of the
cooperator density for different preferential strength and payoffs. It is found
that in some specific cases two games both show the $1/f$-scaling behaviors,
which indicate the existence of long range correlation. We also figure out that
when the large degree nodes have high probability to be selected, the PDG
displays a punctuated equilibrium-type behavior. On the contrary, the SG
exhibits a sudden increase feature. These temporary instable behaviors are
ascribed to the strategy shift of the large degree nodes.


  The inducibility of a graph represents its maximum density as an induced
subgraph over all possible sequences of graphs of size growing to infinity.
This invariant of graphs has been extensively studied since its introduction in
$1975$ by Pippenger and Golumbic. In $2017$, Czabarka, Sz\'ekely and Wagner
extended this notion to leaf-labeled rooted binary trees, which are objects
widely studied in the field of phylogenetics. They obtain the first results and
bounds for the densities and inducibilities of such trees. Following up on
their work, we apply Razborov's flag algebra theory to this setting,
introducing the flag algebra of rooted leaf-labeled binary trees. This
framework allows us to use polynomial optimization methods, based on
semidefinite programming, to efficiently obtain new upper bounds for the
inducibility of trees and to improve existing ones. Additionally, we obtain the
first outer approximations of profiles of trees, which represent all possible
simultaneous densities of a pair of trees. Finally, we are able to prove the
non-convexity of some of these profiles.


  We study the statistics of first passage times (FPTs) of trajectory
observables in both classical and quantum Markov processes. We consider
specifically the FPTs of counting observables, that is, the times to reach a
certain threshold of a trajectory quantity which takes values in the positive
integers and is non-decreasing in time. For classical continuous-time Markov
chains we rigorously prove: (i) a large deviation principle (LDP) for FPTs,
whose corollary is a strong law of large numbers; (ii) a concentration
inequality for the FPT of the dynamical activity, which provides an upper bound
to the probability of its fluctuations to all orders; and (iii) an upper bound
to the probability of the tails for the FPT of an arbitrary counting
observable. For quantum Markov processes we rigorously prove: (iv) the quantum
version of the LDP, and subsequent strong law of large numbers, for the FPTs of
generic counts of quantum jumps; (v) a concentration bound for the the FPT of
total number of quantum jumps, which provides an upper bound to the probability
of its fluctuations to all orders, together with a similar bound for the
sub-class of quantum reset processes which requires less strict irreducibility
conditions; and (vi) a tail bound for the FPT of arbitrary counts. Our results
allow to extend to FPTs the so-called "inverse thermodynamic uncertainty
relations" that upper bound the size of fluctuations in time-integrated
quantities. We illustrate our results with simple examples.


  By far, the fractional derivative model is mainly related to the modelling of
complicated solid viscoelastic material. In this study, we try to build the
fractional derivative PDE model for broadband ultrasound propagation through
human tissues.


  In this paper we prove a Large Deviation Principle for the sequence of
symmetrised empirical measures $\frac{1}{n} \sum_{i=1}^{n}
\delta_{(X^n_i,X^n_{\sigma_n(i)})}$ where $\sigma_n$ is a random permutation
and $((X_i^n)_{1 \leq i \leq n})_{n \geq 1}$ is a triangular array of random
variables with suitable properties. As an application we show how this result
allows to improve the Large Deviation Principles for symmetrised
initial-terminal conditions bridge processes recently established by Adams,
Dorlas and K\"{o}nig.


  Parton energy loss in Au+Au collisions at RHIC energies is studied by
numerically solving the relativistic Boltzmann equation for the partons
including $2 \leftrightarrow 2$ and $2 \to 2 + final state radiation$ collision
processes. Final particle spectra are obtained using two hadronization models;
the Lund string fragmentation and independent fragmentation models. Recent,
preliminary $\pi^0$ transverse momentum distributions from central Au+Au
collisions at RHIC are reproduced using gluon-gluon scattering cross sections
of 5-12 mb, depending upon the hadronization model. Comparisons with the HIJING
jet quenching algorithm are made.


  We study the production of photons through the non-equilibrium relaxation of
a disoriented chiral condensate. We propose that to search for non-equilibrium
photons in the direct photon measurements of heavy-ion collisions can be a
potential test of the formation of disoriented chiral condensates.


  Clusters of galaxies as the largest clearly defined objects in our Universe
are ideal laboratories to study the distribution of the most abundant chemical
elements heavier than hydrogen and helium and the history of their production.
The cluster environment allows us to study the element abundances not only
inside the galaxies, but also in the intergalactic space, the intracluster
medium. Since the intracluster medium is heated to temperatures of several ten
Million degrees, we can study the chemical composition of this medium through
X-ray spectroscopy. Up to 13 heavy elements have been detected by X-ray
spectroscopy so far. The element most easily detected in the X-ray spectra is
iron. In massive galaxy clusters we find a larger mass of heavy elements in the
intracluster medium than in the galaxies. The consideration of the intracluster
medium is therefore vital for an understanding of the complete history of
nucleosynthesis of the heavy elements. The observed abundances for all elements
heavier than nitrogen can roughly be modeled by using two types of sources:
core collapse supernovae and supernovae type Ia. So called cool-core galaxy
clusters show a larger heavy element abundance in the cluster center which
seems to be enriched primarily by products of supernovae of type Ia. The
evidence for observations of an evolution of the heavy element abundance with
redshift has still a moderate significance.


  In this paper, we exhibit strongly singular maximal abelian subalgebras
living inside certain k-folded tensors of von Neumann group factors. The two
classes of groups under consideration are the free groups of rank greater than
2 and the free product of m>2 groups, all finite and having the same order p>2
(m>p-1). We prove actually more, namely that the unique trace preserving
conditional expectations from these group factors onto their Laplacian
subalgebras are asymptotic homomorphisms, which in turn implies that the
subalgebras are strongly singular masas.


  In this paper, we propose new efficient algorithms to verify the null space
condition in compressed sensing (CS). Given an $(n-m) \times n$ ($m>0$) CS
matrix $A$ and a positive $k$, we are interested in computing $\displaystyle
\alpha_k = \max_{\{z: Az=0,z\neq 0\}}\max_{\{K: |K|\leq k\}}$ ${\|z_K
\|_{1}}{\|z\|_{1}}$, where $K$ represents subsets of $\{1,2,...,n\}$, and $|K|$
is the cardinality of $K$. In particular, we are interested in finding the
maximum $k$ such that $\alpha_k < {1}{2}$. However, computing $\alpha_k$ is
known to be extremely challenging. In this paper, we first propose a series of
new polynomial-time algorithms to compute upper bounds on $\alpha_k$. Based on
these new polynomial-time algorithms, we further design a new sandwiching
algorithm, to compute the \emph{exact} $\alpha_k$ with greatly reduced
complexity. When needed, this new sandwiching algorithm also achieves a smooth
tradeoff between computational complexity and result accuracy. Empirical
results show the performance improvements of our algorithm over existing known
methods; and our algorithm outputs precise values of $\alpha_k$, with much
lower complexity than exhaustive search.


  Integer octagonal constraints (a.k.a. ``Unit Two Variables Per Inequality''
or ``UTVPI integer constraints'') constitute an interesting class of
constraints for the representation and solution of integer problems in the
fields of constraint programming and formal analysis and verification of
software and hardware systems, since they couple algorithms having polynomial
complexity with a relatively good expressive power. The main algorithms
required for the manipulation of such constraints are the satisfiability check
and the computation of the inferential closure of a set of constraints. The
latter is called `tight' closure to mark the difference with the (incomplete)
closure algorithm that does not exploit the integrality of the variables. In
this paper we present and fully justify an O(n^3) algorithm to compute the
tight closure of a set of UTVPI integer constraints.


  With advances in neural language models, the focus of linguistic
steganography has shifted from edit-based approaches to generation-based ones.
While the latter's payload capacity is impressive, generating genuine-looking
texts remains challenging. In this paper, we revisit edit-based linguistic
steganography, with the idea that a masked language model offers an
off-the-shelf solution. The proposed method eliminates painstaking rule
construction and has a high payload capacity for an edit-based model. It is
also shown to be more secure against automatic detection than a
generation-based method while offering better control of the security/payload
capacity trade-off.


  We give a distribution-dependent concentration inequality for functions of
independent variables. The result extends Bernstein's inequality from sums to
more general functions, whose variation in any argument does not depend too
much on the other arguments. Applications sharpen existing bounds for
U-statistics and the generalization error of regularized least squares.


  Infinite dimensional moment problems have a long history in diverse applied
areas dealing with the analysis of complex systems but progress is hindered by
the lack of a general understanding of the mathematical structure behind them.
Therefore, such problems have recently got great attention in real algebraic
geometry also because of their deep connection to the finite dimensional case.
In particular, our most recent collaboration with Murray Marshall and Mehdi
Ghasemi about the infinite dimensional moment problem on symmetric algebras of
locally convex spaces revealed intriguing questions and relations between real
algebraic geometry, functional and harmonic analysis. Motivated by this
promising interaction, the principal goal of this paper is to identify the main
current challenges in the theory of the infinite dimensional moment problem and
to highlight their impact in applied areas. The last advances achieved in this
emerging field and briefly reviewed throughout this paper led us to several
open questions which we outline here.


  We study the muon anomalous magnetic moment $(g-2)_{\mu}$ in the context of
the reduced minimal 3-3-1 model recently proposed in the literature. In
particular, its spectrum contains a doubly charged scalar ($H^{\pm \pm}$) and
gauge boson ($U^{\pm \pm}$), new singly charged vectors ($V^{\pm}$) and a
$Z^{\prime}$ boson, each of which might give a sizeable contribution to the
$(g-2)_{\mu}$. We compute the 1-loop contributions from all these new particles
to the $(g-2)_{\mu}$. We conclude that the doubly charged vector boson provides
the dominant contribution, and by comparing our results with the experimental
constraints we derive an expected value for the scale of $SU(3)_L\otimes
U(1)_N$ symmetry breaking $v_{\chi} \sim 2$ TeV. We also note that, if the
discrepancy in the anomalous moment is resolved in the future without this
model then the constraints will tighten to requiring $v_\chi > 2.7$ TeV with
current precision, and will entirely rule out the model if the expected
precision is achieved by the future experiment at Fermilab.


  Two-dimensional structures that exhibit intriguing magnetic phenomena such as
perpendicular magnetic anisotropy and switchable magnetization are of great
interests in spintronics research. Herein, the density-functional theory
studies reveal the critical impacts of strain and external gating on
vacancy-induced magnetism and its spin direction in a graphene-like single
layer of zinc oxide (ZnO). In contrast to the pristine and defective ZnO with
an O-vacancy, the presence of a Zn-vacancy induces significant magnetic moments
to its first neighboring O and Zn atoms due to the charge deficit. We further
predict that the direction of magnetization easy axis reverses from an in-plane
to perpendicular orientation under a practically achieved biaxial compressive
strain of $\sim$1--2\% or applying an electric-field by means of the charge
density modulation. This magnetization reversal is driven by the strain- and
electric-field-induced changes in the spin-orbit coupled \emph{d} states of the
first-neighbor Zn atom to the Zn-vacancy. These findings open interesting
prospects for exploiting strain and electric-field engineering to manipulate
magnetism and magnetization orientation of two-dimensional materials.