  If C and D are varieties of algebras in the sense of general algebra, then by
a representable functor C --> D we understand a functor which, when composed
with the forgetful functor D --> Set, gives a representable functor in the
classical sense; Freyd showed that these functors are determined by D-coalgebra
objects of C. Let Rep(C,D) denote the category of all such functors, a full
subcategory of Cat(C,D), opposite to the category of D-coalgebras in C.
  It is proved that Rep(C,D) has small colimits, and in certain situations,
explicit constructions for the representing coalgebras are obtained.
  In particular, Rep(C,D) always has an initial object. This is shown to be
"trivial" unless C and D either both have_no_ zeroary operations, or both have
_more_than_one_ derived zeroary operation. In those two cases, the functors in
question may have surprisingly opulent structures.
  It is also shown that every set-valued representable functor on C admits a
universal morphism to a D-valued representable functor.
  Several examples are worked out in detail, and areas for further
investigation noted.


  Spin transfer driven excitations in magnetic nanostructures are characterized
by a relatively large microwave emission linewidth (10 -100 MHz). Here we
investigate the role of thermal fluctuations as well as of the non-linear
amplitude-phase coupling parameter and the amplitude relaxation rate to explain
the linewidth broadening of in-plane precession modes induced in planar
nanostructures. Experiments on the linewidth broadening performed on MgO based
magnetic tunnel junctions are compared to the linewidth obtained from macrospin
simulations and from evaluation of the phase variance. In all cases we find
that the linewidth varies linearly with temperature when the amplitude
relaxation rate is of the same order as the linewidth and when the
amplitude-phase coupling parameter is relatively small. The small
amplitude-phase coupling parameter means that the linewidth is dominated by
direct phase fluctuations and not by amplitude fluctuations, explaining thus
its linear dependence as a function of temperature.


  The emergence of nontrivial collective behavior in networks of coupled
chaotic maps is investigated by means of a nonlinear mutual prediction method.
The resulting prediction error is used to measure the amount of information
that a local unit possesses about the collective dynamics. Applications to
locally and globally coupled map systems are considered. The prediction error
exhibits phase transitions at critical values of the coupling for the onset of
ordered collective behavior in these networks. This information measure may be
used as an order parameter for the characterization of complex behavior in
extended chaotic systems.


  In this paper we derive boundary integral identities for the bi-Laplacian
eigenvalue problems under Dirichlet, Navier and simply-supported boundary
conditions. By using these identities, we first obtain the uniqueness criteria
for the solutions of the bi-Laplacian eigenvalue problems, and then prove that
each eigenvalue of the problem with simply-supported boundary condition
increases strictly with Poisson's ratio, thereby showing that each natural
frequency of a simply-supported vibrating plate increases strictly with
Poisson's ratio. In addition, we obtain boundary integral representations for
the strain energies of the vibrating plates under the three boundary
conditions.


  The recent discovery of superconductivity (SC) and charge density wave (CDW)
in kagome metals AV3Sb5 (A = K, Rb, Cs) provides an ideal playground for the
study of emergent electronic orders. Application of moderate pressure leads to
a two-dome-shaped SC phase regime in CsV3Sb5 accompanied by the destabilizing
of CDW phase; such unconventional evolution of SC may involve the
pressure-induced formation of a new stripe-like CDW order resembling that in
La-214 cuprate superconductors. Nonetheless, the nature of this pressure-tuned
SC state and its interplay with the stripe order are yet to be explored. Here,
we perform soft point-contact spectroscopy (SPCS) measurements in CsV3Sb5 to
investigate the evolution of superconducting order parameter with pressure.
Surprisingly, we find that the superconducting gap is significantly enhanced
between the two SC domes, at which the zero-resistance temperature is
suppressed and the transition is remarkably broadened. Moreover, the
temperature dependence of the SC gap in this pressure range severely deviates
from the conventional BCS behavior, evidencing for strong Cooper pair phase
fluctuations. These findings reveal the complex intertwining of the stripe-like
CDW with SC in the compressed CsV3Sb5, suggesting striking parallel to the
cuprate superconductor La2-xBaxCuO4. Our results point to the essential role of
charge degree of freedom in the development of intertwining electronic orders,
thus provides new constraints for theories.


  Multivariate time series anomaly detection is a crucial problem in many
industrial and research applications. Timely detection of anomalies allows, for
instance, to prevent defects in manufacturing processes and failures in
cyberphysical systems. Deep learning methods are preferred among others for
their accuracy and robustness for the analysis of complex multivariate data.
However, a key aspect is being able to extract predictions in a timely manner,
to accommodate real-time requirements in different applications. In the case of
deep learning models, model reduction is extremely important to achieve optimal
results in real-time systems with limited time and memory constraints. In this
paper, we address this issue by proposing a novel compression method for deep
autoencoders that involves three key factors. First, pruning reduces the number
of weights, while preventing catastrophic drops in accuracy by means of a fast
search process that identifies high sparsity levels. Second, linear and
non-linear quantization reduces model complexity by reducing the number of bits
for every single weight. The combined contribution of these three aspects allow
the model size to be reduced, by removing a subset of the weights (pruning),
and decreasing their bit-width (quantization). As a result, the compressed
model is faster and easier to adopt in highly constrained hardware
environments. Experiments performed on popular multivariate anomaly detection
benchmarks, show that our method is capable of achieving significant model
compression ratio (between 80% and 95%) without a significant reduction in the
anomaly detection performance.


  We describe a number of experiments that demonstrate the usefulness of
prosodic information for a processing module which parses spoken utterances
with a feature-based grammar employing empty categories. We show that by
requiring certain prosodic properties from those positions in the input where
the presence of an empty category has to be hypothesized, a derivation can be
accomplished more efficiently. The approach has been implemented in the machine
translation project VERBMOBIL and results in a significant reduction of the
work-load for the parser.


  Recurrent neural networks (RNNs) have many advantages over more traditional
system identification techniques. They may be applied to linear and nonlinear
systems, and they require fewer modeling assumptions. However, these neural
network models may also need larger amounts of data to learn and generalize.
Furthermore, neural networks training is a time-consuming process. Hence,
building upon long-short term memory neural networks (LSTM), this paper
proposes using two types of deep transfer learning, namely parameter
fine-tuning and freezing, to reduce the data and computation requirements for
system identification. We apply these techniques to identify two dynamical
systems, namely a second-order linear system and a Wiener-Hammerstein nonlinear
system. Results show that compared with direct learning, our method accelerates
learning by 10% to 50%, which also saves data and computing resources.


  Multimedia information have strong temporal correlations that shape the way
modalities co-occur over time. In this paper we study the dynamic nature of
multimedia and social-media information, where the temporal dimension emerges
as a strong source of evidence for learning the temporal correlations across
visual and textual modalities. So far, cross-media retrieval models, explored
the correlations between different modalities (e.g. text and image) to learn a
common subspace, in which semantically similar instances lie in the same
neighbourhood. Building on such knowledge, we propose a novel temporal
cross-media neural architecture, that departs from standard cross-media
methods, by explicitly accounting for the temporal dimension through temporal
subspace learning. The model is softly-constrained with temporal and
inter-modality constraints that guide the new subspace learning task by
favouring temporal correlations between semantically similar and temporally
close instances. Experiments on three distinct datasets show that accounting
for time turns out to be important for cross-media retrieval. Namely, the
proposed method outperforms a set of baselines on the task of temporal
cross-media retrieval, demonstrating its effectiveness for performing temporal
subspace learning.


  We have studied the existence of traveling pulses in a general Type-I
excitable 1-dimensional medium. We have obtained the stability region and
characterized the different bifurcations behind either the destruction or loss
of stability of the pulses. In particular, some of the bifurcations delimiting
the stability region have been connected, using singular limits, with the two
different scenarios that mediated the Type-I local excitability, i.e.
homoclinic (saddle-loop) and Saddle-Node on the Invariant Circle bifurcations.
The existence of the traveling pulses has been linked, outside the stability
region, to a drift pitchfork instability of localized steady structures.


  We find a new solution of the renormalization group for the Potts model with
ferromagnetic random valued coupling constants. The solution exhibits
universality and broken replica symmetry. It is argued that the model reaches
this universality class if the replica symmetry is broken initially. Otherwise
the model stays with the replica symmetric renormalization group flow and
reaches the fixed point which has been considered before.


  In this paper we introduce some infinite rectangle exchange transformations
which are based on the simultaneous turning of the squares within a sequence of
square grids. We will show that such noncompact systems have higher dimensional
dynamical compactifications. In good cases, these compactifications are
polytope exchange transformations based on pairs of Euclidean lattices. In each
dimension $8m+4$ there is a $4m+2$ dimensional family of them. Here
$m=0,1,2,...$ The case $m=0$, which we studied in depth in an earlier paper,
has close connections to the $E_4$ Weyl group and the $(2,4,\infty)$ hyperbolic
triangle group.


  A posteriori error estimates based on residuals can be used for reliable
error control of numerical methods. Here, we consider them in the context of
ordinary differential equations and Runge-Kutta methods. In particular, we take
the approach of Dedner & Giesselmann (2016) and investigate it when used to
select the time step size. We focus on step size control stability when
combined with explicit Runge-Kutta methods and demonstrate that a standard I
controller is unstable while more advanced PI and PID controllers can be
designed to be stable. We compare the stability properties of residual-based
estimators and classical error estimators based on an embedded Runge-Kutta
method both analytically and in numerical experiments.


  Using the technique of Angulo & White (2010) we scale the Millennium and
Millennium-II simulations of structure growth in a LCDM universe from the
cosmological parameters with which they were carried out (based on first-year
results from the Wilkinson Microwave Anisotropy Probe, WMAP1) to parameters
consistent with the seven-year WMAP data (WMAP7). We implement semi-analytic
galaxy formation modelling on both simulations in both cosmologies to
investigate how the formation, evolution and clustering of galaxies are
predicted to vary with cosmological parameters. The increased matter density
Omega_m and decreased linear fluctuation amplitude sigma8 in WMAP7 have
compensating effects, so that the abundance and clustering of dark halos are
predicted to be very similar to those in WMAP1 for z <= 3. As a result, local
galaxy properties can be reproduced equally well in the two cosmologies by
slightly altering galaxy formation parameters. The evolution of the galaxy
populations is then also similar. In WMAP7, structure forms slightly later.
This shifts the peak in cosmic star formation rate to lower redshift, resulting
in slightly bluer galaxies at z=0. Nevertheless, the model still predicts more
passive low-mass galaxies than are observed. For rp< 1Mpc, the z=0 clustering
of low-mass galaxies is weaker for WMAP7 than for WMAP1 and closer to that
observed, but the two cosmologies give very similar results for more massive
galaxies and on large scales. At z>1 galaxies are predicted to be more strongly
clustered for WMAP7. Differences in galaxy properties, including, clustering,
in these two cosmologies are rather small up to redshift 3. Given that there
are still considerable residual uncertainties in galaxy formation models, it is
very difficult to distinguish WMAP1 from WMAP7 through observations of galaxy
properties or their evolution.


  In this paper we report phase modulation obtained by inducing a capacitive
charge on graphene layers embedded in the core of a waveguide. There is a
biasing regime in which graphene absorption is negligible but large index
variations can be achieved with a voltage-length product as small as
$V_\pi\,L_\pi \simeq 0.04 $\,V\,cm . Examples of phase induced changes are
computed for straight waveguides and for microring resonators showing the
possibility to implement several optoelectronic functionalities as modulators,
tunable filters, and switches.


  We formulated the $Lambda(1405)$ (abbreviated as $Lambda^*$) $rightarrow
(Sigmapi)^0$ invariant-mass spectra produced in the $K^- + p rightarrow Sigma^+
(1660) + pi^-$, followed by $Sigma^+ (1660) rightarrow Lambda(1405) + pi^+
rightarrow Sigmapi + pi^+$, processes at $p(K^-) = 4.2$ GeV/$c$, in which both
the incident channel for a quasi-bound $K^-p$ state and its decay process to
$(Sigma pi)^0$ were taken into account realistically. We calculated $M(Sigma
pi)$ spectral shapes using mixed transition matrices, $T_{21} = T_{ Sigmapi
leftarrow K^-p}$ and $T_{22} = T_{ Sigma pi leftarrow Sigma pi}$, for various
theoretical models involving $Lambda^*$. The asymmetric spectra were compared
to old experimental data of Hemingway, and it was found that the mixing of the
two channels, written as $(1-f) , T_{21} + f, T_{22}$, gave a better result
than considering the individual channels, yielding $f =
0.376_{-0.019}^{+0.021}$, $M(Lambda^*) = 1406.6_{-3.3}^{+3.4}$ MeV/$c^2$ and
$Gamma = 70 pm 2$ MeV, nearly consistent with the 2014 PDG values.


  Confidence is a fundamental concept in statistics, but there is a tendency to
misinterpret it as probability. In this paper, I argue that an intuitively and
mathematically more appropriate interpretation of confidence is through
belief/plausibility functions, in particular, those that satisfy a certain
validity property. Given their close connection with confidence, it is natural
to ask how a valid belief/plausibility function can be constructed directly.
The inferential model (IM) framework provides such a construction, and here I
prove a complete-class theorem stating that, for every nominal confidence
region, there exists a valid IM whose plausibility regions are contained by the
given confidence region. This characterization has implications for statistics
understanding and communication, and highlights the importance of belief
functions and the IM framework.


  Complete expressions of the thermal-expansion coefficient $\alpha$ and the
Gr\"{u}neisen parameter $\Gamma$ are derived on the basis of the
self-consistent renormalization (SCR) theory. By considering zero-point as well
as thermal spin fluctuation under the stationary condition, the specific heat
for each class of the magnetic quantum critical point (QCP) specified by the
dynamical exponent $z=3$ (FM) and $z=2$ (AFM) and the spatial dimension ($d=3$
and $2$) is shown to be expressed as $C_{V}=C_a-C_b$, where $C_a$ is dominant
at low temperatures, reproducing the past SCR criticality endorsed by the
renormalization group theory. Starting from the explicit form of the entropy
and using the Maxwell relation, $\alpha=\alpha_a+\alpha_b$ (with $\alpha_a$ and
$\alpha_b$ being related to $C_a$ and $C_b$, respectively) is derived, which is
proven to be equivalent to $\alpha$ derived from the free energy. The
temperature-dependent coefficient found to exist in $\alpha_b$, which is
dominant at low temperatures, contributes to the crossover from the
quantum-critical regime to the Curie-Weiss regime and even affects the quantum
criticality at 2d AFM QCP. Based on these correctly calculated $C_{V}$ and
$\alpha$, Gr\"{u}neisen parameter $\Gamma=\Gamma_a+\Gamma_b$ is derived, where
$\Gamma_a$ and $\Gamma_b$ contain $\alpha_a$ and $\alpha_b$, respectively. The
inverse susceptibility coupled to the volume $V$ in $\Gamma_b$ gives rise to
divergence of $\Gamma$ at the QCP for each class even though characteristic
energy scale of spin fluctuation $T_0$ is finite at the QCP, which gives a
finite contribution in $\Gamma_a=-\frac{V}{T_0}\left(\frac{\partial
T_0}{\partial V}\right)_{T=0}$. General properties of $\alpha$ and $\Gamma$
including their signs as well as the relation to $T_0$ and the Kondo
temperature in temperature-pressure phase diagrams of Ce- and Yb-based heavy
electron systems are discussed.


  The question of the renormalization scheme dependence of the $\tau$
semileptonic decay rate is revisited in response to a recent criticism.
Particular attention is payed to a distinction between a consistent
quantitative description of this dependence and the actual selection of a
subset of ``acceptable'' renormalization schemes. It is argued that a
reasonable universal measure of the renormalization scheme dependence can be
formulated, which gives encouraging results when applied to various physical
quantities, including the semileptonic $\tau$ decay rate.


  This is my talk at ICM, Zurich 1994. It contains a short introduction, two
basic examples and a refined version of the Mirror Conjecture formulated in
terms of homological algebra.


  The problem of checking a logged event trace against a temporal logic
specification arises in many practical cases. Unfortunately, known algorithms
for an expressive logic like MTL (Metric Temporal Logic) do not scale with
respect to two crucial dimensions: the length of the trace and the size of the
time interval for which logged events must be buffered to check satisfaction of
the specification. The former issue can be addressed by distributed and
parallel trace checking algorithms that can take advantage of modern cloud
computing and programming frameworks like MapReduce. Still, the latter issue
remains open with current state-of-the-art approaches.
  In this paper we address this memory scalability issue by proposing a new
semantics for MTL, called lazy semantics. This semantics can evaluate temporal
formulae and boolean combinations of temporal-only formulae at any arbitrary
time instant. We prove that lazy semantics is more expressive than standard
point-based semantics and that it can be used as a basis for a correct
parametric decomposition of any MTL formula into an equivalent one with
smaller, bounded time intervals. We use lazy semantics to extend our previous
distributed trace checking algorithm for MTL. We evaluate the proposed
algorithm in terms of memory scalability and time/memory tradeoffs.


  Background and objectives: Dynamic handwriting analysis, due to its
non-invasive and readily accessible nature, has recently emerged as a vital
adjunctive method for the early diagnosis of Parkinson's disease. In this
study, we design a compact and efficient network architecture to analyse the
distinctive handwriting patterns of patients' dynamic handwriting signals,
thereby providing an objective identification for the Parkinson's disease
diagnosis.
  Methods: The proposed network is based on a hybrid deep learning approach
that fully leverages the advantages of both long short-term memory (LSTM) and
convolutional neural networks (CNNs). Specifically, the LSTM block is adopted
to extract the time-varying features, while the CNN-based block is implemented
using one-dimensional convolution for low computational cost. Moreover, the
hybrid model architecture is continuously refined under ablation studies for
superior performance. Finally, we evaluate the proposed method with its
generalization under a five-fold cross-validation, which validates its
efficiency and robustness.
  Results: The proposed network demonstrates its versatility by achieving
impressive classification accuracies on both our new DraWritePD dataset
($96.2\%$) and the well-established PaHaW dataset ($90.7\%$). Moreover, the
network architecture also stands out for its excellent lightweight design,
occupying a mere $0.084$M of parameters, with a total of only $0.59$M
floating-point operations. It also exhibits near real-time CPU inference
performance, with inference times ranging from $0.106$ to $0.220$s.
  Conclusions: We present a series of experiments with extensive analysis,
which systematically demonstrate the effectiveness and efficiency of the
proposed hybrid neural network in extracting distinctive handwriting patterns
for precise diagnosis of Parkinson's disease.


  We give an approach to exponential stability within the framework of
evolutionary equations due to [R. Picard. A structural observation for linear
material laws in classical mathematical physics. Math. Methods Appl. Sci.,
32(14):1768-1803,2009]. We derive sufficient conditions for exponential
stability in terms of the material law operator, which is defined via an
analytic and bounded operator-valued function and give an estimate for the
expected decay rate. The results are illustrated by three examples:
differential-algebraic equations, partial differential equations with finite
delay and parabolic integro-differential equations.


  We consider active nematodynamics on deformable surfaces. Based on a
thermodynamically consistent surface Beris-Edwards model we add nematic
activity and focus on the emerging additional coupling mechanism between the
nematic field, the flow field and the curved surface. We analyse the impact of
the active nematic force at topological defects. Under the presence of
curvature all defects become active and contribute not only tangential forces
but also normal forces. This confirms the proposed role of topological defects
in surface evolution and provides the basis for a dynamic description of
morphogenetic processes.


  We present radiative transfer models for submillimeter galaxies with
spectroscopic redshifts and mid-infrared spectroscopy from Spitzer/IRS and
analyze available Spitzer/MIPS 24, 70 and 160mu data. We use two types of
starburst models, a cirrus model and a model for the emission of an AGN torus
in order to investigate the nature of these objects. We find that for three of
the objects (25%) cirrus emission alone can account for the mid-infrared
spectrum and the MIPS and submillimeter data. For the remaining objects we find
that we need a combination of starburst and cirrus in order to fit
simultaneously the multi--wavelength data.
  We find that the typical submillimeter galaxy has comparable luminosity in
the starburst (median L=10^12.5 Lo) and cirrus (median L=10^12.4 Lo)
components. This could arise if the galaxies have been forming stars
continuously for the last 250Myr with the star formation occurring in the last
5Myr being shrouded by high-optical-depth molecular cloud dust, whereas the
rest of the starlight is attenuated by diffuse dust or cirrus with an Av of
about 1mag.


  In this note, we apply the semi-ampleness criterion in Lemma 3.1 to prove
many classical results in the study of abundance conjecture. As a corollary, we
prove abundance for large Kodaira dimension depending only on [BCHM10].


  The Szegedy quantum walk is a discrete time quantum walk model which defines
a quantum analogue of any Markov chain. The long-term behavior of the quantum
walk can be encoded in a matrix called the average mixing matrix, whose columns
give the limiting probability distribution of the walk given an initial state.
We define a version of the average mixing matrix of the Szegedy quantum walk
which allows us to more readily compare the limiting behavior to that of the
chain it quantizes. We prove a formula for our mixing matrix in terms of the
spectral decomposition of the Markov chain and show a relationship with the
mixing matrix of a continuous quantum walk on the chain. In particular, we
prove that average uniform mixing in the continuous walk implies average
uniform mixing in the Szegedy walk. We conclude by giving examples of Markov
chains of arbitrarily large size which admit average uniform mixing in both the
continuous and Szegedy quantum walk.


  We construct first examples of infinite finitely generated residually finite
torsion groups with positive rank gradient. In particular, these groups are
non-amenable. Some applications to problems about cost and $L^2$-Betti numbers
are discussed.


  In many fields of robotics, knowing the relative position and orientation
between two sensors is a mandatory precondition to operate with multiple
sensing modalities. In this context, the pair LiDAR-RGB cameras offer
complementary features: LiDARs yield sparse high quality range measurements,
while RGB cameras provide a dense color measurement of the environment.
Existing techniques often rely either on complex calibration targets that are
expensive to obtain, or extracted virtual correspondences that can hinder the
estimate's accuracy. In this paper we address the problem of LiDAR-RGB
calibration using typical calibration patterns (i.e. A3 chessboard) with
minimal human intervention. Our approach exploits the planarity of the target
to find correspondences between the sensors measurements, leading to features
that are robust to LiDAR noise.
  Moreover, we estimate a solution by solving a joint non-linear optimization
problem. We validated our approach by carrying on quantitative and comparative
experiments with other state-of-the-art approaches. Our results show that our
simple schema performs on par or better than other approches using complex
calibration targets. Finally, we release an open-source C++ implementation at
\url{https://github.com/srrg-sapienza/ca2lib}


  We investigate equilibria of charged deformable materials via the
minimization of an electroelastic energy. This features the coupling of elastic
response and electrostatics by means of a capacitary term, which is naturally
defined in Eulerian coordinates. The ensuing electroelastic energy is then of
mixed Lagrangian-Eulerian type. We prove that minimizers exist by investigating
the continuity properties of the capacitary terms under convergence of the
deformations


  The structural symmetry of forty-three face-on galaxy images in the R(65 0
nm) and J(450 nm) bands are measured to determine the usefulness of symmetry a
s a morphological parameter. Each galaxy image is rotated by $180$\deg and
subtr acted from the original to obtain a quantitative value for its structural
symmet ry. The symmetry numbers computed for the sample are then compared with
RC3 mor phological types, color \& absolute blue magnitudes. A strong
correlation betw een color and symmetry is found, and the RC3 Hubble sequence
is found to be one of increasing asymmetry. The use of symmetry as a
morphological parameter, and the possible causes of the asymmetries are
discussed.


  I describe the construction of a large class of asymptotically flat initial
data with non-vanishing mass and angular momentum for which the metric and the
extrinsic curvature have asymptotic expansions at space-like infinity in terms
of powers of a radial coordinate. I emphasize the motivations and the main
ideas behind the proofs.


  The multi-user Holographic Multiple-Input and Multiple-Output Surface
(MU-HMIMOS) paradigm, which is capable of realizing large continuous apertures
with minimal power consumption, has been recently considered as an
energyefficient solution for future wireless networks, offering increased
flexibility in impacting electromagnetic (EM) wave propagation according to the
desired communication, localization, and sensing objectives. The tractable
channel modeling in MU-HMIMOS wireless systems is one of the most critical
research challenges, mainly due to the coupling effect induced by the
excessively large number of closely spaced patch antennas. In this paper, we
focus on this challenge for the downlink of multi-user MIMO communications and
extend an EM-compliant channel model to multiuser case, which is expressed in
the wavenumber domain using the Fourier plane wave approximation. Based on the
presented channel model, we investigate the spectral efficiency of maximumratio
transmission and Zero-Forcing (ZF) precoding schemes. We also introduce a novel
hardware efficient ZF precoder, leveraging Neumann series (NS) expansion to
replace the required matrix inversion operation, which is very hard to be
computed in the conventional way due to the extremely large number of patch
antennas in the envisioned MU-HMIMOS communication systems. In comparison with
the conventional independent and identical Rayleigh fading channels that ignore
antenna coupling effects, the proposed EM-compliant channel model captures the
mutual couplings induced by the very small antenna spacing. Our extensive
performance evaluation results demonstrate that our theoretical performance
expressions approximate sufficiently well ...


  The sigma model describing closed strings rotating in AdS_3 x S^3 is known to
reduce to the one-dimensional Neumann-Rosochatius integrable system. In this
article we show that closed spinning strings in AdS_3 x S^3 x T^4 in the
presence of NS-NS three-form flux can be described by an extension of the
Neumann-Rosochatius system. We consider closed strings rotating with one spin
in AdS_3 and two different angular momenta in S^3. For a class of solutions
with constant radii we find the dependence of the classical energy on the spin
and the angular momenta as an expansion in the square of the 't Hooft coupling
of the theory.


  Specific contact resistivity measurements have conventionally been heavy in
both fabrication and simulation/calculation in order to account for complicated
geometries and other effects such as parasitic resistance. We propose a simpler
geometry to deliver current, and the use of a scanning voltage probe to sense
the potential variation along the sample surface, from which the specific
contact resistivity can be straightforwardly deduced. We demonstrate an
analytical example in the case where both materials are thin films.
Experimental data with a scanning Kelvin probe measurement on graphene from the
literature corroborates our model calculation.


  Objects gravitationally captured by the Earth-Moon system are commonly called
temporarily captured orbiters (TCOs), natural Earth satellites, or minimoons.
TCOs are a crucially important subpopulation of near-Earth objects (NEOs) to
understand because they are the easiest targets for future sample-return,
redirection, or asteroid mining missions. Only one TCO has ever been observed
telescopically, 2006 RH 120, and it orbited Earth for about 11 months.
Additionally, only one TCO fireball has ever been observed prior to this study.
We present our observations of an extremely slow fireball (codename
DN160822_03) with an initial velocity of around 11.0 km s-1 that was detected
by six of the high-resolution digital fireball observatories located in the
South Australian region of the Desert Fireball Network. Due to the inherent
dynamics of the system, the probability of the meteoroid being temporarily
captured before impact is extremely sensitive to its initial velocity. We
examine the sensitivity of the fireball's orbital history to the chosen
triangulation method. We use the numerical integrator REBOUND to assess
particle histories and assess the statistical origin of DN160822_03. From our
integrations we have found that the most probable capture time, velocity,
semimajor axis, NEO group, and capture mechanism vary annually for this event.
Most particles show that there is an increased capture probability during
Earth's aphelion and perihelion. In the future, events like these may be
detected ahead of time using telescopes like the Large Synoptic Survey
Telescope, and the pre-atmospheric trajectory can be verified.


  We consider Einstein-Maxwell-dilaton theory in four dimensions including the
Kaluza-Klein theory and obtain the general asymptotic solutions in Bondi gauge.
We find that there are three different types of news functions representing
gravitational, electromagnetic, and scalar radiations. The mass density at any
angle of the system can only decrease whenever there is any type of news
function. The solution space of the Kaluza-Klein theory is also lifted to five
dimensions. We also compute the asymptotic symmetries in both four dimensional
Einstein-Maxwell-dilaton theory and five dimensional pure Einstein theory. We
find that the symmetry algebras of the two theories are the same.


  In critical lattice models, distance ($r$) dependent correlation functions
contain power laws $r^{-2\Delta}$ governed by scaling dimensions $\Delta$ of an
underlying continuum field theory. In Monte Carlo simulations and other
numerical approaches, the leading dimensions can be extracted by data fitting,
which can be difficult when two or more powers contribute significantly. Here a
method utilizing covariance between multiple lattice operators is developed
where the $r$ dependent eigenvalues of the covariance matrix represent scaling
dimensions of individual field operators. The scheme is tested on symmetric
operators in the two-dimensional tricritical Blume-Capel model, where the two
relevant dimensions, as well as some irrelevant ones, are isolated along with
their corresponding eigenvectors. The method will be broadly useful in studies
of classical and quantum models at multicritical points and for targeting
irrelevant operators at simple critical (or multicritical) points.


  We investigate a phase separation instability that occurs in a system of
nearly elastically colliding hard spheres driven by a thermal wall. If the
aspect ratio of the confining box exceeds a threshold value, granular
hydrostatics predict phase separation: the formation of a high-density region
coexisting with a low-density region along the wall that is opposite to the
thermal wall. Event-driven molecular dynamic simulations confirm this
prediction. The theoretical bifurcation curve agrees with the simulations
quantitatively well below and well above the threshold. However, in a wide
region of aspect ratios around the threshold, the system is dominated by
fluctuations, and the hydrostatic theory breaks down. Two possible scenarios of
the origin of the giant fluctuations are discussed.


  Predicting the biological function of molecules, be it proteins or drug-like
compounds, from their atomic structure is an important and long-standing
problem. Function is dictated by structure, since it is by spatial interactions
that molecules interact with each other, both in terms of steric
complementarity, as well as intermolecular forces. Thus, the electron density
field and electrostatic potential field of a molecule contain the "raw
fingerprint" of how this molecule can fit to binding partners. In this paper,
we show that deep learning can predict biological function of molecules
directly from their raw 3D approximated electron density and electrostatic
potential fields. Protein function based on EC numbers is predicted from the
approximated electron density field. In another experiment, the activity of
small molecules is predicted with quality comparable to state-of-the-art
descriptor-based methods. We propose several alternative computational models
for the GPU with different memory and runtime requirements for different sizes
of molecules and of databases. We also propose application-specific
multi-channel data representations. With future improvements of training
datasets and neural network settings in combination with complementary
information sources (sequence, genomic context, expression level), deep
learning can be expected to show its generalization power and revolutionize the
field of molecular function prediction.


  A revised and greatly improved version of the 3D continuum radiative transfer
code MC3D is presented. It is based on the Monte-Carlo method and solves the
radiative transfer problem self-consistently. It is designed for the simulation
of dust temperatures in arbitrary geometric configurations and the resulting
observables: spectral energy distributions, wavelength-dependent images, and
polarization maps. The main objective is the investigation of
``dust-dominated'' astrophysical systems such as young stellar objects
surrounded by an optically thick circumstellar disk and an optically thin(ner)
envelope, debris disks around more evolved stars, asymptotic giant branch
stars, the dust component of the interstellar medium, and active galactic
nuclei.


  Optimal prediction methods compensate for a lack of resolution in the
numerical solution of time-dependent differential equations through the use of
prior statistical information. We present a new derivation of the basic
methodology, show that field-theoretical perturbation theory provides a useful
device for dealing with quasi-linear problems, and provide a nonlinear example
that illuminates the difference between a pseudo-spectral method and an optimal
prediction method with Fourier kernels. Along the way, we explain the
differences and similarities between optimal prediction, the representer method
in data assimilation, and duality methods for finding weak solutions. We also
discuss the conditions under which a simple implementation of the optimal
prediction method can be expected to perform well.


  The increasing complexity and usage of cloud systems have made it challenging
for service providers to ensure reliability. This paper highlights two main
challenges, namely internal and external factors, that affect the reliability
of cloud microservices. Afterward, we discuss the data-driven approach that can
resolve these challenges from four key aspects: ticket management, log
management, multimodal analysis, and the microservice resilience testing
approach. The experiments conducted show that the proposed data-driven AIOps
solution significantly enhances system reliability from multiple angles.


  The lore paradigm for solving so-called horizon and flatness problems in
cosmology is the primordial inflation. Plethora of inflationary models have
been built in last decades and first experimental probes seem to appear in
favor of the inflationary paradigm. We will focus here on one of them, the
Higgs inflation, and show the combined constraint required for such a model at
cosmological as well as gravitational scales, i.e. for compact objects. We will
show that Higgs inflation model gives rise to particlelike solutions around
compact objects, dubbed Higgs monopoles, characterized by the nonminimal
coupling parameter as well as the mass and the compactness of the object. For
large values of the nonminimal coupling constant and specific compactness, the
amplitude of the Higgs field inside the matter distribution can be arbitrarily
large.


  The inverse problem of electrical impedance tomography is severely ill-posed,
meaning that, only limited information about the conductivity can in practice
be recovered from boundary measurements of electric current and voltage.
Recently it was shown that a simple monotonicity property of the related
Neumann-to-Dirichlet map can be used to characterize shapes of inhomogeneities
in a known background conductivity. In this paper we formulate a
monotonicity-based shape reconstruction scheme that applies to approximative
measurement models, and regularizes against noise and modelling error. We
demonstrate that for admissible choices of regularization parameters the
inhomogeneities are detected, and under reasonable assumptions, asymptotically
exactly characterized. Moreover, we rigorously associate this result with the
complete electrode model, and describe how a computationally cheap
monotonicity-based reconstruction algorithm can be implemented. Numerical
reconstructions from both simulated and real-life measurement data are
presented.


  Adversarial examples have been well known as a serious threat to deep neural
networks (DNNs). In this work, we study the detection of adversarial examples,
based on the assumption that the output and internal responses of one DNN model
for both adversarial and benign examples follow the generalized Gaussian
distribution (GGD), but with different parameters (i.e., shape factor, mean,
and variance). GGD is a general distribution family to cover many popular
distributions (e.g., Laplacian, Gaussian, or uniform). It is more likely to
approximate the intrinsic distributions of internal responses than any specific
distribution. Besides, since the shape factor is more robust to different
databases rather than the other two parameters, we propose to construct
discriminative features via the shape factor for adversarial detection,
employing the magnitude of Benford-Fourier coefficients (MBF), which can be
easily estimated using responses. Finally, a support vector machine is trained
as the adversarial detector through leveraging the MBF features. Extensive
experiments in terms of image classification demonstrate that the proposed
detector is much more effective and robust on detecting adversarial examples of
different crafting methods and different sources, compared to state-of-the-art
adversarial detection methods.


  In this paper we prove a new matrix Li-Yau-Hamilton estimate for
K\"ahler-Ricci flow. The form of this new Li-Yau-Hamilton estimate is obtained
by the interpolation consideration originated in \cite{Ch1}. This new
inequality is shown to be connected with Perelman's entropy formula through a
family of differential equalities. In the rest of the paper, We show several
applications of this new estimate and its linear version proved earlier in
\cite{CN}. These include a sharp heat kernel comparison theorem, generalizing
the earlier result of Li and Tian, a manifold version of Stoll's theorem on the
characterization of `algebraic divisors', and a localized monotonicity formula
for analytic subvarieties.
  Motivated by the connection between the heat kernel estimate and the reduced
volume monotonicity of Perelman, we prove a sharp lower bound heat kernel
estimate for the time-dependent heat equation, which is, in a certain sense,
dual to Perelman's monotonicity of the `reduced volume'. As an application of
this new monotonicity formula, we show that the blow-down limit of a certain
type III immortal solution is a gradient expanding soliton.
  In the last section we also illustrate the connection between the new
Li-Yau-Hamilton estimate and the earlier Hessian comparison theorem on the
`reduced distance', proved in \cite{FIN}.


  The \emph{index coding} problem has recently attracted a significant
attention from the research community due to its theoretical significance and
applications in wireless ad-hoc networks. An instance of the index coding
problem includes a sender that holds a set of information messages
$X=\{x_1,...,x_k\}$ and a set of receivers $R$. Each receiver $\rho=(x,H)\in R$
needs to obtain a message $x\in X$ and has prior \emph{side information}
comprising a subset $H$ of $X$. The sender uses a noiseless communication
channel to broadcast encoding of messages in $X$ to all clients. The objective
is to find an encoding scheme that minimizes the number of transmissions
required to satisfy the receivers' demands with \emph{zero error}.
  In this paper, we analyze the relation between the index coding problem, the
more general network coding problem and the problem of finding a linear
representation of a matroid. In particular, we show that any instance of the
network coding and matroid representation problems can be efficiently reduced
to an instance of the index coding problem. Our reduction implies that many
important properties of the network coding and matroid representation problems
carry over to the index coding problem. Specifically, we show that \emph{vector
linear codes} outperform scalar linear codes and that vector linear codes are
insufficient for achieving the optimum number of transmissions.


  Structural microvascular alterations and dysfunction serve as key disease
indicators of cancer, diabetes, ischemic stroke, neurodegenerative disorders
and many other conditions. In vivo visualization of the microvasculature has
traditionally been restricted to millimeter scale depths accessible with
optical microscopy. Optoacoustic imaging has enabled breaking through the
barrier imposed by light diffusion to map functional hemodynamic parameters in
deep-seated vessels, but diffraction and dispersion of ultrasound waves in
heterogeneous living tissues prevents reaching capillary resolution. Herein, we
demonstrate three-dimensional microangiography of deep mouse brain beyond the
acoustic diffraction limit (<20$\mu$m resolution) through the intact scalp and
skull via optoacoustic localization of sparsely-distributed highly absorbing
microparticles. This was enabled by devising 5$\mu$m sized extremely absorbing
dichloromethane microdroplets exhibiting four orders of magnitude higher
optical absorption than red blood cells at near-infrared wavelengths, thus
facilitating in vivo compatibility and single particle sensitivity in the
presence of highly absorbing blood background. Accurate mapping of the blood
flow velocity within microvascular structures was also facilitated by the high
3D frame rate of the optoacoustic tomography system. We further show that the
detected optoacoustic signal intensities from the localized particles may serve
for estimating the light fluence distribution within optically heterogeneous
tissues, a long-standing quantification challenge in biomedical optics. Given
the intrinsic sensitivity of optoacoustics to various functional, metabolic and
molecular events in living tissues, this new approach paves the way for
non-invasive deep-tissue microscopic observations with unrivaled resolution,
contrast and speed.


  The treatment of systematic noise is a significant aspect of transit
exoplanet data processing due to the signal strength of systematic noise
relative to a transit signal. Typically the standard approach to transit
detection is to estimate and remove systematic noise independently of and prior
to a transit detection test. If a transit signal is present in a light curve,
the process of systematic noise removal may distort the transit signal by
overfitting and thereby reduce detection efficiency. We present a Bayesian
framework for joint detection of transit signals and systematic noise
characterization and describe the implementation of these detectors as optimal
Neyman-Pearson likelihood ratio tests. The joint detectors reduce to closed
form as matched filters under the assumption of a Gaussian Bayesian prior for
the systematic noise. The performance of the exploratory detectors was
evaluated in injection tests and show $\sim 2\%$ improvement in overall
detection efficiency relative to the standard approach. We find that joint
detection efficiency is specifically improved for short-period, low
transit-depth exoplanet transits, providing evidence in support of the
hypothesis that joint detection may indeed help to mitigate overfitting. In
addition, an initial feasibility test to detect known exoplanets in Kepler data
using the joint detectors produced encouraging preliminary results.


  We establish a precise relation between mixed boundary conditions for scalar
fields in asymptotically anti de Sitter spacetimes and the equation of state of
the dual fluid. We provide a detailed derivation of the relation in the case of
five bulk-dimensions for scalar fields saturating the Breitenlohner-Freedman
bound. As a concrete example, we discuss the five dimensional scalar-tensor
theories describing a constant speed of sound.


  The non-equilibrium dynamic fluctuations of a stochastic version of the
Gray-Scott (GS) model are studied analytically in leading order in perturbation
theory by means of the dynamic renormalization group. There is an attracting
stable fixed point at one-loop order, and the asymptotic scaling of the
correlation functions is predicted for both spatial and temporally correlated
noise sources. New effective three-body reaction terms, not present in the
original GS model, are induced by the combined interplay of the fluctuations
and nonlinearities.


  The magnetic and electronic properties of the layered Zintl-phase compound
EuAl$_2$Ge$_2$ crystallizing in the trigonal CaAl$_2$Si$_2$-type structure are
reported. Our neutron-diffraction measurements show that EuAl$_2$Ge$_2$
undergoes A-type antiferromagnetic (AFM) ordering below $T_{\rm N} =
27.5(5)$~K, with the Eu moments (Eu$^{2+}$, $S = 7/2$) aligned
ferromagnetically in the $ab$ plane. The $H = 0$ magnetic structure consists of
trigonal AFM domains associated with $ab$-plane magnetic anisotropy and a
field-induced reorientation of the Eu spins in the domains is evident at $T =
2$~K below the critical field $H_{c1} = 2.5(1)$ kOe. Electrical resistivity and
ARPES measurements show that EuAl$_2$Ge$_2$ is metallic both above and below
$T_{\rm N}$. In the AFM phase, we directly observe folded bands in ARPES due to
the doubling of the magnetic unit cell along the $c$ axis with an enhancement
of quasiparticle weight due to the complex change in the coupling between the
magnetic moments and itinerant electrons on cooling below $T_{\rm N}$. The
observed electronic structure is well reproduced by first-principle
calculations, which also predict the presence of nontrivial electronic states
near the Fermi level in the AFM phase with $Z_2$ topological numbers 1;(000).


  Solitary states emerge in oscillator networks when one oscillator separates
from the fully synchronized cluster and becomes incoherent with the rest of the
network. Such chimera-type patterns with an incoherent state formed by a single
oscillator were observed in various oscillator networks; however, there is
still a lack of understanding of how such states can stably appear. Here, we
study the stability of solitary states in Kuramoto networks of identical
two-dimensional phase oscillators with inertia and a phase-lagged coupling. The
presence of inertia can induce rotatory dynamics of the phase difference
between the solitary oscillator and the coherent cluster. We derive asymptotic
stability conditions for such a solitary state as a function of inertia,
network size, and phase lag that may yield either attractive or repulsive
coupling. Counterintuitively, our analysis demonstrates that (i) increasing the
size of the coherent cluster can promote the stability of the solitary state in
the attractive coupling case and (ii) the solitary state can be stable in
small-size networks with all repulsive coupling. We also discuss the
implications of our stability analysis for the emergence of rotatory chimeras.


  We propose a model of ripples in suspended graphene sheets based on plate
equations that are made discrete with the periodicity of the honeycomb lattice
and then periodized. In addition, the equation for the displacements with
respect to the planar configuration contains a double-well site potential, a
nonlinear friction and a multiplicative white noise term satisfying the
fluctuation-dissipation theorem. The nonlinear friction terms agree with those
proposed by Eichler et al [Nature Nanotech. {\bf 6}, 339 (2011)] to explain
their experiments with a graphene resonator. The site double-well potential
indicates that the carbon atoms at each lattice point have equal probability to
move upward or downward off-plane. For the considered parameter values, the
relaxation time due to friction is much larger than the periods of membrane
vibrations and the noise is quite small. Then ripples with no preferred
orientation appear as long-lived metastable states for any temperature.
Numerical solutions confirm this picture.


  Traditional ranking systems are expected to sort items in the order of their
relevance and thereby maximize their utility. In fair ranking, utility is
complemented with fairness as an optimization goal. Recent work on fair ranking
focuses on developing algorithms to optimize for fairness, given position-based
exposure. In contrast, we identify the potential of outliers in a ranking to
influence exposure and thereby negatively impact fairness. An outlier in a list
of items can alter the examination probabilities, which can lead to different
distributions of attention, compared to position-based exposure. We formalize
outlierness in a ranking, show that outliers are present in realistic datasets,
and present the results of an eye-tracking study, showing that users scanning
order and the exposure of items are influenced by the presence of outliers. We
then introduce OMIT, a method for fair ranking in the presence of outliers.
Given an outlier detection method, OMIT improves fair allocation of exposure by
suppressing outliers in the top-k ranking. Using an academic search dataset, we
show that outlierness optimization leads to a fairer policy that displays fewer
outliers in the top-k, while maintaining a reasonable trade-off between
fairness and utility.


  A correlated random walk approach to diffusion is applied to the disordered
nonoverlapping Lorentz gas. By invoking the Lu-Torquato theory for chord-length
distributions in random media [J. Chem. Phys. 98, 6472 (1993)], an analytic
expression for the diffusion constant in arbitrary number of dimensions d is
obtained. The result corresponds to an Enskog-like correction to the Boltzmann
prediction, being exact in the dilute limit, and better or nearly exact in
comparison to renormalized kinetic theory predictions for all allowed densities
in d=2,3. Extensive numerical simulations were also performed to elucidate the
role of the approximations involved.


  We study effect of cavity collapse in non-ideal explosives as a means of
controlling their sensitivity. The main aim is to understand the origin of
localised temperature peaks (hot spots) that play a leading order role at early
ignition stages. Thus, we perform 2D and 3D numerical simulations of shock
induced single gas-cavity collapse in nitromethane. Ignition is the result of a
complex interplay between fluid dynamics and exothermic chemical reaction. In
part I of this work we focused on the hydrodynamic effects in the collapse
process by switching off the reaction terms in the mathematical model. Here, we
reinstate the reactive terms and study the collapse of the cavity in the
presence of chemical reactions. We use a multi-phase formulation which
overcomes current challenges of cavity collapse modelling in reactive media to
obtain oscillation-free temperature fields across material interfaces to allow
the use of a temperature-based reaction rate law. The mathematical and physical
models are validated against experimental and analytic data. We identify which
of the previously-determined (in part I of this work) high-temperature regions
lead to ignition and comment on their reactive strength and reaction growth
rate. We quantify the sensitisation of nitromethane by the collapse of the
cavity by comparing ignition times of neat and single-cavity material; the
ignition occurs in less than half the ignition time of the neat material. We
compare 2D and 3D simulations to examine the change in topology, temperature
and reactive strength of the hot spots by the third dimension. It is apparent
that belated ignition times can be avoided by the use of 3D simulations. The
effect of the chemical reactions on the topology and strength of the hot spots
in the timescales considered is studied by comparing inert and reactive
simulations and examine maximum temperature fields and their growth rates.


  The problem of spurious correlations (SCs) arises when a classifier relies on
non-predictive features that happen to be correlated with the labels in the
training data. For example, a classifier may misclassify dog breeds based on
the background of dog images. This happens when the backgrounds are correlated
with other breeds in the training data, leading to misclassifications during
test time. Previous SC benchmark datasets suffer from varying issues, e.g.,
over-saturation or only containing one-to-one (O2O) SCs, but no many-to-many
(M2M) SCs arising between groups of spurious attributes and classes. In this
paper, we present \benchmark-\{O2O, M2M\}-\{Easy, Medium, Hard\}, an image
classification benchmark suite containing spurious correlations between classes
and backgrounds. To create this dataset, we employ a text-to-image model to
generate photo-realistic images and an image captioning model to filter out
unsuitable ones. The resulting dataset is of high quality and contains
approximately 152k images. Our experimental results demonstrate that
state-of-the-art group robustness methods struggle with \benchmark, most
notably on the Hard-splits with none of them getting over $70\%$ accuracy on
the hardest split using a ResNet50 pretrained on ImageNet. By examining model
misclassifications, we detect reliances on spurious backgrounds, demonstrating
that our dataset provides a significant challenge.


  The faithful state transfer is an important requirement in the construction
of classical and quantum computers. While the high-speed transfer is realized
by optical-fibre interconnects, its implementation in integrated optical
circuits is affected by cross-talk. The cross-talk between densely packed
optical waveguides limits the transfer fidelity and distorts the signal in each
channel, thus severely impeding the parallel transfer of states such as
classical registers, multiple qubits and qudits. Here, we leverage on the
suitably engineered cross-talk between waveguides to achieve the parallel
transfer on optical chip. Waveguide coupling coefficients are designed to yield
commensurate eigenvalues of the array and hence, periodic revivals of the input
state. While, in general, polynomially complex, the inverse eigenvalue problem
permits analytic solutions for small number of waveguides. We present exact
solutions for arrays of up to nine waveguides and use them to design realistic
buses for multi-(qu)bit and qudit transfer. Advantages and limitations of the
proposed solution are discussed in the context of available fabrication
techniques.


  We study GL(2)-bundles with connections with a small parameter on a smooth
projective curve. We describe an open subset in the moduli space of such
bundles. The description degenerates into the Hitchin fibration as the
parameter tends to zero.


  We consider the imaginary time flow of a quadratic hyperbolic Hamiltonian on
the symplectic plane, apply it to the Schr\"odinger polarization and study the
corresponding evolution of polarized sections. The flow is periodic in
imaginary time and the evolution of polarized sections has interesting
features. On the time intervals for which the polarization is real or K\"ahler,
the half--form corrected time evolution of polarized sections is given by
unitary operators which turn out to be equivalent to the classical
Segal-Bargmann transforms (which are usually associated to the quadratic
elliptic Hamiltonian $H=\frac12 p^2$ and to the heat operator). At the right
endpoint of these intervals, the evolution of polarized sections is given by
the Fourier transform from the Schr\"odinger to the momentum representation. In
the complementary intervals of imaginary time, the polarizations are
anti--K\"ahler and the Hilbert space of polarized sections collapses to
${\mathcal H}= \{0\}$.
  Hyperbolic quadratic Hamiltonians thus give rise to a new factorization of
the Segal-Bargmann transform, which is very different from the usual one, where
one first applies a bounded contraction operator (the heat kernel operator),
mapping $L^2$--states to real analytic functions with unique analytic
continuation, and then one applies analytic continuation. In the factorization
induced by an hyperbolic complexifier, both factors are unbounded operators but
their composition is, in the K\"ahler or real sectors, unitary.
  In another paper [KMNT], we explore the application of the above family of
unitary transforms to the definition of new holomorphic fractional Fourier
transforms.


  Based on a theoretical model for opinion spreading on a network, through
avalanches, the effect of external field is now considered, by using methods
from non-equilibrium statistical mechanics. The original part contains the
implementation that the avalanche is only triggered when a local variable (a so
called awareness) reaches and goes above a threshold. The dynamical rules are
constrained to be as simple as possible, in order to sort out the basic
features, though more elaborated variants are proposed. Several results are
obtained for a Erd\"os-R\'enyi network and interpreted through simple
analytical laws, scale free or logistic map-like, i.e., (i) the sizes,
durations, and number of avalanches, including the respective distributions,
(ii) the number of times the external field is applied to one possible node
before all nodes are found to be above the threshold, (iii) the number of nodes
still below the threshold and the number of hot nodes (close to threshold) at
each time step.


  The emerging new paradigm of technologies, the internet of things, entails a
process of device miniaturization to combine several functional components,
such as sensors, actuators, and powering elements, in a single individual
on-chip platform. An essential requirement is for the devices to have a small
footprint and thus to be extended over three-dimensions to present adequate
performance. A suitable technique to realize devices of complex architectures
and virtually any size is three-dimensional printing. So far its use has seen
applications exclusively at the macroscale. Here we report the first 3D printed
architectures via robocasting of two-dimensional atomically thin transition
metal dichalcogenides demonstrating their use as miniaturizable
supercapacitors. The structures are fabricated via direct printing of a liquid
ink of chemically exfoliated 2D nanosheets. The 3D printed architectures
present footprints in the mm2 scale and micron-sized features and they
demonstrate mechanical robustness and chemical stability. They exhibit areal
capacitance of 1450 mF/cm2, rivalling and surpassing comparable devices.
Microsupercapacitors comprising two-dimensional atomically thin sheets can
enable miniaturization and upscaleable production technologies for wide-scale
adoption.


  Machine learning has been widely applied to various applications, some of
which involve training with privacy-sensitive data. A modest number of data
breaches have been studied, including credit card information in natural
language data and identities from face dataset. However, most of these studies
focus on supervised learning models. As deep reinforcement learning (DRL) has
been deployed in a number of real-world systems, such as indoor robot
navigation, whether trained DRL policies can leak private information requires
in-depth study. To explore such privacy breaches in general, we mainly propose
two methods: environment dynamics search via genetic algorithm and candidate
inference based on shadow policies. We conduct extensive experiments to
demonstrate such privacy vulnerabilities in DRL under various settings. We
leverage the proposed algorithms to infer floor plans from some trained Grid
World navigation DRL agents with LiDAR perception. The proposed algorithm can
correctly infer most of the floor plans and reaches an average recovery rate of
95.83% using policy gradient trained agents. In addition, we are able to
recover the robot configuration in continuous control environments and an
autonomous driving simulator with high accuracy. To the best of our knowledge,
this is the first work to investigate privacy leakage in DRL settings and we
show that DRL-based agents do potentially leak privacy-sensitive information
from the trained policies.


  Context. We aim to determine the capabilities of the MEGARA@GTC instrument
integral-field unit to study stellar populations and exploit its combination of
high spectral (R \sim 6,000, 12,000 and 20,000) and spatial (0.62") resolutions
within its 12.5"x11.3" field of view. Aims. We pursue to establish a systematic
method through which we can determine the properties of the stellar populations
in the observations made with MEGARA, more specifically within the MEGADES
legacy project and, for this paper, those of the stellar populations of NGC
7025. Methods. We use MEGARA observations of galaxy NGC 7025. We apply
different approaches to estimate the properties of the stellar populations with
the highest possible certainty. Numerous tests were also performed to check the
reliability of the study. Results. All the studies we conduct (both full
spectral fitting and absorption line indices) on the stellar populations of NGC
7025 indicate that the stars that form its bulge have supersolar metallicity
and considerably old ages (\sim 10 Gyr), in general. We determined that the
bulge of NGC 7025 has a mild negative mass-weighted age gradient using three
different combinations of MEGARA spectral setups. Regarding its more detailed
star formation history, our results indicate that, besides a rather constant
star formation at early epochs, a peak in formation history of the stars in the
bulge is also found 3.5-4.5 Gyr ago, partly explaining the mass-weighted age
gradients measured. Conclusions. The scenario presented in NGC 7025 is that of
an isolated galaxy under secular evolution that about 3.5-4.5 Gyr ago likely
experimented a minor merger (mass ratio 1/10) that induced an increase in star
formation and also perturbed the morphology of its outer disc. We report on
different lessons learned for the ongoing exploitation of the MEGADES survey
with GTC.


  According to the world view of macrorealism, the properties of a given system
exist prior to and independent of measurement, which is incompatible with
quantum mechanics. Leggett and Garg put forward a practical criterion capable
of identifying violations of macrorealism, and so far experiments performed on
microscopic and mesoscopic systems have always ruled out in favor of quantum
mechanics. However, a macrorealist can always assign the cause of such
violations to the perturbation that measurements effect on such small systems,
and hence a definitive test would require using non-invasive measurements,
preferably on macroscopic objects, where such measurements seem more plausible.
However, the generation of truly macroscopic quantum superposition states
capable of violating macrorealism remains a big challenge. In this work we
propose a setup that makes use of measurements on the polarization of light, a
property which has been extensively manipulated both in classical and quantum
contexts, hence establishing the perfect link between the microscopic and
macroscopic worlds. In particular, we use Leggett-Garg inequalities and the
criterion of no-signaling in time to study the macrorealistic character of
light polarization for different kinds of measurements, in particular with
different degrees of coarse-graining. Our proposal is non-invasive for coherent
input states by construction. We show for states with well defined photon
number in two orthogonal polarization modes, that there always exists a way of
making the measurement sufficiently coarse-grained so that a violation of
macrorealism becomes arbitrarily small, while sufficiently sharp measurements
can always lead to a significant violation.


  Spin liquids are conventionally described by gauge theories with a vector
gauge field. However, there exists a wider class of spin liquids with higher
rank tensors as the gauge variable. In this work, we focus on (3+1)-dimensional
spin liquids described by U(1) symmetric tensor gauge theories, which have
recently been shown to be stable gapless spin liquids. We investigate the
particle structure of these tensor gauge theories and find that they have deep
connections with the "fracton" models recently discovered by Vijay, Haah, and
Fu. Tensor gauge theories have more conservation laws than the simple charge
conservation law of rank 1 theories. These conservation laws place severe
restrictions on the motion of particles. Particles in some models are fully
immobile (fractons), while other models have particles restricted to motion
along lower-dimensional subspaces.


  Topological superconductors have long been sought for their potential use in
quantum computing. The type-II Weyl semimetal MoTe$_{2}$ is an obvious
candidate, exhibiting a superconducting state below 500 mK at ambient pressure,
but the question remains whether the pairing is conventional $s^{++}$ or
topological $s^{+-}$. The application of external pressure favors the
superconducting state in MoTe$_{2}$ and suppresses the structural transition
from $1T'$ to $T_{d}$. The competition between the two structures leads to a
mixed phase that strongly enhances the disorder present in the system,
remarkably without affecting the superconducting transition temperature, in
contrast to the expectation of $s^{+-}$ pairing superconductivity. Our thorough
analysis of the electrical and Hall resistivities as a function of pressure
yields the most accurate temperature-pressure phase diagram available to date
for MoTe$_{2}$ and a detailed view of the relationship between disorder and
superconductivity, supporting a conventional $s^{++}$ pairing symmetry.


  Electrical resistivity ($\rho$), magnetoresistance (MR), magnetization,
thermopower and Hall effect measurements on the single crystal
Gd$_{2}$PdSi$_3$, crystallizing in an AlB$_2$-derived hexagonal structure are
reported. The well-defined minimum in $\rho$ at a temperature above N\'eel
temperature (T$_N$= 21 K) and large negative MR below $\sim$ 3T$_N$, reported
earlier for the polycrystals, are reproducible even in single crystals. Such
features are generally uncharacteristic of Gd alloys. In addition, we also
found interesting features in other data, e.g., two-step first-order-like
metamagnetic transitions for the magnetic field along [0001] direction. The
alloy exhibits anisotropy in all these properties, though Gd is a S-state ion.


  The performance of Non-orthogonal Multiple Access (NOMA) system dramatically
decreases in the presence of inter-cell interference. This condition gets more
challenging if a smart jammer is interacting in a network. In this paper, the
NOMA power allocation of two independent Base Stations (BSs) against a smart
jammer is, modeled as a sequential game. In this game, at first, each BS as a
leader independently chooses its power allocation strategy. Then, the smart
jammer as the follower selects its optimal strategy based on the strategies of
the BSs. The solutions of this game are, derived under different conditions.
Based on the game-theoretical analysis, three new schemes are proposed for
anti-jamming NOMA power allocation in a two-cell scenario called a) Q-Learning
based Unselfish (QLU) NOMA power allocation scheme, b) Deep Q-Learning based
Unselfish (DQLU) NOMA power allocation scheme, and c) Hot Booting Deep
Q-Learning based Unselfish (HBDQLU) NOMA power allocation scheme. In these
methods the BSs do not coordinate with each other. But our analysis
theoretically predicts that with high probability, the proposed methods will
converge to the optimal strategy from the total network point of view.
Simulation results show the convergence of the proposed schemes and also their
outperformance with respect to the Q-Learning-based Selfish (QLS) NOMA power
allocation method.


  The chemical behaviour of single metal atoms largely depends on the local
coordination environment, including interactions with the substrate and with
the surrounding gas or liquid. However, the key instrumentation for studying
such systems at the atomic scale generally requires high vacuum conditions,
limiting the degree to which the aforementioned environmental parameters can be
investigated. Here we develop a new platform for transmission electron
microscopy investigation of single metal atoms in liquids and study the dynamic
behaviour of individual platinum atoms on the surface of a single layer MoS2
crystal in water. To achieve the record single atom resolution, we introduce a
double liquid cell based on a 2D material heterostructure, which allows us to
submerge an atomically thin membrane with liquid on both sides while
maintaining the total specimen thickness of only ~ 70 nm. By comparison with an
identical specimen imaged under high vacuum conditions, we reveal drastic
differences in the single atom resting sites and atomic hopping behaviour,
demonstrating that in situ imaging conditions are essential to gain complete
understanding of the chemical activity of individual atoms. These findings pave
the way for in situ liquid imaging of chemical processes with single atom
precision.


  The Diabetic Foot Ulcer Challenge 2022 focused on the task of diabetic foot
ulcer segmentation, based on the work completed in previous DFU challenges. The
challenge provided 4000 images of full-view foot ulcer images together with
corresponding delineation of ulcer regions. This paper provides an overview of
the challenge, a summary of the methods proposed by the challenge participants,
the results obtained from each technique, and a comparison of the challenge
results. The best-performing network was a modified HarDNet-MSEG, with a Dice
score of 0.7287.


  In a recent paper we presented the first semi-analytic model of galaxy
formation in which the Thermally-Pulsing Asymptotic Giant Branch phase of
stellar evolution has been fully implemented. Here we address the comparison
with observations, and show how the TP-AGB recipe affects the performance of
the model in reproducing the colours and near-IR luminosities of high-redshift
galaxies. We find that the semi-analytic model with the TP-AGB better matches
the colour-magnitude and colour-colour relations at z ~ 2, both for
nearly-passive and for star-forming galaxies. The model with TP-AGB produces
star-forming galaxies with red V-K colours, thus revising the unique
interpretation of high-redshift red objects as 'red & dead'. We also show that
without the TP-AGB the semi-analytic model fails at reproducing the observed
colours, a situation that cannot be corrected by dust reddening. We also
explore the effect of nebular emission on the predicted colour-magnitude
relation of star-forming galaxies, to conclude that it does not play a
significant role in reddening their colours, at least in the range of
star-formation rates covered by the model. Finally, the rest-frame K-band
luminosity function at z ~ 2.5 is more luminous by almost 1 magnitude. This
indicates that the AGN feedback recipe that is adopted to regulate the
high-mass end of the luminosity function should be sophisticated to take the
effect of the stellar populations into account at high redshifts.


  If a two-level system coupled to a single-mode cavity is strongly driven by
an external laser, instead of a continuous accumulation of photons in the
cavity, oscillations in the mean photon number occur. These oscillations
correspond to peaks of finite width running up and down in the photon number
distribution, reminiscent of wave packets in linear chain models. A single wave
packet is found if the cavity is resonant to the external laser. Here, we show
that for finite detuning multiple packet structures can exist simultaneously,
oscillating at different frequencies and amplitudes. We further study the
influence of dissipative effects resulting in the formation of a stationary
state, which depending on the parameters can be characterized by a bimodal
photon number distribution. While we give analytical limits for the maximally
achievable photon number in the absence of any dissipation, surprisingly,
dephasing processes can push the photon occupations towards higher photon
numbers.


  In this short note we provide a proof of the importance of the connectedness
assumption in the statement of the optimal $p$-compliance problem with length
penalization and in the statement of the constrained form of this problem for
the existence of solutions.


  Computational studies of basic models of strongly-correlated electron systems
can provide guidance in the search for new materials as well as insight into
the physical mechanisms responsible for their properties. Here, we illustrate
this by examining what numerical computations have shown us about the 2-leg
Hubbard ladder.


  Inspired by the newly observed $\Omega_b$ states by the LHCb Collaboration,
we investigate the two-body strong decays of the low-lying $\lambda$-mode
$\Omega_b$ baryons up to $N=2$ shell using the chiral quark model within the
$j$-$j$ coupling scheme. Our results indicate that: (i) the newly observed
states $\Omega_b(6316)^-$ and $\Omega_b(6330)^-$ are good candidates of the
light spin $j=1$ states, while the spin-parity $J^P=1/2^-$ and $J^P=3/2^-$
cannot be distinguished. The other two states, $\Omega_b(6340)$ and
$\Omega_b(6350)$ mostly correspond to the light spin $j=2$ states, while the
spin-parity $J^P=3/2^-$ and $J^P=5/2^-$ cannot be distinguished as well.(ii)
The $2S$ states with spin-parity $J^P=1/2^+$ and $J^P=3/2^+$, respectively,
might be narrow states with a width of $\Gamma<2$ MeV. (iii) The $1D$ states
are not broad and the total decay widths vary from several to dozens of MeV,
which have a good potential to be observed in future experiments.


  "El Cielo de Salamanca" ("The Sky of Salamanca") is a quarter-sphere-shaped
vault 8.70 metres in diameter. It was painted sometime between 1480 and 1493
and shows five zodiacal constellations, three boreal and six austral. The Sun
and Mercury are also represented. It formed part of a three times larger vault
depicting the 48 Ptolemaic constellations and the rest of the planets known at
the time. This was a splendid work of art that covered the ceiling of the first
library of the University of Salamanca, one of the oldest in Europe having
obtained its royal charter in 1218. But it was also a pioneering scientific
work: a planetarium used to teach astronomy, the first of its kind in the
history of Astronomy that has come down to us in the preserved part that we now
call "The Sky of Salamanca". We describe the scientific context surrounding the
chair of Astrology founded around 1460 at the University of Salamanca, which
led to the production of this unique scientific work of art and to the
flourishing of Astronomy in Salamanca. We analyse the possible dates compatible
with it, showing that they are extremely infrequent. In the period of 1100
years from 1200 to 2300 that we studied there are only 23 years that have
feasible days. We conclude that the information contained in "El Cielo de
Salamanca" is not sufficient to assign it to a specific date but rather to an
interval of several days that circumstantial evidence seems to place in August
1475. The same configuration of the sky will be observable, for the first time
in 141 years, from the 22nd to the 25th of August 2022. The next occasion to
observe it live will be in 2060.


  Quantum devices are systems that can explore quantum phenomena, like
entanglement or coherence, for example, to provide some enhancement performance
concerning their classical counterparts. In particular, quantum batteries are
devices that use entanglement as main element in its high performance in the
charging powerful. In this paper, we explore the quantum battery performance
and its relationship with the amount of entanglement that arises during the
charging process. By using a general approach to a two and three-cell battery,
our results suggest that entanglement is not the main resource to quantum
batteries, where there is a non-trivial correlation-coherence trade-off as
resource for the high efficiency of such quantum devices.


  High-frequency response of a system with drifting electrons in a highly doped
graphene and surface polar optical phonons of a polar substrate is considered.
For this interacting system, we obtained a dielectric function, frequencies and
decrement/increment of cooperative plasmon-optical phonon oscillations. We
found, that the response is significantly depends on the degree of
nonequilibrium of the electrons. In particular, interaction between drifting
plasmons and surface polar optical phonons leads to an instability of the
electron subsystem due to Vavilov-Cherenkov effect. We suggest that the hybrid
system - graphene on a polar substrate - is capable to be used in amplifiers or
generators of THz electromagnetic radiation.


  We review the derivation of a noncommutative version of the nonlinear sigma
model on $\CPn$ and it's soliton solutions for finite $\theta$ emphasizing the
similarities it bears to the GMS scalar field theory. It is also shown that
unlike the scalar theory, some care needs to be taken in defining the
topological charge of BPS solitons of the theory due to nonvanishing surface
terms in the energy functional. Finally it is shown that, like its commutative
analogue, the noncommutative $\CPn$-model also exhibits a non-BPS sector.
Unlike the commutative case however, there are some surprises in the
noncommutative case that merit further study.


  We report a new form of compensating accelerating beam generated by amplitude
modulation of the symmetric Airy beam (SAB) caustics with an exponential
apodization mask. Our numerical study manifests that the compensating beam is
with one main-lobe beam structure and can maintain the mean-intensity invariant
both in the free space and loss media. Specially, the beam inherits the
beamlets structure from the SAB and owns a novel damped oscillating propagation
property. We also conduct a comparative study of its propagation property with
that of the Airy beam theoretically. And by altering the signs of 2D masks, the
main lobe of the compensating beam can be modulated to orientate in four
different quadrants flexibly. The proposed compensating accelerating beam is
anticipated to get special applications in particle manipulation or plasmas
regions.


  The production of charmed and beauty hadrons in proton-proton and
proton-antiproton collisions at high energies is analyzed within the modified
quark-gluon string model (QGSM) including the internal motion of quarks in
colliding hadrons. It is shown that using both the QGSM and NLO QCD one can
describe the experimental data rather successfully in a wide region of
transverse momenta. We also present some predictions for the future experiments
on the beauty baryon production in $pp$ collisions at LHC energies and on the
charmed meson production in ${\bar p}p$ reactions at GSI energies.


  Sidon sets are those sets such that the sums of two of its elements never
coincide. They go back to the 30s when Sidon asked for the maximal size of a
subset of consecutive integers with that property. This question is now
answered in a satisfactory way. Their natural generalization, called B 2 [g]
sets and defined by the fact that there are at most g ways (up to reordering
the summands) to represent a given integer as a sum of two elements of the set,
are much more difficult to handle and not as well understood. In this article,
using a numerical approach, we improve the best upper estimates on the size of
a B 2 [g] set in an interval of integers in the cases g = 2, 3, 4 and 5.


  In a well-known 1914 paper, Ramanujan gave a number of rapidly converging
series for $1/\pi$ which are derived using modular functions of higher level.
D. V. and G. V. Chudnovsky in their 1988 paper derived an analogous series
representing $1/\pi$ using the modular function $J$ of level 1, which results
in highly convergent series for $1/\pi$, often used in practice. In this paper,
we explain the Chudnovsky method in the context of elliptic curves, modular
curves, and the Picard-Fuchs differential equation. In doing so, we also
generalize their method to produce formulae which are valid around any singular
point of the Picard-Fuchs differential equation. Applying the method to the
family of elliptic curves parameterized by the absolute Klein invariant $J$ of
level 1, we determine all Chudnovsky-Ramanujan type formulae which are valid
around one of the three singular points: $0, 1, \infty$.


  There are lots of new physics models which predict an extra neutral gauge
boson, referred as Z'-boson. In a certain class of these new physics models,
the Z'-boson has flavor-dependent couplings with the fermions in the Standard
Model (SM). Based on a simple model in which couplings of the SM fermions in
the third generation with the Z'-boson are different from those of the
corresponding fermions in the first two generations, we study the signatures of
Z'-boson at the Large Hadron Collider (LHC) and the International Linear
Collider (ILC). We show that at the LHC, the Z'-boson with mass around 1 TeV
can be produced through the Drell-Yan processes and its dilepton decay modes
provide us clean signatures not only for the resonant production of Z'-boson
but also for flavor-dependences of the production cross sections. We also study
fermion pair productions at the ILC involving the virtual Z'-boson exchange.
Even though the center-of-energy of the ILC is much lower than a Z'-boson mass,
the angular distributions and the forward-backward asymmetries of fermion pair
productions show not only sizable deviations from the SM predictions but also
significant flavor-dependences.


  In this work, the room temperature polar vapor sensing behavior of two
dimentional (2D) heterojunction Graphene-TiS3 materials and TiS3 nanoribbons is
investigated. TiS3 nanoribbons were synthesized via chemical vapor transport
(CVT) and their structure was investigated by scanning electron microscopy
(SEM), high resolution transmission electron microscopy (HRTEM), energy
dispersive X- ray spectroscopy (EDS), X-ray diffraction (XRD), Raman
spectroscopy and Fourier transform infrared spectroscopy (FT-IR) analysis. The
gas sensing performance of the TiS3 nanoribbons was assessed through the
observed changes in their electronic behavior. Sensing devices were fabricated
with gold contacts and with lithographically patterned graphene (Gr) electrodes
in a 2D heterojunction Gr-TiS3-Gr architecture.. It is observed that the gold
contacted TiS3 device has a rather linear I-V behavior while the Gr-TiS3-Gr
heterojunction forms a contact with a higher Schottky barrier (250 meV). I-V
responses of the sensors were recorded at room temperature with a relative
humidity of 55% and for different ethanol vapor concentrations (varying from 2
to 20 ppm). I-V plots indicated an increase in the resistance of Gr-TiS3-Gr by
the adsorption of water and ethanol molecules with relatively high sensing
response (~3353% at 2 ppm). Our results reveal that selective and stable
responses to a low concentration of ethanol vapor (2 ppm) can be achieved at
room temperature with transient response and recovery times of around 6 s and
40 s, respectively. Our proposed design demonstrate a new approach for
selective molecular recognition using polar interactions between analyte vapors
and heterojunctions of 2D-materials.


  A quantum advantage can be achieved in the unitary charging of quantum
batteries if their cells are interacting. Here, we try to clarify with some
analytical calculations whether and how this quantum advantage is achieved for
sparse Sachdev-Ye-Kitaev (SYK) interactions and in general for fermionic
interactions with disorder. To do this we perform a simple modelization of the
interactions. In particular, we find that for $q$-point rescaled sparse SYK
interactions the quantum advantage goes as $\Gamma\sim
N^{\frac{\alpha-q}{2}+1}$ for $\alpha\geq q/2$ and $\Gamma\sim
N^{1-\frac{\alpha}{2}}$ for $q/2>\alpha\geq 0$, where $\alpha$ is related to
the connectivity and $N$ is the number of cells.


  Grain segregation occurs under various conditions, such as vibration, shear
and mixing. In the gravity-driven shear flow, size segregation is triggered by
the percolation of small particles through the opened voids (kinetic sieving),
and large particles are accumulated in the upper layer. One hypothesis for the
upward migration of large particles is the squeeze expulsion mechanism, which
remains yet ambiguous due to limited evidences from either physical or
numerical experiments. Here we show statistically how the percolation of small
particles facilitates the upward movement of large particles. We found that in
large particles, the mechanical anisotropy (strong force network) coincides
with the geometric anisotropy (contact network), which indicates squeeze, and
the connectivity of large particles is much higher when they are squeezed
through small particles. The presence of small particles filling the voids
hinders the downward movements and provides dynamic steps for the climbing
large particles. Furthermore, increasing the coefficient of friction promotes
rotation and empowers more large particles to reach the top layer, implying
that the climbing particles tend to rotate relative to their neighbors. Our
findings of the microstructure and movement pattern of individual particles add
new evidences to the mechanism of squeeze expulsion and provide new perspective
for the study of segregation.


  Pseudo-parabolic equations have been used to model unsaturated fluid flow in
porous media. In this paper it is shown how a pseudo-parabolic equation can be
upscaled when using a spatio-temporal decomposition employed in the
Peszyn'ska-Showalter-Yi paper [8]. The spatial-temporal decomposition
transforms the pseudo-parabolic equation into a system containing an elliptic
partial differential equation and a temporal ordinary differential equation. To
strengthen our argument, the pseudo-parabolic equation has been given
advection/convection/drift terms. The upscaling is done with the technique of
periodic homogenization via two-scale convergence. The well-posedness of the
extended pseudo-parabolic equation is shown as well. Moreover, we argue that
under certain conditions, a non-local-in-time term arises from the elimination
of an unknown.


  In this series of lectures we review observational evidence for, and
theoretical investigations into, cosmic acceleration and dark energy. The notes
are in four sections. First I review the basic cosmological formalism to
describe the expansion history of the universe and how distance measures are
defined. The second section covers the evidence for cosmic acceleration from
cosmic distance measurements. Section 3 discusses the theoretical avenues being
considered to explain the cosmological observations and section 4 discusses how
the growth of inhomogeneities and large scale structure observations might help
us pin down the theoretical origin of cosmic acceleration.


  We investigate the quantum Hall (QH) states near the charge neutral Dirac
point of a high mobility graphene sample in high magnetic fields. We find that
the QH states at filling factors $\nu=\pm1$ depend only on the perpendicular
component of the field with respect to the graphene plane, indicating them to
be not spin-related. A non-linear magnetic field dependence of the activation
energy gap at filling factor $\nu=1$ suggests a many-body origin. We therefore
propose that the $\nu=0$ and $\pm1$ states arise from the lifting of the spin
and sub-lattice degeneracy of the $n=0$ LL, respectively.


  X-ray observations of three Shakhbazyan's Compact Groups of Galaxies, SCGG
202, SCGG 205, and SCGG 223, are presented for the first time. Extended X-ray
emission was detected from SCGG 202 and SCGG 223 with 0.5-2 keV luminosity of
1E42 erg/s and 3E42 erg/s (for H_0 = 75 km/s/Mpc), respectively, while no
significant emission was detected from SCGG 205 with an upper limit of 0.7E42
erg/s. The X-ray spectra of SCGG 202 and SCGG 223 can be described with
thin-thermal plasma emission with temperature about 1 keV. X-ray properties of
SCGG 202 and SCGG 223 are in good agreement with those of other known groups of
galaxies, proving the physical nature of their grouping.


  The SSH protocol was designed in the late nineties to cope with the security
problems of the telnetf family of protocols. It brought authentication and
confidentiality to remote access protocols and is now widely used. Almost 30
years after the initial design, we revisit SSH in the light of recent protocols
including QUIC, TLS 1.3 and HTTP/3. We propose, implement and evaluate SSH3, a
protocol that provides an enhanced feature set without compromise compared to
SSHv2. SSH3 leverages HTTP-based authorization mechanisms to enable new
authentication methods in addition to the classical password-based and
private/public key pair authentications. SSH3 users can now configure their
remote server to be accessed through the identity provider of their
organization or using their Google or Github account. Relying on HTTP/3 and the
QUIC protocol, SSH3 offers UDP port forwarding in addition to regular TCP
forwarding as well as a faster and secure session establishment. We implement
SSH3 over quic-go and evaluate its performance.


  We study analytically the constraints of the conformal bootstrap on the
low-lying spectrum of operators in field theories with global conformal
symmetry in one and two spacetime dimensions. We introduce a new class of
linear functionals acting on the conformal bootstrap equation. In 1D, we use
the new basis to construct extremal functionals leading to the optimal upper
bound on the gap above identity in the OPE of two identical primary operators
of integer or half-integer scaling dimension. We also prove an upper bound on
the twist gap in 2D theories with global conformal symmetry. When the external
scaling dimensions are large, our functionals provide a direct point of contact
between crossing in a 1D CFT and scattering of massive particles in large
$\textrm{AdS}_2$. In particular, CFT crossing can be shown to imply that
appropriate OPE coefficients exhibit an exponential suppression characteristic
of massive bound states, and that the 2D flat-space S-matrix should be analytic
away from the real axis.


  Electronic voting systems are essential for holding virtual elections, and
the need for such systems increases due to the COVID-19 pandemic and the social
distancing that it mandates. One of the main challenges in e-voting systems is
to secure the voting process: namely, to certify that the computed results are
consistent with the cast ballots, and that the privacy of the voters is
preserved. We propose herein a secure voting protocol for elections that are
governed by order-based voting rules. Our protocol offers perfect ballot
secrecy, in the sense that it issues only the required output, while no other
information on the cast ballots is revealed. Such perfect secrecy, which is
achieved by employing secure multiparty computation tools, may increase the
voters' confidence and, consequently, encourage them to vote according to their
true preferences. Evaluation of the protocol's computational costs establishes
that it is lightweight and can be readily implemented in real-life electronic
elections.


  In this work, we manipulate the phase shift of a Josephson junction using a
parallel double quantum dot (QD). By employing a superconducting quantum
interference device, we determine how orbital hybridization and detuning affect
the current-phase relation in the Coulomb blockade regime. For weak
hybridization between the QDs, we find $\pi$ junction characteristics if at
least one QD has an unpaired electron. Notably the critical current is higher
when both QDs have an odd electron occupation. By increasing the inter-QD
hybridization the critical current is reduced, until eventually a $\pi$-0
transition occurs. A similar transition appears when detuning the QD levels at
finite hybridization. Based on a zero-bandwidth model, we argue that both cases
of phase-shift transitions can be understood considering an increased weight of
states with a double occupancy in the ground state and with the Cooper pair
transport dominated by local Andreev reflection.


  By using a simulated annealing approach, Monte Carlo and molecular-dynamics
techniques we have studied static and dynamic behavior of the classical
two-dimensional anisotropic Heisenberg model. We have obtained numerically that
the vortex developed in such a model exhibit two different behaviors depending
if the value of the anisotropy $\lambda$ lies below or above a critical value
$\lambda_c$ . The in-plane and out-of-plane correlation functions ($S^{xx}$ and
$S^{zz}$) were obtained numerically for $\lambda < \lambda_c$ and $\lambda >
\lambda_c$ . We found that the out-of-plane dynamical correlation function
exhibits a central peak for $\lambda > \lambda_c$ but not for $\lambda <
\lambda_c$ at temperatures above $T_{BKT}$ .


  In this work, we investigate the dynamics of bouncing cosmologies within the
framework of Weyl-type $f(Q,T)$ gravity. Here, $Q$ represents the non-metricity
of the space-time, is determined by the vector field $w_\mu$, while $T$
represents the trace of the matter energy-momentum tensor. Our objective is to
explore the feasibility of avoiding the Big Bang singularity by implementing a
matter-bounce cosmology. To achieve this, we consider a specific model with the
functional form $f(Q,T)=\alpha Q+\frac{\beta }{6\kappa ^2}T$, where $\alpha$
and $\beta$ are model parameters. We analyze the dynamical parameters
associated with this model and examine the influence of the Weyl-type $f(Q,T)$
theory on these parameters. Moreover, we assess the stability of the proposed
model to ensure its viability as a cosmological scenario. Through our analysis,
we aim to gain insights into the potential implications and consequences of
Weyl-type $f(Q,T)$ gravity for bouncing scenarios, contributing to our
understanding of alternative gravitational theories in the context of
cosmology.