  Password managers have the potential to help users more effectively manage
their passwords and address many of the concerns surrounding password-based
authentication, however prior research has identified significant
vulnerabilities in existing password managers. Since that time, five years has
passed, leaving it unclear whether password managers remain vulnerable or
whether they are now ready for broad adoption. To answer this question, we
evaluate thirteen popular password managers and consider all three stages of
the password manager lifecycle--password generation, storage, and autofill. Our
evaluation is the first analysis of password generation in password managers,
finding several non-random character distributions and identifying instances
where generated passwords were vulnerable to online and offline guessing
attacks. For password storage and autofill, we replicate past evaluations,
demonstrating that while password managers have improved in the half-decade
since those prior evaluations, there are still significant issues, particularly
with browser-based password managers; these problems include unencrypted
metadata, unsafe defaults, and vulnerabilities to clickjacking attacks. Based
on our results, we identify password managers to avoid, provide recommendations
on how to improve existing password managers, and identify areas of future
research.


  We provide performance guarantees for a variant of simulation-based policy
iteration for controlling Markov decision processes that involves the use of
stochastic approximation algorithms along with state-of-the-art techniques that
are useful for very large MDPs, including lookahead, function approximation,
and gradient descent. Specifically, we analyze two algorithms; the first
algorithm involves a least squares approach where a new set of weights
associated with feature vectors is obtained via least squares minimization at
each iteration and the second algorithm involves a two-time-scale stochastic
approximation algorithm taking several steps of gradient descent towards the
least squares solution before obtaining the next iterate using a stochastic
approximation algorithm.


  We compute the stationary in-degree probability, $P_{in}(k)$, for a growing
network model with directed edges and arbitrary out-degree probability. In
particular, under preferential linking, we find that if the nodes have a light
tail (finite variance) out-degree distribution, then the corresponding
in-degree one behaves as $k^{-3}$. Moreover, for an out-degree distribution
with a scale invariant tail, $P_{out}(k)\sim k^{-\alpha}$, the corresponding
in-degree distribution has exactly the same asymptotic behavior only if
$2<\alpha<3$ (infinite variance). Similar results are obtained when
attractiveness is included. We also present some results on descriptive
statistics measures %descriptive statistics such as the correlation between the
number of in-going links, $D_{in}$, and outgoing links, $D_{out}$, and the
conditional expectation of $D_{in}$ given $D_{out}$, and we calculate these
measures for the WWW network. Finally, we present an application to the
scientific publications network. The results presented here can explain the
tail behavior of in/out-degree distribution observed in many real networks.


  The use of classical thermal field to approximate real-time quantum thermal
field theory is discussed. For a \lambda\phi^4 theory, it is shown that the
classical Rayleigh-Jeans divergence can be canceled with the appropriate
counterterms, and a comparison is made between the classical and quantum
perturbative expansion. It is explained why Hard Thermal Loops prevent the same
method to work for gauge theories.


  In the framework of non-relativistic QED, we show that the renormalized mass
of the electron (after having taken into account radiative corrections) appears
as the kinematic mass in its response to an external potential force.
Specifically, we study the dynamics of an electron in a slowly varying external
potential and with slowly varying initial conditions and prove that, for a long
time, it is accurately described by an associated effective dynamics of a
Schr\"odinger electron in the same external potential and for the same initial
data, with a kinetic energy operator determined by the renormalized dispersion
law of the translation-invariant QED model.


  The prevalence and energetics of quasar feedback is a major unresolved
problem in galaxy formation theory. In this paper, we present Gemini Integral
Field Unit observations of ionized gas around eleven luminous, obscured,
radio-quiet quasars at z~0.5 out to ~15 kpc from the quasar; specifically, we
measure the kinematics and morphology of [O III]5007 emission. The round
morphologies of the nebulae and the large line-of-sight velocity widths (with
velocities containing 80% of the emission as high as 1000 km/s combined with
relatively small velocity difference across them (from 90 to 520 km/s) point
toward wide-angle quasi-spherical outflows. We use the observed velocity widths
to estimate a median outflow velocity of 760 km/s, similar to or above the
escape velocities from the host galaxies. The line-of-sight velocity dispersion
declines slightly toward outer parts of the nebulae (by 3% per kpc on average).
The majority of nebulae show blueshifted excesses in their line profiles across
most of their extents, signifying gas outflows. For the median outflow
velocity, we find a kinetic energy flow between 4x10^{44} and 3x10^{45} erg/s
and mass outflow rate between 2000 and 20000 Msun/yr. These values are large
enough for the observed quasar winds to have a significant impact on their host
galaxies. The median rate of converting bolometric luminosity to kinetic energy
of ionized gas clouds is ~2%. We report four new candidates for "super-bubbles"
-- outflows that may have broken out of the denser regions of the host galaxy.


  The Visible Light Photon Counter (VLPC) features high quantum efficiency and
low pulse height dispersion. These properties make it ideal for efficient
photon number state detection. The ability to perform efficient photon number
state detection is important in many quantum information processing
applications, including recent proposals for performing quantum computation
with linear optical elements. In this paper we investigate the unique
capabilities of the VLPC. The efficiency of the detector and cryogenic system
is measured at 543nm wavelengths to be 85%. A picosecond pulsed laser is then
used to excite the detector with pulses having average photon numbers ranging
from 3-5. The output of the VLPC is used to discriminate photon numbers in a
pulse. The error probability for number state discrimination is an increasing
function of the number of photons, due to buildup of multiplication noise. This
puts an ultimate limit on the ability of the VLPC to do number state detection.
For many applications, it is sufficient to discriminate between 1 and more than
one detected photon. The VLPC can do this with 99% accuracy.


  We introduce a new class of zero-dimensional weighted complete intersections,
by abstracting the essential features of rational cohomology algebras of equal
rank homogeneous spaces of compact connected Lie groups. We prove that, on a
1-connected closed manifold M whose rational cohomology algebra belongs to this
class, every isometry has a non-trivial invariant geodesic, for any metric on
M. We use rational surgery to construct large classes of new examples for which
the above result may be applied.


  We discuss the foundations and extend the range of applicability of the
widely used Kubo-Greenwood formula (KGF) for the electronic conductivity. The
conductivity is derived from the current density, and only the probability
amplitude rather than the transition probability is used. It is shown that the
contribution to the conductivity from degenerate states in a low or zero
frequency external electric field and the contribution from states near
resonance with a finite frequency external field are finite. The improved
conductivity expression does not include the familiar "energy conserving" delta
function, and no artificial broadening parameter for delta function is required
for the DC limit. We explored two methods of computing current density. We
discuss the role of many-electron statistics in computing the conductivity in
single-particle approximations, and we show that the conventional KGF is due to
the contribution from single-particle excited states.


  In this paper, we propose a new quantitative method for determining the state
number l of the beam carry Orbital Angular Momentum (OAM), both individually
and in a sum in a combination of l= -3, -2, -1, 0, 1, 2, 3 based on analysis of
the S21 system parameters. This allows the receiving device to be tuned to
receive beams with a specific OAM state. Radio waves carry OAM have a frequency
of 80 GHz. The work is an experiment on a computer model. Simulation of beams
with different states l, as well as determination of S system parameters, is
carried out using the software product SCT Studio, and addition or
superposition of S parameters of beams with different states l was produced by
means of the software product Matlab.


  Bibliometric techniques are not yet widely used to enhance retrieval
processes in digital libraries, although they offer value-added effects for
users. In this paper we will explore how statistical modelling of scholarship,
such as Bradfordizing or network analysis of coauthorship network, can improve
retrieval services for specific communities, as well as for large, cross-domain
large collections. This paper aims to raise awareness of the missing link
between information retrieval (IR) and bibliometrics / scientometrics and to
create a common ground for the incorporation of bibliometric-enhanced services
into retrieval at the digital library interface.


  In this paper we provide a first analysis of the research questions that
arise when dealing with the problem of communicating pieces of formal
argumentation through natural language interfaces. It is a generally held
opinion that formal models of argumentation naturally capture human argument,
and some preliminary studies have focused on justifying this view.
Unfortunately, the results are not only inconclusive, but seem to suggest that
explaining formal argumentation to humans is a rather articulated task.
Graphical models for expressing argumentation-based reasoning are appealing,
but often humans require significant training to use these tools effectively.
We claim that natural language interfaces to formal argumentation systems offer
a real alternative, and may be the way forward for systems that capture human
argument.


  Maps between Riemannian manifolds which are submersions on a dense subset,
are studied by means of the eigenvalues of the pull-back of the target metrics,
the first fundamental form. Expressions for the derivatives of these
eigenvalues yield characterizations of harmonicity, totally geodesic maps and
biconformal changes of metric preserving harmonicity. A Schwarz lemma for
pseudo harmonic morphisms is proved, using the dilatation of the eigenvalues
and, in dimension five, a Bochner technique method, involving the Laplacian of
the difference of the eigenvalues, gives conditions forcing pseudo harmonic
morphisms to be harmonic morphisms.


  In this paper we present ProSLAM, a lightweight stereo visual SLAM system
designed with simplicity in mind. Our work stems from the experience gathered
by the authors while teaching SLAM to students and aims at providing a highly
modular system that can be easily implemented and understood. Rather than
focusing on the well known mathematical aspects of Stereo Visual SLAM, in this
work we highlight the data structures and the algorithmic aspects that one
needs to tackle during the design of such a system. We implemented ProSLAM
using the C++ programming language in combination with a minimal set of well
known used external libraries. In addition to an open source implementation, we
provide several code snippets that address the core aspects of our approach
directly in this paper. The results of a thorough validation performed on
standard benchmark datasets show that our approach achieves accuracy comparable
to state of the art methods, while requiring substantially less computational
resources.


  We investigated whether outward Planetesimal Driven Migration (PDM) takes
place or not in simulations when the self gravity of planetesimals is included.
We performed $N$-body simulations of planetesimal disks with large width (0.7 -
4AU) which ranges over the ice line. The simulations consisted of two stages.
The first stage simulations were carried out to see the runaway growth phase
using the planetesimals of initially the same mass. The runaway growth took
place both at the inner edge of the disk and at the region just outside the ice
line. This result was utilized for the initial setup of the second stage
simulations in which the runaway bodies just outside the ice line were replaced
by the protoplanets with about the isolation mass. In the second stage
simulations, the outward migration of the protoplanet was followed by the
stopping of the migration due to the increase of the random velocity of the
planetesimals. Due to this increase of random velocities, one of the PDM
criteria derived in Minton and Levison (2014) was broken. In the current
simulations, the effect of the gas disk is not considered. It is likely that
the gas disk plays an important role in planetesimal driven migration, and we
plan to study its effect in future papers.


  Galactic, young massive star clusters are approximately coeval aggregates of
stars, close enough to resolve the individual stars, massive enough to have
produced large numbers of massive stars, and young enough for these stars to be
in a pre-supernova state. As such these objects represent powerful natural
laboratories in which to study the evolution of massive stars. To be used in
this way, it is crucial that accurate and precise distances are known, since
this affects both the inferred luminosities of the cluster members and the age
estimate for the cluster itself. Here we present distance estimates for three
star clusters rich in Red Supergiants ($\chi$ Per, NGC 7419 and Westerlund 1)
based on their average astrometric parallaxes $\bar{\pi}$ in Gaia Data Release
2, where the measurement of $\bar{\pi}$ is obtained from a proper-motion
screened sample of spectroscopically-confirmed cluster members. We determine
distances of $d=2.25^{+0.16}_{-0.14}$kpc, $d=3.00^{+0.35}_{-0.29}$kpc, and
$d=3.87^{+0.95}_{-0.64}$kpc for the three clusters respectively. We find that
the dominant source of error is that in Gaia's zero-point parallax offset
$\pi_{\rm ZP}$, and we argue that more precise distances cannot be determined
without an improved characterization of this quantity.


  In this paper we study the Parisi variational problem for mixed $p$-spin
glasses with Ising spins. Our starting point is a characterization of Parisi
measures whose origin lies in the first order optimality conditions for the
Parisi functional, which is known to be strictly convex. Using this
characterization, we study the phase diagram in the temperature-external field
plane. We begin by deriving self-consistency conditions for Parisi measures
that generalize those of de Almeida and Thouless to all levels of Replica
Symmetry Breaking (RSB) and all models. As a consequence, we conjecture that
for all models the Replica Symmetric (RS) phase is the region determined by the
natural analogue of the de Almeida-Thouless condition. We show that for all
models, the complement of this region is in the RSB phase. Furthermore, we show
that the conjectured phase boundary is exactly the phase boundary in the plane
less a bounded set. In the case of the Sherrington-Kirkpatrick model, we extend
this last result to show that this bounded set does not contain the critical
point at zero external field.


  The hidden nature and the limited accessibility of the Dark Web, combined
with the lack of public datasets in this domain, make it difficult to study its
inherent characteristics such as linguistic properties. Previous works on text
classification of Dark Web domain have suggested that the use of deep neural
models may be ineffective, potentially due to the linguistic differences
between the Dark and Surface Webs. However, not much work has been done to
uncover the linguistic characteristics of the Dark Web. This paper introduces
CoDA, a publicly available Dark Web dataset consisting of 10000 web documents
tailored towards text-based Dark Web analysis. By leveraging CoDA, we conduct a
thorough linguistic analysis of the Dark Web and examine the textual
differences between the Dark Web and the Surface Web. We also assess the
performance of various methods of Dark Web page classification. Finally, we
compare CoDA with an existing public Dark Web dataset and evaluate their
suitability for various use cases.


  We present the discovery of a planetary-mass companion to CFHTWIR-Oph 98, a
low-mass brown dwarf member of the young Ophiuchus star-forming region, with a
wide 200-au separation (1.46 arcsec). The companion was identified using Hubble
Space Telescope images, and confirmed to share common proper motion with the
primary using archival and new ground-based observations. Based on the very low
probability of the components being unrelated Ophiuchus members, we conclude
that Oph 98 AB forms a binary system. From our multi-band photometry, we
constrain the primary to be an M9-L1 dwarf, and the faint companion to have an
L2-L6 spectral type. For a median age of 3 Myr for Ophiuchus, fits of
evolutionary models to measured luminosities yield masses of $15.4\pm0.8$
M$_\mathrm{Jup}$ for Oph 98 A and $7.8\pm0.8$ M$_\mathrm{Jup}$ for Oph 98 B,
with respective effective temperatures of $2320\pm40$ K and $1800\pm40$ K. For
possible system ages of 1-7 Myr, masses could range from 9.6-18.4
M$_\mathrm{Jup}$ for the primary, and from 4.1-11.6 M$_\mathrm{Jup}$ for the
secondary. The low component masses and very large separation make this binary
the lowest binding energy system imaged to date, indicating that the outcome of
low-mass star formation can result in such extreme, weakly-bound systems. With
such a young age, Oph 98 AB extends the growing population of young
free-floating planetary-mass objects, offering a new benchmark to refine
formation theories at the lowest masses.


  Quantum mechanics has maintained over the years the reputation of being "the
most obscure theory." It works perfectly well, but nobody seems to know why. It
has been argued that the difficulty in understanding quantum theory is our
failed attempt to force onto it a wrong conceptual scheme, wanting at all costs
to think about the objects of the theory as, precisely, objects, i.e., entities
having continuously actual spatiotemporal properties. This too restrictive
spatiotemporal scheme is most probably at the heart of the problem, as also
underlined by the Einsteinian revolution, but then what could be an
alternative? Many thinkers have suggested that we must surrender to the fact
that our physical world is one of immanent powers and potencies. Aristotle did
so ante quantum litteram, followed by scholars like Heisenberg, Primas,
Shimony, Piron, Kastner, Kauffman, de Ronde, just to name a few, including the
authors, who were both students of Piron in Geneva. However, if on the one hand
a potentiality ontology puts the accent on the processes of change, responsible
for the incessant shifts between actual and potential properties, on the other
hand it does not tell what these changes are all about. In other words, the
metaphysical question remains of identifying the nature of the bearer of these
potencies, or potentialities, and of the entities that can actualize them. It
is the purpose of the present article to emphasize that the above question has
found a possible answer in the recent Conceptuality Interpretation of Quantum
Mechanics, which we believe offers the missing ontology and metaphysics that
can make the theory fully intelligible, and even intuitive.


  In our previous work, we proposed a systematic cross-layer framework for
dynamic multimedia systems, which allows each layer to make autonomous and
foresighted decisions that maximize the system's long-term performance, while
meeting the application's real-time delay constraints. The proposed solution
solved the cross-layer optimization offline, under the assumption that the
multimedia system's probabilistic dynamics were known a priori. In practice,
however, these dynamics are unknown a priori and therefore must be learned
online. In this paper, we address this problem by allowing the multimedia
system layers to learn, through repeated interactions with each other, to
autonomously optimize the system's long-term performance at run-time. We
propose two reinforcement learning algorithms for optimizing the system under
different design constraints: the first algorithm solves the cross-layer
optimization in a centralized manner, and the second solves it in a
decentralized manner. We analyze both algorithms in terms of their required
computation, memory, and inter-layer communication overheads. After noting that
the proposed reinforcement learning algorithms learn too slowly, we introduce a
complementary accelerated learning algorithm that exploits partial knowledge
about the system's dynamics in order to dramatically improve the system's
performance. In our experiments, we demonstrate that decentralized learning can
perform as well as centralized learning, while enabling the layers to act
autonomously. Additionally, we show that existing application-independent
reinforcement learning algorithms, and existing myopic learning algorithms
deployed in multimedia systems, perform significantly worse than our proposed
application-aware and foresighted learning methods.


  Deep feedforward and recurrent networks have achieved impressive results in
many perception and language processing applications. This success is partially
attributed to architectural innovations such as convolutional and long
short-term memory networks. The main motivation for these architectural
innovations is that they capture better domain knowledge, and importantly are
easier to optimize than more basic architectures. Recently, more complex
architectures such as Neural Turing Machines and Memory Networks have been
proposed for tasks including question answering and general computation,
creating a new set of optimization challenges. In this paper, we discuss a
low-overhead and easy-to-implement technique of adding gradient noise which we
find to be surprisingly effective when training these very deep architectures.
The technique not only helps to avoid overfitting, but also can result in lower
training loss. This method alone allows a fully-connected 20-layer deep network
to be trained with standard gradient descent, even starting from a poor
initialization. We see consistent improvements for many complex models,
including a 72% relative reduction in error rate over a carefully-tuned
baseline on a challenging question-answering task, and a doubling of the number
of accurate binary multiplication models learned across 7,000 random restarts.
We encourage further application of this technique to additional complex modern
architectures.


  Music recommender systems are an integral part of our daily life. Recent
research has seen a significant effort around black-box recommender based
approaches such as Deep Reinforcement Learning (DRL). These advances have led,
together with the increasing concerns around users' data collection and
privacy, to a strong interest in building responsible recommender systems. A
key element of a successful music recommender system is modelling how users
interact with streamed content. By first understanding these interactions,
insights can be drawn to enable the construction of more transparent and
responsible systems. An example of these interactions is skipping behaviour, a
signal that can measure users' satisfaction, dissatisfaction, or lack of
interest. In this paper, we study the utility of users' historical data for the
task of sequentially predicting users' skipping behaviour. To this end, we
adapt DRL for this classification task, followed by a post-hoc explainability
(SHAP) and ablation analysis of the input state representation. Experimental
results from a real-world music streaming dataset (Spotify) demonstrate the
effectiveness of our approach in this task by outperforming state-of-the-art
models. A comprehensive analysis of our approach and of users' historical data
reveals a temporal data leakage problem in the dataset. Our findings indicate
that, overall, users' behaviour features are the most discriminative in how our
proposed DRL model predicts music skips. Content and contextual features have a
lesser effect. This suggests that a limited amount of user data should be
collected and leveraged to predict skipping behaviour.


  The excitation function of proton elastic scattering from $^{10}$Be at keV
energy is calculated using the self-consistent Skyrme Hartree-Fock in the
continuum method. The calculation successfully reproduces the narrow
near-threshold proton-emitting resonance ($E_x = 11.4$ MeV, $\Gamma = 6$ keV,
and quantum number $J^{\pi} = 1/2^+$) in $^{11}$B relevant to the
$\beta$-delayed proton emission of $^{11}$Be. This supports the recent
experimental result of Y. Ayyad \textit{et al.} at the ReA3 re-accelerator
facility of the National Superconducting Cyclotron Laboratory (NSCL) at the
Michigan State University. The resonance is interpreted as the $s_{1/2}$
single-proton resonance state in the Skyrme Hartree-Fock mean-field theory.


  Urea titration of RNA by urea is an effective approach to investigate the
forces stabilizing this biologically important molecule. We used all atom
molecular dynamics simulations using two urea force fields and two RNA
constructs to elucidate in atomic detail the destabilization mechanism of
folded RNA in aqueous urea solutions. Urea denatures RNA by forming multiple
hydrogen bonds with the RNA bases and has little influence on the
phosphodiester backbone. Most significantly we discovered that urea engages in
stacking interactions with the bases. We also estimate, for the first time,
m-value for RNA, which is a measure of the strength of urea-RNA interactions.
Our work provides a conceptual understanding of the mechanism by which urea
enhances RNA folding rates.


  We announce a detailed investigation of limits of N-soliton solutions of the
Korteweg-deVries (KdV) equation as $N$ tends to infinity. Our main results
provide new classes of KdV-solutions including in particular new types of
soliton-like (reflectionless) solutions. As a byproduct we solve an inverse
spectral problem for one-dimensional Schr\"odinger operators and explicitly
construct smooth and real-valued potentials that yield a purely absolutely
continuous spectrum on the nonnegative real axis and give rise to an eigenvalue
spectrum that includes any prescribed countable and bounded subset of the
negative real axis.


  Leptoquarks are prime candidates for explaining the intriguing hints for
lepton flavour universality violation. In particular, the $SU(2)_L$ doublet of
scalar leptoquarks $S_2$ is capable of providing an explanation for the
tensions between the measurements and the Standard Model predictions in
$(g-2)_\mu$, $b\to s\ell^+ \ell^-$ and $b\to c\tau\nu$ processes, as well as in
non-resonant di-electron production. However, in the minimal setup with a
single leptoquark generation, a common explanation for all these issues is not
possible as this would lead to unacceptably large charged lepton flavour
violation. We therefore propose a model with three generations of $S_2$, each
coupling exclusively to a single lepton flavour, \textit{i.e.}~a model
extending the Standard Model particle content by an electroquark, a muoquark
and a tauquark. We show that after taking into account other constraints, such
as those originating from electroweak precision observables and $\Delta F=2$
processes, it is possible to provide a combined explanation for all these hints
of lepton flavour universality violation. Moreover, we find that the presence
of the tauquark can generate a dimension-six ${\cal O}_9^U$ operator via
off-shell photon penguin diagrams, which, together with the muoquark
contribution, further improves the global fit to $b \to s \ell^+ \ell^-$ data.


  An emergent quantized field enriches quantum many-body systems. We propose an
antiparticle analog of the exciton in semimetals as an emergent collective mode
in interacting electron systems. We show that inter-band excitations in
semimetals are generally comprised of both excitons and antiparticles of
excitons. These two stand for two distinct inter-band collective modes in
semimetals, having different energies and opposite conserved charges. The
conserved charge here is a quantity conjugate to a joint U(1) symmetry of two
electron's bands associated with the inter-band excitations. The opposite
charges foster fertile scattering processes among the inter-band collective
modes. In spin-polarized systems, they also suggest possible experimental
detections of the antiparticles. We clarify that the effective theory of the
inter-band excitations is given by a generalized Klein-Gordon theory. Our
theory provides a comprehensive understanding of excitonic spectra in generic
semimetals, bringing a new insight into electronic collective phenomena in
solids.


  For sufficiently high dimensions, the naturally graded nonsplit nilpotent Lie
algebras with linear characteristic sequence are classified.


  In this paper we find the general (i.e. valid for arbitrary values of the
winding number) form of the gauge zero-modes, in the adjoint representation,
for theories living on manifolds of the ALE type.


  We design an ingenious scheme to realize the Haldane's quantum Hall model
without Landau level by using ultracold atoms trapped in an optical lattice.
Three standing-wave laser beams are used to construct a wanted honeycomb
lattice, where different on-site energies in two sublattices required in the
Haldane's model can be implemented through tuning the phase of one of the laser
beams. The staggered magnetic field is generated from the Berry phase
associated with the atom moving in a region with other three standing-wave
laser beams. Moreover, we establish a relation between the Hall conductivity
and the equilibrium atomic density upon turning on a stimulated uniform
magnetic field, which enables us to detect the topological Chern number with
the density profile measurement technique that is typically used in ultracold
atoms experiments.


  In this essay, we discuss the fine-tuning problems of the Higgs mass and the
cosmological constant. We argue that these are indeed legitimate problems, as
opposed to some other "problems" that are sometimes described using similar
vocabulary. We then notice, following Tom Banks, that the problems become less
compelling once we recognize that the Universe contains quantum gravity, and
thus isn't fundamentally described by bulk QFT. Embracing this "solution"
requires a reversal of the standard arrows UV->IR and past->future. The first
reversal is familiar from AdS/CFT. The second reversal refers more specifically
to our Universe's cosmology, and is clearly in potential conflict with the
Second Law of Thermodynamics. In the final part of the essay, we attempt to
defuse this conflict, suggesting that the Second Law can arise naturally from
de Sitter boundary conditions at future infinity.


  The notion of curvature on graphs has recently gained traction in the
networks community, with the Ollivier-Ricci curvature (ORC) in particular being
used for several tasks in network analysis, such as community detection. In
this work, we choose a different approach and study augmentations of the
discretization of the Ricci curvature proposed by Forman (AFRC). We empirically
and theoretically investigate its relation to the ORC and the un-augmented
Forman-Ricci curvature. In particular, we provide evidence that the AFRC
frequently gives sufficient insight into the structure of a network to be used
for community detection, and therefore provides a computationally cheaper
alternative to previous ORC-based methods. Our novel AFRC-based community
detection algorithm is competitive with an ORC-based approach.


  We present globally regular vortex-type solutions for a pure SU(2) Yang-Mills
field coupled to gravity in 3+1 dimensions. These gravitating vortices are
static, cylindrically symmetric and purely magnetic, and they support a
non-zero chromo-magnetic flux through their cross section. In addition, they
carry a constant non-Abelian current, and so in some sense they are analogs of
the superconducting cosmic strings. They have a compact central core dominated
by a longitudinal magnetic field and endowed with an approximately Melvin
geometry. This magnetic field component gets color screened in the exterior
part of the core, outside of which the fields approach exponentially fast those
of the electrovacuum Bonnor solutions with a circular magnetic field. In the
far field zone the solutions are not asymptotically flat but tend to vacuum
Kasner metrics.


  We study in this paper the well-posedness and stability for two linear
Schr\"odinger equations in $d$-dimensional open bounded domain under Dirichlet
boundary conditions with an infinite memory. First, we establish the
well-posedness in the sens of semigroup theory. Then, a decay estimate
depending on the smoothness of initial data and the arbitrarily growth at
infinity of the relaxation function is established for each equation with the
help of multipliers method.


  We introduce and investigate symmetric operators $L_0$ associated in the
complex Hilbert space $L^2(\mathbb{R})$ with a formal differential expression
\[l[u] :=-(pu')'+qu + i((ru)'+ru') \] under minimal conditions on the
regularity of the coefficients. They are assumed to satisfy conditions
\[q=Q'+s;\quad \frac{1}{\sqrt{|p|}}, \frac{Q}{\sqrt{|p|}}, \frac{r}{\sqrt{|p|}}
\in L^2_{loc}\left(\mathbb{R}\right), \quad s \in
L^1_{loc}\left(\mathbb{R}\right), \quad\frac{1}{p}\neq 0\,\,\text{a.e.,} \]
where the derivative of the function $Q$ is understood in the sense of
distributions, and all functions $p$, $Q$, $r$, $s$ are real-valued. In
particular, the coefficients $q$ and $r'$ may be Radon measures on
$\mathbb{R}$, while function $p$ may be discontinuous. The main result of the
paper are constructive sufficient conditions on the coefficient $p$ which
provide that the operator $L_0$ being semi-bounded implies it being
self-adjoint.


  Robotic applications require both correct task performance and compensation
for undefined behaviors. Although deep learning is a promising approach to
perform complex tasks, the response to undefined behaviors that are not
reflected in the training dataset remains challenging. In a human-robot
collaborative task, the robot may adopt an unexpected posture due to collisions
and other unexpected events. Therefore, robots should be able to recover from
disturbances for completing the execution of the intended task. We propose a
compensation method for undefined behaviors by switching between two
controllers. Specifically, the proposed method switches between learning-based
and model-based controllers depending on the internal representation of a
recurrent neural network that learns task dynamics. We applied the proposed
method to a pick-and-place task and evaluated the compensation for undefined
behaviors. Experimental results from simulations and on a real robot
demonstrate the effectiveness and high performance of the proposed method.


  This work presents a use case of federated learning (FL) applied to
discovering a maze with LiDAR sensors-equipped robots. Goal here is to train
classification models to accurately identify the shapes of grid areas within
two different square mazes made up with irregular shaped walls. Due to the use
of different shapes for the walls, a classification model trained in one maze
that captures its structure does not generalize for the other. This issue is
resolved by adopting FL framework between the robots that explore only one maze
so that the collective knowledge allows them to operate accurately in the
unseen maze. This illustrates the effectiveness of FL in real-world
applications in terms of enhancing classification accuracy and robustness in
maze discovery tasks.


  In this paper some quite simple examples of applications of the zeta-function
regularization to superstring theories are presented. It is shown that the
Virasoro anomaly in the BRST formulation of (super)strings can be directly
computed from the original expressions of the operators as well as normal
ordering constants and masses of ground levels. Hawking's zeta regularization
is recognized as an efficient tool for direct calculations, bringing no
ambiguities.
  Possible implications for global GSO operators' phases definitions (maybe
ensuring modular invariance) will be discussed elsewhere.


  Creating realistic or stylized facial and lip sync animation is a tedious
task. It requires lot of time and skills to sync the lips with audio and convey
the right emotion to the character's face. To allow animators to spend more
time on the artistic and creative part of the animation, we present Audio2Rig:
a new deep learning based tool leveraging previously animated sequences of a
show, to generate facial and lip sync rig animation from an audio file. Based
in Maya, it learns from any production rig without any adjustment and generates
high quality and stylized animations which mimic the style of the show.
Audio2Rig fits in the animator workflow: since it generates keys on the rig
controllers, the animation can be easily retaken. The method is based on 3
neural network modules which can learn an arbitrary number of controllers.
Hence, different configurations can be created for specific parts of the face
(such as the tongue, lips or eyes). With Audio2Rig, animators can also pick
different emotions and adjust their intensities to experiment or customize the
output, and have high level controls on the keyframes setting. Our method shows
excellent results, generating fine animation details while respecting the show
style. Finally, as the training relies on the studio data and is done
internally, it ensures data privacy and prevents from copyright infringement.


  We show the complete cancellation of gauge and gravitational anomalies in the
M-theory of Horava and Witten using their boundary contribution, and a term
coming from the existence of two and five-branes. A factor of three discrepancy
noted in an earlier work is resolved. We end with a comment on flux
quantization.


  It is well-known that there is no universal metric for image quality
evaluation. In this case, distortion-specific metrics can be more reliable. The
artifact imposed by image compression can be considered as a combination of
various distortions. Depending on the image context, this combination can be
different. As a result, Generalization can be regarded as the major challenge
in compressed image quality assessment. In this approach, stacking is employed
to provide a reliable method. Both semantic and low-level information are
employed in the presented IQA to predict the human visual system. Moreover, the
results of the Full-Reference (FR) and No-Reference (NR) models are aggregated
to improve the proposed Full-Reference method for compressed image quality
evaluation. The accuracy of the quality benchmark of the clic2024 perceptual
image challenge was achieved 79.6\%, which illustrates the effectiveness of the
proposed fusion-based approach.


  We present measurements of the singly ionized helium to hydrogen ratio
($n_{He^+}/n_{H^+}$) toward diffuse gas surrounding three Ultra-Compact HII
(UCHII ) regions: G10.15-0.34, G23.46-0.20 \& G29.96-0.02. We observe radio
recombination lines (RRLs) of hydrogen and helium near 5 GHz using the GBT to
measure the $n_{He^+}/n_{H^+}$ ratio. The measurements are motivated by the low
helium ionization observed in the warm ionized medium (WIM) and in the inner
Galaxy diffuse ionized regions (DIR). Our data indicate that the helium is not
uniformly ionized in the three observed sources. Helium lines are not detected
toward a few observed positions in sources G10.15-0.34 \& G23.46-0.20 and the
upper limits of the $n_{He^+}/n_{H^+}$ ratio obtained are 0.03 and 0.05
respectively. The selected sources harbor stars of type O6 or hotter as
indicated by helium line detection toward the bright radio continuum emission
from the sources with mean $n_{He^+}/n_{H^+}$ value 0.06$\pm$0.02. Our data
thus show that helium in diffuse gas located a few pc away from the young
massive stars embedded in the observed regions is not fully ionized.We
investigate the origin of the non-uniform helium ionization and rule out the
possibilities : (a) that the helium is doubly ionized in the observed regions
and (b) that the low $n_{He^+}/n_{H^+}$ values are due to additional hydrogen
ionizing radiation produced by accreting low-mass stars (Smith 2014). We find
that selective absorption of ionizing photons by dust can result in low helium
ionization but needs further investigation to develop a self-consistent model
for dust in HII regions.


  In order to study the influence of compactness on low-energy properties, we
compare the phase structures of the compact and non-compact two-dimensional
multi-frequency sine-Gordon models. It is shown that the high-energy scaling of
the compact and non-compact models coincides, but their low-energy behaviors
differ. The critical frequency $\beta^2 = 8\pi$ at which the sine-Gordon model
undergoes a topological phase transition is found to be unaffected by the
compactness of the field since it is determined by high-energy scaling laws.
However, the compact two-frequency sine-Gordon model has first and second order
phase transitions determined by the low-energy scaling: we show that these are
absent in the non-compact model.


  We propose a semiparametric model for autonomous nonlinear dynamical systems
and devise an estimation procedure for model fitting. This model incorporates
subject-specific effects and can be viewed as a nonlinear semiparametric mixed
effects model. We also propose a computationally efficient model selection
procedure. We show by simulation studies that the proposed estimation as well
as model selection procedures can efficiently handle sparse and noisy
measurements. Finally, we apply the proposed method to a plant growth data used
to study growth displacement rates within meristems of maize roots under two
different experimental conditions.


  A theory of combined interference and interaction effects on the diffusive
transport properties of 3D topological insulator surface states is developed.
We focus on a slab geometry (characteristic for most experiments) and show that
interactions between the top and bottom surfaces are important at not too high
temperatures. We treat the general case of different surfaces (different
carrier densities, uncorrelated disorder, arbitrary dielectric environment,
etc.). In order to access the low-energy behavior of the system we renormalize
the interacting diffusive sigma model in the one loop approximation. It is
shown that intersurface interaction is relevant in the renormalization group
(RG) sense and the case of decoupled surfaces is therefore unstable. An
analysis of the emerging RG flow yields a rather rich behavior. We discuss
realistic experimental scenarios and predict a characteristic non-monotonic
temperature dependence of the conductivity. In the infrared (low-temperature)
limit, the systems flows into a metallic fixed point. At this point, even
initially different surfaces have the same transport properties. Investigating
topological effects, we present a local expression of the $\mathbb Z_2$ theta
term in the sigma model by first deriving the Wess-Zumino-Witten theory for
class DIII by means of non-abelian bosonization and then breaking the symmetry
down to AII. This allows us to study a response of the system to an external
electromagnetic field. Further, we discuss the difference between the system of
Dirac fermions on the top and bottom surfaces of a topological insulator slab
and its non-topological counterpart in a double-well structure with strong
spin-orbit interaction.


  In this paper, we extend and complete the classification of the generic
singularities of the 3D-contact sub-Riemmanian conjugate locus in a
neighbourhood of the origin.


  Time-relevant and accurate threat information from public domains are
essential for cyber security. In a constantly evolving threat landscape, such
information assists security researchers in thwarting attack strategies. In
this work, we collect and analyze threat-related information from Twitter to
extract intelligence for proactive security. We first use a convolutional
neural network to classify the tweets as containing or not valuable threat
indicators. In particular, to gather threat intelligence from social media, the
proposed approach collects pertinent Indicators of Compromise (IoCs) from
tweets, such as IP addresses, URLs, File hashes, domain addresses, and CVE IDs.
Then, we analyze the IoCs to confirm whether they are reliable and valuable for
threat intelligence using performance indicators, such as correctness,
timeliness, and overlap. We also evaluate how fast Twitter shares IoCs compared
to existing threat intelligence services. Furthermore, through machine learning
models, we classify Twitter accounts as either automated or human-operated and
delve into the role of bot accounts in disseminating cyber threat information
on social media. Our results demonstrate that Twitter is growing into a
powerful platform for gathering precise and pertinent malware IoCs and a
reliable source for mining threat intelligence.


  We study the large-N limit of a system of N bosons interacting with a
potential of intensity 1/N. When the ground state energy is to the first order
given by Hartree's theory, we study the next order, predicted by Bogoliubov's
theory. We show the convergence of the lower eigenvalues and eigenfunctions
towards that of the Bogoliubov Hamiltonian (up to a convenient unitary
transform). We also prove the convergence of the free energy when the system is
sufficiently trapped. Our results are valid in an abstract setting, our main
assumptions being that the Hartree ground state is unique and non-degenerate,
and that there is complete Bose-Einstein condensation on this state. Using our
method we then treat two applications: atoms with ''bosonic'' electrons on one
hand, and trapped 2D and 3D Coulomb gases on the other hand.


  The sacred landscape of the Inka capital Cusco was conceived in accordance
with a complex cosmographic view in which religion and astronomy were
intimately connected. Some previously unnoticed possibilities in interpreting
these connections are proposed.


  Let $X$ be a smooth projective variety of Albanese fiber dimension 1 and of
general type. We prove that the translates through 0 of all components of
$V^0(\omega_X)$ generate $\Pic^0(X)$. We then study the pluricanonical maps of
$X$. We show that $|4K_X|$ induces a birational map.


  The bright disk of RX J1604 has a very simple axisymmetric structure and is
well suited as a benchmark object for accurate photo-polarimetric measurements.
We used archival data of RX J1604 from the ESO archive and carefully corrected
the polarization signal for instrumental effects, also taking the interstellar
polarization into account. We derive accurate radial disk profiles for the
intrinsic polarized intensity, ${\hat{Q}}_{\varphi}(r)/I_{\star}$, and measure
different profile peak radii for different bands because of the wavelength
dependence of the dust opacity. The disk-integrated polarization is
$\hat{Q}_{\varphi}/I_{\star} = 0.92 \pm 0.04\%$ for the R band and $1.51 \pm
0.11\%$ for the J band, indicating a red color for the polarized reflectivity
of the disk. The intensity of the disk is $I_{\rm disk}/I_{\star} = 3.9 \pm 0.5
\%$ in the J band, and the fractional polarization is $\hat{p}_{\varphi} = 38
\pm 4\%$ for the J band and $42 \pm 2\%$ for the H band. The comparison with
the IR excess for RX J1604 yields an apparent disk albedo of about $\Lambda_{I}
\approx 0.16 \pm 0.08$. We also find that previously described shadows seen in
the R band data are likely affected by calibration errors. Using dust
scattering models for transition disks, We derive approximate J band values for
the scattering albedo $\omega \approx 0.5$, scattering asymmetry $g \approx
0.5$, and scattering polarization $p_{\rm max} \approx 0.7$ for the dust. The
positive R to J band color for the polarized reflectivity is mainly a result of
the wavelength dependence of dust parameters because the scattering geometry is
expected to be very similar for different colors. This work demonstrates the
potential of accurate photo-polarimetric measurements of the circumstellar disk
RX J1604 for the determination of dust scattering parameters that strongly
constrain the physical properties of the dust.


  Let A be a commutative unital algebra over an algebraically closed field k of
characteristic not equal to 2, whose generators form a finite-dimensional
subspace V, with no nontrivial homogeneous quadratic relations. Let Q be a Hopf
algebra that coacts on A inner-faithfully, while leaving V invariant. We prove
that Q must be commutative when either: (i) the coaction preserves a
non-degenerate bilinear form on V; or (ii) Q is co-semisimple,
finite-dimensional, and char(k)=0.


  There are two approaches to projective representation theory of symmetric and
alternating groups, which are powerful enough to work for modular
representations. One is based on Sergeev duality, which connects projective
representation theory of the symmetric group and representation theory of the
algebraic supergroup $Q(n)$ via appropriate Schur (super)algebras and Schur
functors.
  The second approach follows the work of Grojnowski for classical affine and
cyclotomic Hecke algebras and connects projective representation theory of
symmetric groups in characteristic $p$ to the crystal graph of the basic module
of the twisted affine Kac-Moody algebra of type $A_{p-1}^{(2)}$.
  The goal of this work is to connect the two approaches mentioned above and to
obtain new branching results for projective representations of symmetric
groups. This is achieved by developing the theory of lowering operators for the
supergroup $Q(n)$ which is parallel to (although much more intricate than) the
similar theory for $GL(n)$ developed by the first author. The theory of
lowering operators for $GL(n)$ is a non-trivial generalization of Carter's work
in characteristic zero, and it has received a lot of attention. So this part of
our work might be of independent interest.
  One of the applications of lowering operators is to tensor products of
irreducible $Q(n)$-modules with natural and dual natural modules, which leads
to important special translation functors. We describe the socles and primitive
vectors in such tensor products.


  In this paper we explore a family of type isomorphisms in System F whose
validity corresponds, semantically, to some form of the Yoneda isomorphism from
category theory. These isomorphisms hold under theories of equivalence stronger
than beta-eta-equivalence, like those induced by parametricity and
dinaturality. We show that the Yoneda type isomorphisms yield a rewriting over
types, that we call Yoneda reduction, which can be used to eliminate
quantifiers from a polymorphic type, replacing them with a combination of
monomorphic type constructors. We establish some sufficient conditions under
which quantifiers can be fully eliminated from a polymorphic type, and we show
some application of these conditions to count the inhabitants of a type and to
compute program equivalence in some fragments of System F.


  In this work we review some features of topological defects in field theory
models for real scalar fields. We investigate topological defects in models
involving one and two or more real scalar fields. In models involving a single
field we examine two different subclasses of models, which support one or more
topological defects. In models involving two or more real scalar fields, we
explore the presence of defects that live inside topological defects, and
junctions and networks of defects. In the case of junctions of defects we
investigte structures that simulate nanotubes and fulerenes. Our investigations
may also be used to describe nonlinear properties of polymers, Langmuir films
and optical solitons in fibers.


  Uncertainty visualizations often emphasize point estimates to support
magnitude estimates or decisions through visual comparison. However, when
design choices emphasize means, users may overlook uncertainty information and
misinterpret visual distance as a proxy for effect size. We present findings
from a mixed design experiment on Mechanical Turk which tests eight uncertainty
visualization designs: 95% containment intervals, hypothetical outcome plots,
densities, and quantile dotplots, each with and without means added. We find
that adding means to uncertainty visualizations has small biasing effects on
both magnitude estimation and decision-making, consistent with discounting
uncertainty. We also see that visualization designs that support the least
biased effect size estimation do not support the best decision-making,
suggesting that a chart user's sense of effect size may not necessarily be
identical when they use the same information for different tasks. In a
qualitative analysis of users' strategy descriptions, we find that many users
switch strategies and do not employ an optimal strategy when one exists.
Uncertainty visualizations which are optimally designed in theory may not be
the most effective in practice because of the ways that users satisfice with
heuristics, suggesting opportunities to better understand visualization
effectiveness by modeling sets of potential strategies.


  There is an enormous potential in applying conjugated polymers in novel
organic opto-electronic devices such as light emitting diodes and solar cells.
Although prototypes and first products exist, a comprehensive understanding of
the fundamental processes and energetics involved during photoexcitation is
still lacking and limits further device optimisations. Here we report on a
unique analysis of the excited states involved in charge generation by
photoexcitation. On the model system poly(3-hexylthiophene) (P3HT), we
demonstrate the general applicability of our novel approach. From photoemission
spectroscopy of occupied and unoccupied states we determine the transport gap
to 2.6 eV, which we show to be in agreement with the onset of photoconductivity
by spectrally resolved photocurrent measurements. For photogenerated singlet
exciton at the absorption edge, 0.7 eV of excess energy are required to
overcome the binding energy; the intermediate charge transfer state is situated
only 0.3 eV above the singlet exciton. Our results give direct evidence of
energy levels involved in the photogeneration and charge transport within
conjugated polymers.


  The conformal formulation of the Einstein constraint equations has been
studied intensively since the modern version of the conformal method was first
pub- lished in the early 1970s. Proofs of existence and uniqueness of solutions
were limited to the constant mean curvature (CMC) case through the early 90s,
with analogous results for the near-CMC case beginning to appear thereafter. In
the last decade, there has been some limited progress towards understanding the
properties of the conformal method for far-from-CMC solutions as well. Although
it was initially conceivable that that these far-from-CMC results would lead to
a solution theory for the non-CMC case that would mirror the good properties of
the CMC and near-CMC cases, examples of bifurcations and of nonexistence of
solutions have been since discovered. Nevertheless, the general properties of
the conformal method for far-from-CMC data remain unknown. In this article we
apply analytic and numerical continuation techniques to the study of the con-
formal method, in an attempt to give some insight into what the solution
behavior is in the far-from-CMC case in various scenarios.


  The nuclear modification factors R_AA and R_CP of Lambda and K0s in Pb-Pb
collisions at sqrt(s_NN)= 2.76 TeV measured by ALICE at LHC are presented. In
central collisions a strong suppression at high p_T (p_T > 8 GeV/c) with
respect to pp collisions is observed. The p_T region below is dominated by an
enhancement of Lambda over the suppressed K0s. The results are compared to
those for charged hadrons and to Lambda from lower collision energies.


  Ferroelectricity can exist in elemental phases as a result of charge
transfers between atoms occupying inequivalent Wyckoff positions. We
investigate the emergence of ferroelectricity in two-dimensional elemental
materials with buckled honeycomb lattices. Various multi-bilayer structures
hosting ferroelectricity are designed by stacking-engineering. Ferroelectric
materials candidates formed by group IV and V elements are predicted
theoretically. Ultrathin Bi films show layer-stacking-dependent physical
properties of ferroelectricity, topology, and metallicity. The two-bilayer Bi
film with a polar stacking sequence is found to be an elemental topological
ferroelectric material. Three and four bilayers Bi films with polar structures
are ferroelectric-like elemental polar metals with topological nontrivial edge
states. For Ge and Sn, trivial elemental polar metals are predicted. Our work
reveals the possibility of design two-dimensional elemental topological
ferroelectrics and polar metals by stacking-engineering.


  The fine-grained action analysis of the existing action datasets is
challenged by insufficient action categories, low fine granularities, limited
modalities, and tasks. In this paper, we propose a Multi-modality and
Multi-task dataset of Figure Skating (MMFS) which was collected from the World
Figure Skating Championships. MMFS, which possesses action recognition and
action quality assessment, captures RGB, skeleton, and is collected the score
of actions from 11671 clips with 256 categories including spatial and temporal
labels. The key contributions of our dataset fall into three aspects as
follows. (1) Independently spatial and temporal categories are first proposed
to further explore fine-grained action recognition and quality assessment. (2)
MMFS first introduces the skeleton modality for complex fine-grained action
quality assessment. (3) Our multi-modality and multi-task dataset encourage
more action analysis models. To benchmark our dataset, we adopt RGB-based and
skeleton-based baseline methods for action recognition and action quality
assessment.


  A random phase property is proposed for products of random matrices drawn
from any one of the classical groups associated with the ten Cartan symmetry
classes of non-interacting disordered Fermion systems. It allows to calculate
the Lyapunov spectrum explicitly in a perturbative regime. These results apply
to quasi-one-dimensional random Dirac operators which can be constructed as
representatives for each of the ten symmetry classes. For those symmetry
classes that correspond to two-dimensional topological insulators or
superconductors, the random Dirac operators describing the one-dimensional
boundaries have vanishing Lyapunov exponents and almost surely an absolutely
continuous spectrum, reflecting the gapless and conducting nature of the
boundary degrees of freedom.


  Humanoid robots that act as human-robot interfaces equipped with social
skills can assist people in many of their daily activities. Receptionist robots
are one such application where social skills and appearance are of utmost
importance. Many existing robot receptionist systems suffer from high cost and
they do not disclose internal architectures for further development for robot
researchers. Moreover, there does not exist customizable open-source robot
receptionist frameworks to be deployed for any given application. In this paper
we present an open-source robot receptionist intelligence core -- "DEVI"(means
'lady' in Sinhala), that provides researchers with ease of creating customized
robot receptionists according to the requirements (cost, external appearance,
and required processing power). Moreover, this paper also presents details on a
prototype implementation of a physical robot using the DEVI system. The robot
can give directional guidance with physical gestures, answer basic queries
using a speech recognition and synthesis system, recognize and greet known
people using face recognition and register new people in its database, using a
self-learning neural network. Experiments conducted with DEVI show the
effectiveness of the proposed system.


  The configuration of graphene (GE) sheet conforming to the spherical surface
substrate is studied through theoretical model and molecular simulations. Two
basic configurations are observed: fully conformation and wrinkling. The final
configuration of the adsorbed GE results from the competition between two
energy terms: the adhesion energy between GE and substrate, the strain energy
stored in the GE due to the deformations. Here, we derive theoretical solutions
by accounting for two energy terms, and predict the final morphology of GE on
the spherical surface (a special kind of nano-developable curved surface)
substrate with using the phase diagram. A critical cone angle of the absorbed
GE for an arbitrary spherical surface substrate is obtained. Fully conformation
of GE is observed when the cone angle of absorbed GE is below the critical
value, otherwise wrinkles appear. Molecular simulations are implemented to
verify the theoretical model with results agree well with theoretical
predictions. Results from our present work can offer a guide for designing new
functional graphene electronical devices (such as nanoswithes) and fabricating
high quality nanostructured coating (Fig. 13).


  Studies of the Gr\"uneisen ratio, i.e., the ratio between thermal expansion
and specific heat, have become a powerful tool in the context of quantum
criticality, since it was shown theoretically that the Gr\"uneisen ratio
displays characteristic power-law divergencies upon approaching the transition
point of a continuous quantum phase transition. Here we show that the
Gr\"uneisen ratio also diverges at a symmetry-enhanced first-order quantum
phase transition, albeit with mean-field exponents, as the enhanced symmetry
implies the vanishing of a mode gap which is finite away from the transition.
We provide explicit results for simple pseudo-spin models, both with and
without Goldstone modes in the stable phases, and discuss implications.


  Image denoising stands as a critical challenge in image processing and
computer vision, aiming to restore the original image from noise-affected
versions caused by various intrinsic and extrinsic factors. This process is
essential for applications that rely on the high quality and clarity of visual
information, such as image restoration, visual tracking, and image
registration, where the original content is vital for performance. Despite the
development of numerous denoising algorithms, effectively suppressing noise,
particularly under poor capture conditions with high noise levels, remains a
challenge. Image denoising's practical importance spans multiple domains,
notably medical imaging for enhanced diagnostic precision, as well as
surveillance and satellite imagery where it improves image quality and
usability. Techniques like the Fourier transform, which excels in noise
reduction and edge preservation, along with phase congruency-based methods,
offer promising results for enhancing noisy and low-contrast images common in
modern imaging scenarios.


  An original boundary integral formulation is proposed for the problem of a
semi-infinite crack at the interface between two dissimilar elastic materials
in the presence of heat flows and mass diffusion. Symmetric and skew-symmetric
weight function matrices are used together with a generalized Betti's
reciprocity theorem in order to derive a system of integral equations that
relate the applied loading, the temperature and mass concentration fields, the
heat and mass fluxes on the fracture surfaces and the resulting crack opening.
The obtained integral identities can have many relevant applications, such as
for the modelling of crack and damage processes at the interface between
different components in electrochemical energy devices characterized by
multi-layered structures (solid oxide fuel cells and lithium ions batteries).


  Minimum Bias production cross sections of $\eta$ mesons have been measured in
200 AGeV/c S+Au and S+S collisions at the CERN SPS by reconstructing the $\eta
\to \gamma\gamma$ decay. The measurements have been made over the rapidity
range $2.1 \leq y \leq 2.9$ using the leadglass spectrometer of WA80. Within
the statistical and systematical uncertainties the spectral shapes of $\pi^0$
and $\eta$ mesons yields are identical when their invariant differential cross
section is plotted as a function of the transverse mass. The relative
normalization of the $\eta$ to $\pi^0$ transverse mass spectra is found to be
$0.53 \pm 0.07$ for S+Au and $0.43 \pm 0.15$ for S+S reactions. Extrapolation
to full phase space leads to an integrated cross section ratio of $\eta$ to
$\pi^0$ mesons of $0.147 \pm 0.017 {\rm (stat.)} \pm 0.015 {\rm (syst.)}$, and
$0.120 \pm 0.034 {\rm (stat.)} \pm 0.022 {\rm (syst.)}$ for S+Au and S+S
collisions, respectively.


  We study the Gross-Pitaevskii equation involving a nonlocal interaction
potential. Our aim is to give sufficient conditions that cover a variety of
nonlocal interactions such that the associated Cauchy problem is globally
well-posed with non-zero boundary condition at infinity, in any dimension. We
focus on even potentials that are positive definite or positive tempered
distributions.


  The optical klystron enhancement to self-amplified spontaneous emission
(SASE) free electron lasers (FELs) is studied in theory and in simulations. In
contrast to a seeded FEL, the optical klystron gain in a SASE FEL is not
sensitive to any phase mismatch between the radiation and the microbunched
electron beam. The FEL performance with the addition of four optical klystrons
located at the undulator long breaks in the Linac Coherent Light Source (LCLS)
shows significant improvement if the uncorrelated energy spread at the
undulator entrance can be controlled to a very small level. In addition, FEL
saturation at shorter x-ray wavelengths (around 1.0 \AA) within the LCLS
undulator length becomes possible. We also discuss the application of the
optical klystron in a compact x-ray FEL design that employs relatively low
electron beam energy together with a short-period undulator.


  This paper proposes a model based on gene expression programming for
predicting the discharge coefficient of triangular labyrinth weirs. The
parameters influencing discharge coefficient prediction were first examined and
presented as crest height ratio to the head over the crest of the weir, a crest
length of water to channel width, a crest length of water to the head over the
crest of the weir, Froude number and vertex angle dimensionless parameters.
Different models were then presented using sensitivity analysis in order to
examine each of the dimensionless parameters presented in this study. In
addition, an equation was presented through the use of nonlinear regression
(NLR) for the purpose of comparison with GEP. The results of the studies
conducted by using different statistical indexes indicated that GEP is more
capable than NLR. This is to the extent that GEP predicts the discharge
coefficient with an average relative error of approximately 2.5% in such a
manner that the predicted values have less than 5% relative error in the worst
model.


  In this note, we establish the following Second Main Theorem type estimate
for every entire non-algebraically degenerate holomorphic curve
$f\colon\mathbb{C}\rightarrow\mathbb{P}^n(\mathbb{C})$, in present of a {\sl
generic} hypersuface $D\subset\mathbb{P}^n(\mathbb{C})$ of sufficiently high
degree $d\geq 15(5n+1)n^n$: \[ T_f(r) \leq \,N_f^{[1]}(r,D) + O\big(\log T_f(r)
+ \log r \big)\parallel, \] where $T_f(r)$ and $N_f^{[1]}(r,D)$ stand for the
order function and the $1$-truncated counting function in Nevanlinna theory.
This inequality quantifies recent results on the logarithmic Green--Griffiths
conjecture.


  Strong gravitational lensing can produce copies of gravitational-wave signals
from the same source with the same waveform morphologies but different
amplitudes and arrival times. Some of these strongly-lensed gravitational-wave
signals can be demagnified and become sub-threshold. We present TESLA-X, an
enhanced approach to the original GstLAL-based TargetEd Subthreshold Lensing
seArch (TESLA) method, for improving the detection efficiency of these
potential sub-threshold lensed signals. TESLA-X utilizes lensed injections to
generate a targeted population model and a targeted template bank. We compare
the performance of a full template bank search, TESLA, and TESLA-X methods via
a simulation campaign, and demonstrate the performance of TESLA-X in recovering
lensed injections, particularly targeting a mock event. Our results show that
the TESLA-X method achieves a maximum of $\sim 10\%$ higher search sensitivity
compared to the TESLA method within the sub-threshold regime, presenting a step
towards detecting the first lensed gravitational wave. TESLA-X will be employed
for the LIGO-Virgo-KAGRA's collaboration-wide analysis to search for lensing
signatures in the fourth observing run.


  We study an extension of the symplectic formalism in order to quantize
reducible systems. We show that a procedure like {\it ghost-of-ghost} of the
BFV method can be applied in terms of Lagrange multipliers. We use the
developed formalism to quantize the antisymmetric Abelian gauge fields.


  Advanced techniques for manipulation of internal states, standard in atomic
physics, are demonstrated for a charged molecular species for the first time.
We address individual hyperfine states of ro-vibrational levels of a diatomic
ion by optical excitation of individual hyperfine transitions, and achieve
controlled transfer of population into a selected hyperfine state. We use
molecular hydrogen ions (HD^{+}) as a model system and employ a novel
frequency-comb-based, continuous-wave 5 \mum laser spectrometer. The achieved
spectral resolution is the highest obtained so far in the optical domain on a
molecular ion species. As a consequence, we are also able to perform the most
precise test yet of the ab-initio theory of a molecule.


  In this paper, we implement a $3$-dimensional holographic effective theory
with gauge-axion coupling. The analytical black hole solution is worked out. We
investigate the Direct current (DC) thermoelectric conductivities. A novel
property is that DC electric conductivity for vanishing gauge-axion coupling is
temperature dependent. It is different from that of $4$-dimensional axion model
whose DC electric conductivity is temperature independent. In addition, the
gauge-axion coupling induces a metal insulator transition (MIT) at zero
temperature. The properties of other DC thermoelectric conductivities are also
discussed. Moreover we find that the Wiedemann-Franz (WF) law is violated in
our model.


  The coaxial wire method provides an experimental way of measuring wake fields
without the need for a particle beam. A special setup has been designed and is
in the process of being fabricated at SLAC to measure the loss factors and
synchronous frequencies of dipole modes in both traveling and standing wave
structures for the Next Linear Collider (NLC). The method is described and
predictions based on electromagnetic field simulations are discussed


  The causal dose response curve is commonly selected as the statistical
parameter of interest in studies where the goal is to understand the effect of
a continuous exposure on an outcome.Most of the available methodology for
statistical inference on the dose-response function in the continuous exposure
setting requires strong parametric assumptions on the probability distribution.
Such parametric assumptions are typically untenable in practice and lead to
invalid inference. It is often preferable to instead use nonparametric methods
for inference, which only make mild assumptions about the data-generating
mechanism. We propose a nonparametric test of the null hypothesis that the
dose-response function is equal to a constant function. We argue that when the
null hypothesis holds, the dose-response function has zero variance. Thus, one
can test the null hypothesis by assessing whether there is sufficient evidence
to claim that the variance is positive. We construct a novel estimator for the
variance of the dose-response function, for which we can fully characterize the
null limiting distribution and thus perform well-calibrated tests of the null
hypothesis. We also present an approach for constructing simultaneous
confidence bands for the dose-response function by inverting our proposed
hypothesis test. We assess the validity of our proposal in a simulation study.
In a data example, we study, in a population of patients who have initiated
treatment for HIV, how the distance required to travel to an HIV clinic affects
retention in care.


  The design of single chip current source based on a common power operational
amplifier is presented and demonstrated for the purpose of controlling applied
magnetic fields using bias/shim electromagnets in cold atom experiments. The
efficacy of the design is realized via application to red-detuned
polarization-gradient cooling of $^{87}$Rb down to 3 $\mu$K. Further, we
demonstrate Raman spectroscopy using these devices to apply current and so
generate a precise, accurate, and reproducible magnetic field. This work is
intended as a short tutorial for new graduate students and postdocs of laser
cooling and trapping.


  We introduce a new function on the set of pairs of cluster variables via
$f$-vectors, which we call it the compatibility degree (of cluster complexes).
The compatibility degree is a natural generalization of the classical
compatibility degree introduced by Fomin and Zelevinsky. In particular, we
prove that the compatibility degree has the duality property, the symmetry
property, the embedding property and the compatibility property, which the
classical one has. We also conjecture that the compatibility degree has the
exchangeability property. As pieces of evidence of this conjecture, we
establish the exchangeability property for cluster algebras of rank 2, acyclic
skew-symmetric cluster algebras, cluster algebras arising from weighted
projective lines, and cluster algebras arising from marked surfaces.


  We consider the possibility of the quantum vacuum states in f(R,T) gravity.
Particularly, we study the Bogoliubov transformations associated to different
vacuum states for some f(R,T) models. The method consists of fixing the f(R,T)
free parameters by requiring the Bogoliubov coefficients to be minimized. In
such a way, the particle production is related to the value of the Hubble
parameter and also the given f(R,T) model.


  We prove that there are only finitely many modular curves of $D$-elliptic
sheaves over $\mathbb{F}_q(T)$ which are hyperelliptic. In odd characteristic
we give a complete classification of such curves.


  With rapid development and deployment of generative language models in global
settings, there is an urgent need to also scale our measurements of harm, not
just in the number and types of harms covered, but also how well they account
for local cultural contexts, including marginalized identities and the social
biases experienced by them. Current evaluation paradigms are limited in their
abilities to address this, as they are not representative of diverse, locally
situated but global, socio-cultural perspectives. It is imperative that our
evaluation resources are enhanced and calibrated by including people and
experiences from different cultures and societies worldwide, in order to
prevent gross underestimations or skews in measurements of harm. In this work,
we demonstrate a socio-culturally aware expansion of evaluation resources in
the Indian societal context, specifically for the harm of stereotyping. We
devise a community engaged effort to build a resource which contains
stereotypes for axes of disparity that are uniquely present in India. The
resultant resource increases the number of stereotypes known for and in the
Indian context by over 1000 stereotypes across many unique identities. We also
demonstrate the utility and effectiveness of such expanded resources for
evaluations of language models. CONTENT WARNING: This paper contains examples
of stereotypes that may be offensive.


  Contact pressure between the human body and its surroundings has important
implications. For example, it plays a role in comfort, safety, posture, and
health. We present a method that infers contact pressure between a human body
and a mattress from a depth image. Specifically, we focus on using a depth
image from a downward facing camera to infer pressure on a body at rest in bed
occluded by bedding, which is directly applicable to the prevention of pressure
injuries in healthcare. Our approach involves augmenting a real dataset with
synthetic data generated via a soft-body physics simulation of a human body, a
mattress, a pressure sensing mat, and a blanket. We introduce a novel deep
network that we trained on an augmented dataset and evaluated with real data.
The network contains an embedded human body mesh model and uses a white-box
model of depth and pressure image generation. Our network successfully infers
body pose, outperforming prior work. It also infers contact pressure across a
3D mesh model of the human body, which is a novel capability, and does so in
the presence of occlusion from blankets.


  When comparing a set of La0.67Sr0.33MnO3 (LSMO) samples, the Curie
temperature (TC) of the samples is an important figure of merit for the sample
quality. Therefore, a reliable method to determine TC is required. Here, a
method based on the analysis of the magnetization loops is proposed.


  Investigation of melting line of graphite and liquid carbon has long history.
However, up to now there are still numerous controversies in the field, for
instance, the melting temperatures obtained in different experiments are in
very bad agrement. In the present paper we compare several models of carbon
widely used in computational studies and the results of ab-initio simulations
of liquid carbon. We show that the empirical models fail to reproduce the
properties of liquid carbon correctly. We also discuss the "melting" of
graphene.


  Meta-learning algorithms are able to learn a new task using previously
learned knowledge, but they often require a large number of meta-training tasks
which may not be readily available. To address this issue, we propose a method
for few-shot learning with fewer tasks, which we call MetaModulation. The key
idea is to use a neural network to increase the density of the meta-training
tasks by modulating batch normalization parameters during meta-training.
Additionally, we modify parameters at various network levels, rather than just
a single layer, to increase task diversity. To account for the uncertainty
caused by the limited training tasks, we propose a variational MetaModulation
where the modulation parameters are treated as latent variables. We also
introduce learning variational feature hierarchies by the variational
MetaModulation, which modulates features at all layers and can consider task
uncertainty and generate more diverse tasks. The ablation studies illustrate
the advantages of utilizing a learnable task modulation at different levels and
demonstrate the benefit of incorporating probabilistic variants in few-task
meta-learning. Our MetaModulation and its variational variants consistently
outperform state-of-the-art alternatives on four few-task meta-learning
benchmarks.


  This study investigates development of open access (OA) to publications
produced by authors affiliated with Ukrainian universities and research
organisations in the period 2012-2021. In order to get a comprehensive overview
we assembled data from three popular databases: Dimensions, Web of Science
(WoS) and Scopus. Our final dataset consisted of 187,135 records. To determine
the OA status of each article, this study utilised Unpaywall data which was
obtained via API. It was determined that 71.5% of all considered articles
during the observed period were openly available at the time of analysis. Our
findings show that gold OA was the most prevalent type of OA through a 10 years
studied period. We also took a look at how OA varies by research fields, how
dominant large commercial publishers are in disseminating national research and
the preferences of authors regarding where to self-archive articles versions.
We concluded that Ukraine needs to be thoughtful with engagement with large
publishers and make sure academics control publishing, not for profit
companies, which would monopolise research output distribution, leaving
national publishers behind. Beyond that we put a special emphasis on the
importance of FAIRness of national scholarly communication infrastructure in
monitoring OA uptake.


  Covert communication can prevent the adversary from knowing that a wireless
transmission has occurred. In the additive white Gaussian noise channels, a
square root law is obtained and the result shows that Alice can reliably and
covertly transmit $\mathcal{O}(\sqrt{n})$ bits to Bob in $n$ channel uses. If
additional "friendly" node near the adversary can inject artificial noise to
aid Alice in hiding her transmission attempt, covert throughput can be
improved, i.e., Alice can covertly transmit
$\mathcal{O}(\min\{n,\lambda^{\alpha/2}\sqrt{n}\})$ bits to Bob over $n$ uses
of the channel ($\lambda$ is the density of friendly nodes and $\alpha$ is the
path loss exponent of wireless channels). In this paper, we consider the covert
communication in a noisy wireless network, where Bob and the adversary Willie
not only experience the background noise, but also the aggregated interference
from other transmitters. Our results show that uncertainty in interference
experienced by Willie is beneficial to Alice. When the distance between Alice
and Willie $d_{a,w}=\omega(n^{\delta/4})$ ($\delta=2/\alpha$ is stability
exponent), Alice can reliably and covertly transmit
$\mathcal{O}(\log_2\sqrt{n})$ bits to Bob in $n$ channel uses. Although the
covert throughput is lower than the square root law and the friendly jamming
scheme, the spatial throughput is higher. From the network perspective, the
communications are hidden in "the sound and the fury" of noisy wireless
networks, and what Willie sees is merely a "shadow" wireless network. He knows
for certain that some nodes are transmitting, but he cannot catch anyone
red-handed.


  The problem of a condensate of a relativistic neutral vector boson gas
constituted of particles bearing a magnetic moment is discussed. Such a vector
boson system is expected to be formed either by parallel spin-pairing of
neutrons in a sufficiently strong magnetic field, or by neutral atoms under
specific conditions of magnetic field strength and density. A strong
self-magnetization arises due to a Bose-Einstein-like condensation. Then the
system, which may resemble the superfluid said to exist in the core of neutron
stars, becomes more unstable under transverse collapse than the ordinary
fermion gas. In the nonrelativistic limit of laboratory conditions, an analogy
with the behavior of exploding Bose-Einstein condensates for critical values of
magnetic field strength and particle density; reported by several authors, is
briefly discussed.


  Generating high fidelity identity-preserving faces with different facial
attributes has a wide range of applications. Although a number of generative
models have been developed to tackle this problem, there is still much room for
further improvement.In paticular, the current solutions usually ignore the
perceptual information of images, which we argue that it benefits the output of
a high-quality image while preserving the identity information, especially in
facial attributes learning area.To this end, we propose to train GAN
iteratively via regularizing the min-max process with an integrated loss, which
includes not only the per-pixel loss but also the perceptual loss. In contrast
to the existing methods only deal with either image generation or
transformation, our proposed iterative architecture can achieve both of them.
Experiments on the multi-label facial dataset CelebA demonstrate that the
proposed model has excellent performance on recognizing multiple attributes,
generating a high-quality image, and transforming image with controllable
attributes.


  The atomic structure of the icosahedral Ti-Zr-Ni quasicrystal is determined
by invoking similarities to periodic crystalline phases, diffraction data and
the results from ab initio calculations. The structure is modeled by
decorations of the canonical cell tiling geometry. The initial decoration model
is based on the structure of the Frank-Kasper phase W-TiZrNi, the 1/1
approximant structure of the quasicrystal. The decoration model is optimized
using a new method of structural analysis combining a least-squares refinement
of diffraction data with results from ab initio calculations. The resulting
structural model of icosahedral Ti-Zr-Ni is interpreted as a simple decoration
rule and structural details are discussed.


  We describe a new logical data model, called the concept-oriented model
(COM). It uses mathematical functions as first-class constructs for data
representation and data processing as opposed to using exclusively sets in
conventional set-oriented models. Functions and function composition are used
as primary semantic units for describing data connectivity instead of relations
and relation composition (join), respectively. Grouping and aggregation are
also performed by using (accumulate) functions providing an alternative to
group-by and reduce operations. This model was implemented in an open source
data processing toolkit examples of which are used to illustrate the model and
its operations. The main benefit of this model is that typical data processing
tasks become simpler and more natural when using functions in comparison to
adopting sets and set operations.


  In this paper we propose a novel power adapted network coding (PANC) for a
non-orthogonal multiple-access relay channel (MARC), where two sources transmit
their information simultaneously to the destination with the help of a relay.
Different from the conventional XOR-based network coding (CXNC), the relay in
our PANC generates network coded bits by considering the coefficients of the
source-to-relay channels, and forwards each bit with a pre-optimized power
level. Specifically, by defining a symbol pair as two symbols from the two
sources, we first derive the exact symbol pair error rate (SPER) of the system.
Noting that the generations of the exact SPER are complicated due to the
irregularity of the decision regions caused by random channel coefficients, we
propose a coordinate transform (CT) method to simplify the derivations of the
SPER. Next, we prove that with a power scaling factor at relay, our PANC scheme
can achieve full diversity gain, i.e., two-order diversity gain, of the system,
while the CXNC can only achieve one-order diversity gain due to multi-user
interference. In addition, we optimize the power levels at the relay to
equivalently minimize the SPER at the destination concerning the relationship
between SPER and minimum Euclidean distance of the received constellation.
Simulation results show that (1) the SPER derived based on our CT method can
well approximate the exact SPER with a much lower complexity; (2) the PANC
scheme with power level optimizations and power scaling factor design can
achieve full diversity, and obtain a much higher coding gain than the PANC
scheme with randomly chosen power levels.


  We report the discovery of the X-ray transient SAX J2103.5+4545 which was
active from February to September 1997. The observed peak intensity of 20 mCrab
(2 to 25 keV) occurred on April 11. An analysis of data obtained around the
time of the peak revealed a pulsed signal with a period of 358.61 +/- 0.03 s on
MJD 50569. The pulse profile has a pulsed fraction of ~40%. No change in the
pulse period was detected, with an upper limit of 6 s/yr. The energy spectrum
complies to a power law function with a photon index of 1.27 +/- 0.14 and
low-energy absorption equivalent to a hydrogen column density of 3.1 +/- 1.4
10**22 atoms cm**-2 of cold gas of cosmic abundances. In analogy to other X-ray
pulsars with similar characteristics we propose this object to be a neutron
star in close orbit around a mass-losing star of early spectral type. The B
star HD 200709 is a marginal candidate optical counterpart.


  The properties of neutron matter are integral to the correct description of
neutron stars as well as the description of neutron-rich nuclei. One key
property of neutron matter is its superfluid behaviour in a range of densities
relevant to the inner crust of neutron stars. This work investigates the
finite-size effects in the pairing gap of a pure neutron matter superfluid
system at densities found in the inner crust of cold neutron stars. The BCS
(Bardeen-Cooper-Schrieffer) treatment of superfluidity gives rise to the
mean-field pairing gap while a projection after variation (PBCS Theory) can
provide a beyond-mean-field pairing gap through an odd-even staggering formula.
While these two pairing gap results should agree in the thermodynamic limit, in
this work we demonstrate that this is the case for systems far from the
thermodynamic limit as well. This is a first step towards a model-independent
extraction of the pairing gap in neutron matter.


  We construct a physically realistic and analytically tractable model for
spin-1 systems with orbital degeneracy on the honeycomb lattice, relevant to
honeycomb materials with large Hund's and weak spin-orbit couplings, and two
electrons in t2g orbitals. This model realizes many new phases whose building
blocks are orbital loops decorated by Haldane chains. These include a Haldane
loop crystal, a symmetry-protected topological phase, and, notably, a regime
where the decorated loops resonate. When taken to the three-dimensional
hyperhoneycomb lattice, the latter regime becomes a (symmetry-enriched) U(1)
quantum spin-orbital liquid, "disordered" both in the spin and orbital
channels. We hope this construction will pave the way for realizing many of the
Haldane-chain-based phases which have been theoretically proposed in the
literature.


  In the game-theoretic model war of attrition, players are subject to an
explicit cost proportional to the duration of contests. We construct a model
where the time cost is not explicitly given, but instead depends implicitly on
the strategies of the whole population. We identify and analyse the underlying
mechanisms responsible for the implicit time cost. Each player participates in
a series of games, where those prepared to wait longer win with higher
certainty but play less frequently. The model is characterised by the ratio of
the winner's score to the loser's score, in a single game. The fitness of a
player is determined by the accumulated score from the games played during a
generation. We derive the stationary distribution of strategies under the
replicator dynamics. When the score ratio is high, we find that the stationary
distribution is unstable, with respect to both evolutionary and dynamical
stability, and the dynamics converge to a limit cycle. When the ratio is low,
the dynamics converge to the stationary distribution. For an intermediate
interval of the ratio, the distribution is dynamically but not evolutionarily
stable. Finally, the implications of our results for previous models based on
the war of attrition are discussed.


  In this article, we define an index of Maslov type for general symplectic
paths which have two arbitrary end points. This Maslov-type index is a
generalization of the Conley-Zehnder-Long index and the method of constructing
the index is consistent no matter whether the starting point of the path is
identity or not, which is different from the ones for Long's Maslov-type index
and Liu's $L_0$-index. Some natural properties for the index still hold. We
review other versions of Maslov indices and compare them with our definition.
In particular, this Maslov-type index can be looked as a realization of
Cappell-Lee-Miller's index for a pair of Lagrangian paths from the point of
view of index for symplectic paths.


  We present an analysis of the kinematic properties of stellar populations in
the Galactic halo, making use of over 100,000 main sequence turnoff (MSTO)
stars observed in the Sloan Digital Sky Survey. After dividing the Galactic
halo into an inner-halo region (IHR) and outer-halo region (OHR), based on the
spatial variation of carbon-to-iron ratios in the sample, we find that stars in
the OHR exhibit a clear retrograde motion of $-$49 $\pm$ 4 km s$^{-1}$ and a
more spherical distribution of stellar orbits, while stars in the IHR have zero
net rotation ($-$3 $\pm$ 1 km s$^{-1}$) with a much more radially biased
distribution of stellar orbits. Furthermore, we classify the carbon-enhanced
metal-poor (CEMP) stars among the MSTO sample in each halo component into
CEMP-no and CEMP-$s$ sub-classes, based on their absolute carbon abundances,
$A$(C), and examine the spatial distributions and kinematics associated with
each sub-class. The CEMP-no stars are the majority sub-class of CEMP stars in
the OHR ($\sim$ 65%), and the minority sub-class in the IHR ($\sim$ 44%),
similar to the results of several previous analyses. The CEMP-no stars in each
halo region exhibit slightly higher counter-rotation than the CEMP-$s$ stars,
but within statistical errors. The CEMP-no stars also show a more spherical
distribution of orbits than the CEMP-$s$ stars in each halo region. These
distinct characteristics provide strong evidence that numerous low-mass
satellite galaxies (similar to the ultra-faint dwarf galaxies) have donated
stars to the OHR, while more-massive dwarf galaxies provided the dominant
contribution to the IHR.


  Mechanics of the camera for the large size telescopes of CTA must protect and
provide a stable environment for its instrumentation. This is achieved by a
stiff support structure enclosed in an air and water tight volume. The
structure is specially devised to facilitate extracting the power dissipated by
the focal plane electronics while keeping its weight small enough to guarantee
an optimum load on the telescope structure. A heat extraction system is
designed to keep the electronics temperature within its optimal operation
range, stable in time and homogeneous along the camera volume, whereas it is
decoupled from the temperature in the telescope environment. In this
contribution, we present the details of this system as well as its verification
based in finite element analysis computations and tested prototypes. Finally,
issues related to the integration of the camera mechanics and electronics will
be dealt with.


  We report a degeneracy between the gravitational-wave signals from
quasi-circular precessing black-hole mergers and those from extremely eccentric
mergers, namely head-on collisions. Performing model selection on numerically
simulated signals of head-on collisions using models for quasi-circular
binaries we find that, for signal-to-noise ratios of 15 and 25, typical of
Advanced LIGO observations, head-on mergers with respective total masses of
$M\in (125,300)M_\odot$ and $M\in (200,440)M_\odot$ would be identified as
precessing quasi-circular intermediate-mass black hole binaries, located at a
much larger distance. Ruling out the head-on scenario would require to perform
model selection using currently nonexistent waveform models for head-on
collisions, together with the application of astrophysically motivated priors
on the (rare) occurrence of those events. We show that in situations where
standard parameter inference of compact binaries may report component masses
inside (outside) the pair-instability supernova gap, the true object may be a
head-on merger with masses outside (inside) this gap. We briefly discuss the
potential implications of these findings for the recent gravitational-wave
detection GW190521, which we analyse in detail in [Phys. Rev. Lett. 126,
081101].


  In this paper, we investigate the edge-Wiener index, the Szeged index, the
edge-Szeged index, and the PI index, which are some of the most studied
distance-based topological indices. As the main result we show that for
benzenoid systems these indices can be computed in sub-linear time with respect
to the number of vertices. More precisely, they can be computed in the time
dependent on the length of the boundary cycle of a benzenoid system.


  Spin-polarized electric current exerts torque on local magnetic spins,
resulting in magnetic domain-wall (DW) motion in ferromagnetic nanowires. Such
current-driven DW motion opens great opportunities toward next-generation
magnetic devices controlled by current instead of magnetic field. However, the
nature of the current-driven DW motion--considered qualitatively different from
magnetic-field-driven DW motion--remains yet unclear mainly due to the
painfully high operation current densities J_OP, which introduce uncontrollable
experimental artefacts with serious Joule heating. It is also crucial to reduce
J_OP for practical device operation. By use of metallic Pt/Co/Pt nanowires with
perpendicular magnetic anisotropy, here we demonstrate DW motion at current
densities down to the range of 10^9 A/m^2--two orders smaller than existing
reports. Surprisingly the current-driven motion exhibits a scaling behaviour
identical to the field-driven motion and thus, belongs to the same universality
class despite their qualitative differences. Moreover all DW motions driven by
either current or field (or by both) collapse onto a single curve, signalling
the unification of the two driving mechanisms. The unified law manifests
non-vanishing current efficiency at low current densities down to the practical
level, applicable to emerging magnetic nanodevices.