  Symmetric binary matrices representing relations among entities are commonly
collected in many areas. Our focus is on dynamically evolving binary relational
matrices, with interest being in inference on the relationship structure and
prediction. We propose a nonparametric Bayesian dynamic model, which reduces
dimensionality in characterizing the binary matrix through a lower-dimensional
latent space representation, with the latent coordinates evolving in continuous
time via Gaussian processes. By using a logistic mapping function from the
probability matrix space to the latent relational space, we obtain a flexible
and computational tractable formulation. Employing P\`olya-Gamma data
augmentation, an efficient Gibbs sampler is developed for posterior
computation, with the dimension of the latent space automatically inferred. We
provide some theoretical results on flexibility of the model, and illustrate
performance via simulation experiments. We also consider an application to
co-movements in world financial markets.


  We give a new analytical proof of the Morse index theorem for geodesics in
Riemannian manifolds.


  We show that incommensurability can enhance superconductivity in one
dimensional quasiperiodic systems with s-wave pairing. As a parent model, we
use a generalized Aubry-Andr\'e model that includes quasiperiodic modulations
both in the potential and in the hoppings. In the absence of interactions, the
model contains extended, critical and localized phases for incommensurate
modulations. Our results reveal that in a substantial region inside the parent
critical phase, there is a significant increase of the superconducting critical
temperature compared to the extended phase and the uniform limit without
quasiperiodic modulations. We also analyse the results for commensurate
modulations with period close to the selected incommensurate one. We find that
while in the commensurate case, the scaling of the critical temperature with
interaction strength follows the exponentially small weak-coupling BCS
prediction for a large enough system size, it scales algebraically in the
incommensurate case within the critical and localized parent phases. These
qualitatively distinct behaviors lead to a significant
incommensurability-induced enhancement of the critical temperature in the weak
and intermediate coupling regimes, accompanied by an increase in the
superconducting order parameter at zero temperature.


  Squidgets or 'sketch-widgets' is a novel stroke-based UI framework for direct
scene manipulation. Squidgets is motivated by the observation that sketch
strokes comprising visual abstractions of scene elements implicitly provide
natural handles for the direct manipulation of scene parameters. Configurations
of such strokes can further be explicitly drawn by users to author custom
widgets associated with scene attributes. Users manipulate a scene by simply
drawing strokes: a squidget is selected by partially matching the drawn stroke
against both implicit scene contours and explicitly authored curves, and used
in-situ to interactively control scene parameters associated with the squidget.
We present an implementation of squidgets within the 3D modeling animation
system Maya, and report on an evaluation of squidget creation and manipulation,
by both casual users and professional artists.


  Traditional simultaneous localization and mapping (SLAM) methods focus on
improvement in the robot's localization under environment and sensor
uncertainty. This paper, however, focuses on mitigating the need for exact
localization of a mobile robot to pursue autonomous navigation using a sparse
set of images. The proposed method consists of a model architecture - RoomNet,
for unsupervised learning resulting in a coarse identification of the
environment and a separate local navigation policy for local identification and
navigation. The former learns and predicts the scene based on the short term
image sequences seen by the robot along with the transition image scenarios
using long term image sequences. The latter uses sparse image matching to
characterise the similarity of frames achieved vis-a-vis the frames viewed by
the robot during the mapping and training stage. A sparse graph of the image
sequence is created which is then used to carry out robust navigation purely on
the basis of visual goals. The proposed approach is evaluated on two robots in
a test environment and demonstrates the ability to navigate in dynamic
environments where landmarks are obscured and classical localization methods
fail.


  Left ventricular assist devices (LVADs) are used to provide haemodynamic
support to patients with critical cardiac failure. Severe complications can
occur because of the modifications of the blood flow in the aortic region. In
this work, the effect of a continuous flow LVAD device on the aortic flow is
investigated by means of a non-intrusive reduced order model (ROM) built using
the proper orthogonal decomposition with interpolation (PODI) method. The full
order model (FOM) is represented by the incompressible Navier-Stokes equations
discretized by using a Finite Volume (FV) technique, coupled with three-element
Windkessel models to enforce outlet boundary conditions in a multi-scale
approach. A patient-specific framework is proposed: a personalized geometry
reconstructed from Computed Tomography (CT) images is used and the
individualization of the coefficients of the three-element Windkessel models is
based on experimental data provided by the Right Heart Catheterization (RCH)
and Echocardiography (ECHO) tests. Pre-surgery configuration is also considered
at FOM level in order to further validate the model. A parametric study with
respect to the LVAD flow rate is considered. The accuracy of the reduced order
model is assessed against results obtained with the full order model.


  Explainable artificial intelligence (XAI) has helped elucidate the internal
mechanisms of machine learning algorithms, bolstering their reliability by
demonstrating the basis of their predictions. Several XAI models consider
causal relationships to explain models by examining the input-output
relationships of prediction models and the dependencies between features. The
majority of these models have been based their explanations on counterfactual
probabilities, assuming that the causal graph is known. However, this
assumption complicates the application of such models to real data, given that
the causal relationships between features are unknown in most cases. Thus, this
study proposed a novel XAI framework that relaxed the constraint that the
causal graph is known. This framework leveraged counterfactual probabilities
and additional prior information on causal structure, facilitating the
integration of a causal graph estimated through causal discovery methods and a
black-box classification model. Furthermore, explanatory scores were estimated
based on counterfactual probabilities. Numerical experiments conducted
employing artificial data confirmed the possibility of estimating the
explanatory score more accurately than in the absence of a causal graph.
Finally, as an application to real data, we constructed a classification model
of credit ratings assigned by Shiga Bank, Shiga prefecture, Japan. We
demonstrated the effectiveness of the proposed method in cases where the causal
graph is unknown.


  Demixing of binary fluids subjected to slow temperature ramps shows repeated
waves of nucleation which arise as a consequence of the competition between
generation of supersaturation by the temperature ramp and relaxation of
supersaturation by diffusive transport and flow. Here, we use an
advection-reaction-diffusion model to study the oscillations in the weak- and
strong-diffusion regime. There is a sharp transition between the two regimes,
which can only be understood based on the probability distribution function of
the composition rather than in terms of the average composition. We argue that
this transition might be responsible for some yet unclear features of
experiments, like the appearance of secondary oscillations and bimodal droplet
size distributions.


  We study the controllability of the Bloch equation, for an ensemble of non
interacting half-spins, in a static magnetic field, with dispersion in the
Larmor frequency. This system may be seen as a prototype for infinite
dimensional bilinear systems with continuous spectrum, whose controllability is
not well understood. We provide several mathematical answers, with
discrimination between approximate and exact controllability, and between
finite time or infinite time controllability: this system is not exactly
controllable in finite time $T$ with bounded controls in $L^2(0,T)$, but it is
approximately controllable in $L^\infty$ in finite time with unbounded controls
in $L^{\infty}_{loc}([0,+\infty))$. Moreover, we propose explicit controls
realizing the asymptotic exact controllability to a uniform state of spin +1/2
or -1/2.


  Numerical schemes used for the integration of complex flow simulations should
provide accurate solutions for the long time integrations these flows require.
To this end, the performance of various high-order accurate numerical schemes
is investigated for direct numerical simulations (DNS) of homogeneous isotropic
two-dimensional decaying turbulent flows. The numerical accuracy of compact
difference, explicit central difference, Arakawa, and
dispersion-relation-preserving schemes are analyzed and compared with the
Fourier-Galerkin pseudospectral scheme. In addition, several explicit
Runge-Kutta schemes for time integration are investigated. We demonstrate that
the centered schemes suffer from spurious Nyquist signals that are generated
almost instantaneously and propagate into much of the field when the numerical
resolution is insufficient. We further show that the order of the scheme
becomes increasingly important for increasing cell Reynolds number.
Surprisingly, the sixth-order schemes are found to be in perfect agreement with
the pseudospectral method. Considerable reduction in computational time
compared to the pseudospectral method is also reported in favor of the finite
difference schemes. Among the fourth-order schemes, the compact scheme provides
better accuracy than the others for fully resolved computations. The
fourth-order Arakawa scheme provides more accurate results for under-resolved
computations, however, due to its conservation properties. Our results show
that, contrary to conventional wisdom, difference methods demonstrate superior
performance in terms of accuracy and efficiency for fully resolved DNS
computations of the complex flows considered here. For under-resolved
simulations, however, the choice of difference method should be made with care.


  Estimating the fidelity of state preparation in multi-qubit systems is
generally a time-consuming task. Nevertheless, this complexity can be reduced
if the desired state can be characterized by certain symmetries measurable with
the corresponding experimental setup. In this paper we give simple expressions
to estimate the fidelity of multi-qubit state preparation for
rotational-invariant, stabilizer, and generalized coherent states. We
specifically discuss the cat, W-type, and generalized coherent states, and
obtain efficiently measurable lower bounds for the fidelity. We use these
techniques to estimate the fidelity of a quantum simulation of an Ising-like
interacting model using two trapped ions. These results are directly applicable
to experiments using fidelity-based entanglement witnesses, such as quantum
simulations and quantum computation.


  We obtain a bound on the number of solutions of $x^q=x$ in a finite
noncommutative algebra over a field with $q$ elements. Furthermore, we
completely characterize those rings for which this maximum number is attained.


  This paper extends the property of interlacing of the zeros of eigenfunctions
in Hermitian systems to the topological property of winding number in
non-Hermitian systems. Just as the number of nodes of each eigenfunction in a
self-adjoint Sturm-Liouville problem are well-ordered, so too are the winding
numbers of each eigenfunction of Hermitian and of unbroken PT-symmetric
potentials. Varying a system back and forth past an exceptional point changes
the windings of its eigenfunctions in a specific manner. Nonlinear,
higher-dimensional, and general non-Hermitian systems also exhibit
manifestations of these characteristics.


  Modeling the high-$T$ paramagnetic state of bulk UO$_2$ by a
non-spin-polarized calculation and neglecting the Hubbard-U correction for the
$f$ electrons in U atoms, the lattice thermal conductivity of bulk UO$_2$ is
investigated by the exact solution of the Boltzmann transport equation for the
steady-state phonon distribution function. The results show that TA branches
corresponding to U-atoms vibrations have the largest lifetimes and therefore
have dominant role in thermal conductivity, while the optical branches
corresponding mainly to O-atoms vibrations have the shortest lifetimes. Using
this simple model, our results for the thermal conductivity show a very good
agreement with the experiments. The calculations are repeated for bulk UO$_2$
with different U-235 concentrations of 3\%, 5\%, 7\%, and 20\%, and the results
show a small decrease of thermal conductivity which arise from scattering of
phonons by impurities.


  We determine the density parameters $\Omega_m$ of gravitating matter and
$\Omega_{\Lambda}$ of vacuum energy, by making a $\chi^2$ fit to nine
independent astrophysical constraints. Paying rigorous attention to statistical
detail, we find that the present best values are $\Omega_m=0.31\pm 0.07,
\Omega_{\Lambda}=0.70\pm 0.13$, where these $1\sigma$ errors are approximately
Gaussian (thus trivially convertible to whatever percentage confidence range
desired). The total $\chi^2$ is 2.5 for 7 degrees of freedom, testifying that
the various systematic errors included are generous. Since $\Omega_m +
\Omega_{\Lambda}= 1.01\pm 0.15$, it follows that the Einstein-de Sitter model
is very strongly ruled out, that also any low-density model with
$\Omega_{\Lambda}=0$ is ruled out, and that a flat cosmology is not only
possible, but clearly preferred. In the flat case we find $\Omega_m=0.31\pm
0.04$, from which it follows that the age of the Universe is $t_0 =
13.7^{+1.2}_{-1.1}(0.68/h)$ Gyr.


  The maximally chaotic K-systems are dynamical systems which have nonzero
Kolmogorov entropy. On the other hand, the hyperbolic dynamical systems that
fulfil the Anosov C-condition have exponential instability of phase
trajectories, mixing of all orders, countable Lebesgue spectrum and positive
Kolmogorov entropy. The C-condition defines a rich class of maximally chaotic
systems which span an open set in the space of all dynamical systems. The
interest in Anosov-Kolmogorov C-K systems is associated with the attempts to
understand the relaxation phenomena, the foundation of the statistical
mechanics, the appearance of turbulence in fluid dynamics, the non-linear
dynamics of the Yang-Mills field as well as the dynamical properties of
gravitating N-body systems and the Black hole thermodynamics. In this respect
of special interest are C-K systems that are defined on Reimannian manifolds of
negative sectional curvature and on a high-dimensional tori. Here we shall
review the classical- and quantum-mechanical properties of maximally chaotic
dynamical systems, the application of the C-K theory to the investigation of
the Yang-Mills dynamics and gravitational systems as well as their application
in the Monte Carlo method.


  We address the question of understanding the production of $J/\psi$ particles
regarding the global underlying event in proton-proton collisions. To do so, we
propose to look at a new observable: the $J/\psi$ production as a function of
the charged particles multiplicity of the event. We demonstrate the interest
for an experimental measurement by varying the model of multiple interactions
in the PYTHIA generator.


  Using the light-cone gauge approach to relativistic field dynamics, we study
arbitrary spin fermionic and bosonic fields propagating in flat space of
dimension greater than or equal to four. Generating functions of parity
invariant cubic interaction vertices for totally symmetric and mixed-symmetry
massive and massless fields are obtained. For the case of totally symmetric
fields, we derive restrictions on the allowed values of spins and the number of
derivatives. These restrictions provide a complete classification of parity
invariant cubic interaction vertices for totally symmetric fermionic and
bosonic fields. As an example of application of the light-cone formalism, we
obtain simple expressions for the Yang-Mills and gravitational interactions of
massive arbitrary spin fermionic fields. For some particular cases, using our
light-cone cubic vertices, we discuss the corresponding manifestly Lorentz
invariant and on-shell gauge invariant cubic vertices.


  According to Aristotle "time is the number of change with respect to the
before and after". That's certainly a vague concept, but at the same time it's
both simple and satisfying from a philosophical point of view: things do not
change along time, but they do change and the measurement of such changes is
what we call time. This deprives time of any attribute of substantiality,
meanwhile depriving it of all problems in defining the properties of time as a
substance. With the rise of Classical Mechanics, Aristotle's view is abandoned
and Newton's concept of "true" and absolute time imposes itself; time flows
independently on changes of any kind. Relativity will then radically modify our
concept of time, but won't actually modify the fundamental idea: things keep
changing along time -- changes do not make time. This work will argue
Aristotle's thesis, showing how such an approach automatically leads to the
principles of Special Relativity. An interesting consequence and, at least
virtually, measurable will also be highlighted: the fact that synchronizing two
clocks with a precision greater than a certain scale is impossible, estimating
such scale around $10^{-22}$s.


  The possibility that part of the dark matter is made of massive compact halo
objects (MACHOs) remains poorly constrained over a wide range of masses, and
especially in the $20-100\, M_\odot$ window. We show that strong gravitational
lensing of extragalactic fast radio bursts (FRBs) by MACHOs of masses larger
than $\sim20\,M_\odot$ would result in repeated FRBs with an observable time
delay. Strong lensing of an FRB by a lens of mass $M_L$ induces two images,
separated by a typical time delay $\sim$ few $\times(M_L/30\, M_\odot)$
milliseconds. Considering the expected FRB detection rate by upcoming
experiments, such as CHIME, of $10^4$ FRBs per year, we should observe from
tens to hundreds of repeated bursts yearly, if MACHOs in this window make up
all the dark matter. A null search for echoes with just $10^4$ FRBs, would
constrain the fraction $f_{\rm DM}$ of dark matter in MACHOs to $f_{\rm
DM}\lesssim 0.08$ for $M_L\gtrsim 20\,M_\odot$.


  Oscillation experiments show that neutrinos have masses. They however only
determine the neutrinop mass differences. Information on the absolute masses
can be obtained by studying the kinematics in weak decays, or by searching for
neutrinoless double beta decay. Recent results are reviewed, as well as future
projects.


  Hybrid systems, and Piecewise Deterministic Markov Processes in particular,
are widely used to model and numerically study systems exhibiting multiple time
scales in biochemical reaction kinetics and related areas. In this paper an
almost sure convergence analysis for numerical simulation algorithms for
Piecewise Deterministic Markov Processes is presented. The discussed numerical
methods arise through discretisina a constructive method defining these
processes. The stochastic problem of simulating the random, path-dependent jump
times of such processes is reformulated as a hitting time problem for a system
of ordinary differential equations with random threshold. Then deterministic
continuous methods (methods with dense output) are serially employed to solve
these problems numerically. We show that the almost sure asymptotic convergence
rate of the stochastic algorithm is identical to the order of the embedded
deterministic method. We illustrate our theoretical findings by numerical
examples from mathematical neuroscience were Piecewise Deterministic Markov
Processes are used as biophysically accurate stochastic models of neuronal
membranes.


  In a previous paper (gr-qc/9907063) we described the early inflationary
universe in terms of quantum information. In this paper, we analize those
results in more detail, and we stress the fact that, during inflation, the
universe can be described as a superposed state of quantum registers. The
self-reduction of the superposed quantum state is consistent with the Penrose's
Objective Reduction (OR) model. The quantum gravity threshold is reached at the
end of inflation, and corresponds to a superposed state of 10^9 quantum
registers. This is also the number of superposed tubulins-qubits in our brain,
which undergo the Penrose-Hameroff's Orchestrated Objective Reduction, (Orch
OR), leading to a conscious event. Then, an analogy naturally arises between
the very early quantum computing universe,and our mind.


  In this paper, epistemology and ontology of quantum states are discussed
based on a completely new way of founding quantum theory. The fundamental
notions are conceptual variables in the mind of an observer or in the joint
minds of a group of observers. These conceptual variables are very often
accessible, that is, it is possible to find values of the variables by doing
experiments or by making measurements. An important notion is that of maximal
accessibility. It is shown here that this new machinery may facilitate the
discussion of when a specific quantum state can be given an ontological
interpretation, and also the more speculative question whether all states can
be given such an interpretation. The discussion here is general, and has
implications for the basic problem of how one should look upon information from
experiments and measurement, in particularly the question concerning when this
information may reflect properties of the real world.


  Electron spin resonance (ESR) spectroscopy is an important tool to
characterize the ground state of conduction electrons and to measure their
spin-relaxation times. Observing ESR of the itinerant electrons is thus of
great importance in graphene and in single-wall carbon nanotubes (SWCNTs).
Often, the identification of CESR signal is based on two facts: the apparent
asymmetry of the ESR signal (known as a Dysonian lineshape) and on the
temperature independence of the ESR signal intensity. We argue that these are
insufficient as benchmarks and instead the ESR signal intensity (when
calibrated against an intensity reference) yields an accurate characterization.
We detail the method to obtain the density of states from an ESR signal, which
can be compared with theoretical estimates. We demonstrate the success of the
method for K doped graphite powder. We give a benchmark for the observation of
ESR in graphene.


  In the work, the thermal and vacuum fluctuation is predicted capable of
generating a Casimir thrust force on a rotating chiral particle, which will
push or pull the particle along the rotation axis. The Casimir thrust force
comes from two origins: i) the rotation-induced symmetry-breaking in the vacuum
and thermal fluctuation and ii) the chiral cross-coupling between electric and
magnetic fields and dipoles, which can convert the vacuum spin angular momentum
(SAM) to the vacuum force. Using the fluctuation dissipation theorem (FDT), we
derive the analytical expressions for the vacuum thrust force in dipolar
approximation and the dependences of the force on rotation frequency,
temperature and material optical properties are investigated. The work reveals
a new mechanism to generate a vacuum force, which opens a new way to exploit
zero-point energy of vacuum.


  Selenium is a crucial earth-abundant and non-toxic semiconductor with a wide
range of applications across the semiconductor industries. Selenium has drawn
attention from scientific communities for its wide range of applicability: from
photovoltaics to imaging devices. Its usage as a photosensitive material
largely involves the synthesis of the amorphous phase (a-Se) via various
experimental techniques. However, the ground state crystalline phase of this
material, known as the trigonal selenium (\textit{t}-Se), is not extensively
studied for its optimum electronic and optical properties. In this work, we
present density functional theory (DFT) based systematic studies on the
ultra-thin $(10\overline{1}0)$ surface slabs of \textit{t}-Se. We report the
surface energies, work function, electronic and optical properties as a
function of number of layers for $(10\overline{1}0)$ surface slabs to access
its suitability for applications as a photosensitive material.


  In Reinforcement Learning, agents learn policies by exploring and interacting
with the environment. Due to the curse of dimensionality, learning policies
that map high-dimensional sensory input to motor output is particularly
challenging. During training, state of the art methods (SAC, PPO, etc.) explore
the environment by perturbing the actuation with independent Gaussian noise.
While this unstructured exploration has proven successful in numerous tasks, it
can be suboptimal for overactuated systems. When multiple actuators, such as
motors or muscles, drive behavior, uncorrelated perturbations risk diminishing
each other's effect, or modifying the behavior in a task-irrelevant way. While
solutions to introduce time correlation across action perturbations exist,
introducing correlation across actuators has been largely ignored. Here, we
propose LATent TIme-Correlated Exploration (Lattice), a method to inject
temporally-correlated noise into the latent state of the policy network, which
can be seamlessly integrated with on- and off-policy algorithms. We demonstrate
that the noisy actions generated by perturbing the network's activations can be
modeled as a multivariate Gaussian distribution with a full covariance matrix.
In the PyBullet locomotion tasks, Lattice-SAC achieves state of the art
results, and reaches 18% higher reward than unstructured exploration in the
Humanoid environment. In the musculoskeletal control environments of MyoSuite,
Lattice-PPO achieves higher reward in most reaching and object manipulation
tasks, while also finding more energy-efficient policies with reductions of
20-60%. Overall, we demonstrate the effectiveness of structured action noise in
time and actuator space for complex motor control tasks. The code is available
at: https://github.com/amathislab/lattice.


  We extend the adiabatic regularization method by introducing an arbitrary
mass scale $\mu$ in the construction of the subtraction terms. This allows us
to obtain, in a very robust way, the running of the coupling constants by
demanding $\mu$-invariance of the effective semiclassical (Maxwell-Einstein)
equations. In particular, we get the running of the electric charge of
perturbative quantum electrodynamics. Furthermore, the method brings about a
renormalization of the cosmological constant and the Newtonian gravitational
constant. The running obtained for these dimensionful coupling constants has
new relevant (non-logarithmic) contributions, not predicted by dimensional
regularization.


  A finite temperature model of strongly correlated nucleons with underlying
isospin symmetries is developed. The model can be used to study the role of
bound states and Feshbach resonances on the thermal properties of a spin 1/2,
isospin 1/2 system of protons and neutrons by varying the proton fraction. An
analysis of features associated with a universal thermodynamic limit or unitary
limit is given. In the limit of very large scattering length, the effective
range to quantum thermal wavelength appears as a limiting scale in an
interaction energy and equation of state.


  Centimeter-wave transitions are important counterparts to the rotational
mm-wave transitions usually observed to study gas in star-forming regions.
However, given their relative weakness, these transitions have historically
been neglected. We present Australia Telescope Compact Array 4cm- and 15mm-band
spectral line observations of nine nearby star-forming galaxies in the H75
array configuration. Thirteen different molecular lines are detected across the
sample from OH, NH$_3$, H$_2$O, H$_2$CO, and c-C$_3$H$_2$, as well as 18 radio
recombination lines (RRLs) in NGC 253. Excited OH $^2\Pi_{3/2}$ absorption is
detected towards NGC 253 (J=5/2), NGC 4945 (J=9/2), and Circinus (J=9/2); the
latter two represent only the third and fourth extragalactic J=9/2 detections.
These lines in Circinus suggest rotation temperatures in excess of 2000 K, and
thus it is likely that the populations of OH rotational states are not governed
by a Boltzmann distribution. Circinus's OH lines are blueshifted from the
systemic velocity by ~35 km s$^{-1}$, while NGC 4945's are redshifted by ~100
km s$^{-1}$. NGC 4945's OH absorption likely indicates infall onto the nucleus.
The NH$_3$ (1,1) through (6,6) lines in NGC 4945 display a superposition of
emission and absorption similar to that seen in other dense gas tracers. Strong
(3,3) emission points towards maser activity. The relative NH$_3$ absorption
strengths in NGC 4945 show similar anomalies as in previous studies of Arp 220
(weak (1,1) and strong (5,5) absorption). A trend towards higher LTE electron
temperatures with increasing RRL frequency is present in NGC 253, likely
indicative of stimulated emission within the nuclear region.


  From bone and wood to concrete and carbon fibre, composites are ubiquitous
natural and engineering materials. Eshelby's inclusion theory describes how
macroscopic stress fields couple to isolated microscopic inclusions, allowing
prediction of a composite's bulk mechanical properties from a knowledge of its
microstructure. It has been extended to describe a wide variety of phenomena
from solid fracture to cell adhesion. Here, we show experimentally and
theoretically that Eshelby's theory breaks down for small liquid inclusions in
a soft solid. In this limit, an isolated droplet's deformation is strongly
size-dependent with the smallest droplets mimicking the behaviour of solid
inclusions. Furthermore, in opposition to the predictions of conventional
composite theory, we find that finite concentrations of small liquid inclusions
enhance the stiffness of soft solids. A straight-forward extension of Eshelby's
theory, accounting for the surface tension of the solid-liquid interface,
explains our experimental observations. The counterintuitive effect of
liquid-stiffening of solids is expected whenever droplet radii are smaller than
an elastocapillary length, given by the ratio of the surface tension to Young's
modulus of the solid matrix.


  In this second paper of the series, we study with new Keck/DEIMOS spectra the
stellar populations of seven spectroscopically confirmed ultra-diffuse galaxies
(UDGs) in the Coma cluster. We find intermediate to old ages (~ 7Gyr), low
metallicities ([Z/H] ~ -0.7dex) and mostly super-solar abundance patterns
([Mg/Fe] ~ 0.13dex). These properties are similar to those of low-luminosity
(dwarf) galaxies inhabiting the same area in the cluster and are most
consistent with being the continuity of the stellar mass scaling relations of
more massive galaxies. These UDGs' star formation histories imply a relatively
recent infall into the Coma cluster, consistent with the theoretical
predictions for a dwarf-like origin. However, considering the scatter in the
resulting properties and including other UDGs in Coma, together with the
results from the velocity phase-space study of the Paper I in this series, a
mixed-bag of origins is needed to explain the nature of all UDGs. Our results
thus reinforce a scenario in which many UDGs are field dwarfs that become
quenched through their later infall onto cluster environments, whereas some
UDGs could be genuine primordial galaxies that failed to develop due to an
early quenching phase. The unknown proportion of dwarf-like to primordial-like
UDGs leaves the enigma of the nature of UDGs still open.


  We review the prediction of inflation and the constraints on inflationary
models coming from recent observations.


  We present a theoretical study of superconductivity of polarons in the
Hubbard-Holstein model. A residual kinematic interaction proportional to the
square of the polaron hopping energy between polarons and phonons provides a
pairing field for the polarons. We find that superconducting instability in the
d-wave channel is possible with small transition temperatures which is maximum
in the large to small polaron cross-over region. An s-wave instability is found
to be not possible when the effective on-site interaction between polarons is
repulsive.


  We propose a vision-based reinforcement learning (RL) approach for
closed-loop trajectory generation in an arm reaching problem. Arm trajectory
generation is a fundamental robotics problem which entails finding
collision-free paths to move the robot's body (e.g. arm) in order to satisfy a
goal (e.g. place end-effector at a point).
  While classical methods typically require the model of the environment to
solve a planning, search or optimization problem, learning-based approaches
hold the promise of directly mapping from observations to robot actions.
  However, learning a collision-avoidance policy using RL remains a challenge
for various reasons, including, but not limited to, partial observability, poor
exploration, low sample efficiency, and learning instabilities.
  To address these challenges, we present a residual-RL method that leverages a
greedy goal-reaching RL policy as the base to improve exploration, and the base
policy is augmented with residual state-action values and residual actions
learned from images to avoid obstacles. Further more, we introduce novel
learning objectives and techniques to improve 3D understanding from multiple
image views and sample efficiency of our algorithm.
  Compared to RL baselines, our method achieves superior performance in terms
of success rate.


  A search for phi radiative decays has been performed using a data sample of
about 2.0 million phi decays collected by the CMD-2 detector at VEPP-2M
collider in Novosibirsk. From the selected e+ e- -> pi+ pi- gamma events the
following results were obtained: B(phi -> f0(980) gamma) < 1x10-4 for
destructive and B(phi -> f0(980) gamma) < 7x10-4 for constructive interference
with the Bremsstrahlung process respectively, B(phi -> gamma -> pi+ pi- gamma)
< 3x10-5 for E of gamma > 20 MeV, B(phi -> rho gamma) < 7x10-4. From the
selected e+ e- -> mu+ mu- gamma events B(phi -> mu+ mu- gamma) =
(2.3+-1.0)x10-5 has been obtained for E of gamma> 20 MeV. The upper limit on
the P,CP-violating decay eta -> pi+ pi- has also been placed: B(eta -> pi+ pi-)
< 9x10-4 . All upper limits are at 90 % C.L.


  Grid states form a discrete set of mixed quantum states that can be described
by graphs. We characterize the entanglement properties of these states and
provide methods to evaluate entanglement criteria for grid states in a
graphical way. With these ideas we find bound entangled grid states for
two-particle systems of any dimension and multiparticle grid states that
provide examples for the different aspects of genuine multiparticle
entanglement. Our findings suggest that entanglement theory for grid states,
although being a discrete set, has already a complexity similar to the one for
general states.


  The SuperNEMO project aims to search for neutrinoless double beta decay
($0\nu\beta\beta$) up to a sensitivity of 10$^{26}$ years for the
$0\nu\beta\beta$ half-life (down to $\sim$ 50~meV in the effective Majorana
neutrino mass), using $\sim$100 kg of source and a `tracko-calo' detector. The
current status of the 2006--2010 R\&D programme is discussed here.


  In this paper, we calculate simulated scattered light images of a
circumstellar disk in which a planet is forming by gravitational instability.
The simulated images bear no correlation to the vertically integrated surface
density of the disk, but rather trace the density structure in the tenuous
upper layers of the disk. Although the density at high altitudes does not bear
a direct relation to activity at the midplane, the very existence of structure
at high altitudes along with high time variability is an indicator of
gravitational instability within the disk. The timescale for variations is much
shorter than the orbital period of the planet, which facilitates observation of
the phenomenon. Scattered light images may not necessarily be able to tell us
where exactly a planet might be forming in a disk, but can still be a useful
probe of active planet formation within a circumstellar disk. Although these
phenomena are unlikely to be observable by current telescopes, future large
telescopes, such as the Giant Magellan Telescope, may be able to detect them.


  Influence of the charge imbalance effect on the system of intrinsic Josephson
junctions of high temperature superconductors under external electromagnetic
radiation are investigated. We demonstrate that the charge imbalance is
responsible for a slope in the Shapiro step in the IV-characteristic. The
nonperiodic boundary conditions shift the Shapiro step from the canonical
position which determined by a frequency of external radiation. We also
demonstrate how the system parameters affect on the shift of Shapiro step.


  Although media content is increasingly produced, distributed, and consumed in
multiple combinations of modalities, how individual modalities contribute to
the perceived emotion of a media item remains poorly understood. In this paper
we present MusicVideos (MuVi), a novel dataset for affective multimedia content
analysis to study how the auditory and visual modalities contribute to the
perceived emotion of media. The data were collected by presenting music videos
to participants in three conditions: music, visual, and audiovisual.
Participants annotated the music videos for valence and arousal over time, as
well as the overall emotion conveyed. We present detailed descriptive
statistics for key measures in the dataset and the results of feature
importance analyses for each condition. Finally, we propose a novel transfer
learning architecture to train Predictive models Augmented with Isolated
modality Ratings (PAIR) and demonstrate the potential of isolated modality
ratings for enhancing multimodal emotion recognition. Our results suggest that
perceptions of arousal are influenced primarily by auditory information, while
perceptions of valence are more subjective and can be influenced by both visual
and auditory information. The dataset is made publicly available.


  We introduce and study a $d$-dimensional generalization of Hamiltonian cycles
in graphs - the Hamiltonian $d$-cycles in $K_n^d$ (the complete simplicial
$d$-complex over a vertex set of size $n$). Those are the simple $d$-cycles of
a complete rank, or, equivalently, of size $1 + {{n-1} \choose d}$.
  The discussion is restricted to the fields $F_2$ and $Q$. For $d=2$, we
characterize the $n$'s for which Hamiltonian $2$-cycles exist. For $d=3$ it is
shown that Hamiltonian $3$-cycles exist for infinitely many $n$'s. In general,
it is shown that there always exist simple $d$-cycles of size ${{n-1} \choose
d} - O(n^{d-3})$. All the above results are constructive.
  Our approach naturally extends to (and in fact, involves) $d$-fillings,
generalizing the notion of $T$-joins in graphs. Given a $(d-1)$-cycle $Z^{d-1}
\in K_n^d$, ~$F$ is its $d$-filling if $\partial F = Z^{d-1}$. We call a
$d$-filling Hamiltonian if it is acyclic and of a complete rank, or,
equivalently, is of size ${{n-1} \choose d}$. If a Hamiltonian $d$-cycle $Z$
over $F_2$ contains a $d$-simplex $\sigma$, then $Z\setminus \sigma$ is a a
Hamiltonian $d$-filling of $\partial \sigma$ (a closely related fact is also
true for cycles over $Q$). Thus, the two notions are closely related.
  Most of the above results about Hamiltonian $d$-cycles hold for Hamiltonian
$d$-fillings as well.


  Enhancing neural networks with knowledge of physical equations has become an
efficient way of solving various physics problems, from fluid flow to
electromagnetism. Graph neural networks show promise in accurately representing
irregularly meshed objects and learning their dynamics, but have so far
required supervision through large datasets. In this work, we represent meshes
naturally as graphs, process these using Graph Networks, and formulate our
physics-based loss to provide an unsupervised learning framework for partial
differential equations (PDE). We quantitatively compare our results to a
classical numerical PDE solver, and show that our computationally efficient
approach can be used as an interactive PDE solver that is adjusting boundary
conditions in real-time and remains sufficiently close to the baseline
solution. Our inherently differentiable framework will enable the application
of PDE solvers in interactive settings, such as model-based control of
soft-body deformations, or in gradient-based optimization methods that require
a fully differentiable pipeline.


  We introduce novel dynamic oracles for training two of the most accurate
known shift-reduce algorithms for constituent parsing: the top-down and
in-order transition-based parsers. In both cases, the dynamic oracles manage to
notably increase their accuracy, in comparison to that obtained by performing
classic static training. In addition, by improving the performance of the
state-of-the-art in-order shift-reduce parser, we achieve the best accuracy to
date (92.0 F1) obtained by a fully-supervised single-model greedy shift-reduce
constituent parser on the WSJ benchmark.


  Topological features in quantum computing provide controllability and noise
error avoidance in the performance of logical gates. While such resilience is
favored in the manipulation of quantum systems, it is very hard to identify
topological features in nature. This paper proposes a scheme where holonomic
quantum gates have intrinsic topological features. An ion trap is employed
where the vibrational modes of the ions are coherently manipulated with lasers
in an adiabatic cyclic way producing geometrical holonomic gates. A crucial
ingredient of the manipulation procedures is squeezing of the vibrational
modes, which effectively suppresses exponentially any undesired fluctuations of
the laser amplitudes, thus making the gates resilient to control errors.


  We introduce the Hydrangea simulations, a suite of 24 cosmological
hydrodynamic zoom-in simulations of massive galaxy clusters (M_200c =
10^14-10^15 M_Sun) with baryon particle masses of ~10^6 M_Sun. Designed to
study the impact of the cluster environment on galaxy formation, they are a key
part of the `Cluster-EAGLE' project (Barnes et al. 2017). They use a galaxy
formation model developed for the EAGLE project, which has been shown to yield
both realistic field galaxies and hot gas fractions of galaxy groups consistent
with observations. The total stellar mass content of the simulated clusters
agrees with observations, but central cluster galaxies are too massive, by up
to 0.6 dex. Passive satellite fractions are higher than in the field, and at
stellar masses Mstar > 10^10 M_Sun this environmental effect is quantitatively
consistent with observations. The predicted satellite stellar mass function
matches data from local cluster surveys. Normalized to total mass, there are
fewer low-mass (Mstar < 10^10 M_Sun) galaxies within the virial radius of
clusters than in the field, primarily due to star formation quenching.
Conversely, the simulations predict an overabundance of massive galaxies in
clusters compared to the field that persists to their far outskirts (>
5r_200c). This is caused by a significantly increased stellar mass fraction of
(sub-)haloes in the cluster environment, by up to ~0.3 dex even well beyond
r_200c. Haloes near clusters are also more concentrated than equally massive
field haloes, but these two effects are largely uncorrelated.


  The spectra of baryons at LHC can explain the features of the proton spectra
in cosmic rays (CR). It seems important to study all baryon data that are
available from collider experiments in wide range of energies. Transverse
momentum spectra of baryons from RHIC ($\sqrt(s)$=62 and 200 GeV) and from LHC
($\sqrt(s)$=0.9 and 7 TeV) have been considered. It is seen that the slope of
distributions at low $p_T$'s is changing with energy. The QGSM fit of these
spectra gives the average transverse momenta which behave as $s^{0.06}$ that is
similar to the previously observed behavior of $\Lambda^0$ hyperon spectra. The
change in average transverse momenta that are slowly growing in VHE hadron
interactions at CR detectors cannot cause the "knee" in measured cosmic ray
proton spectra. In addition, the available data on heavy quark hadron
production from LHC-b at $\sqrt{s}$=7 TeV were also studied. The preliminary
dependence of hadron average transverse momenta on their masses at LHC energy
is presented. The possible source of cosmic ray antiparticle-to-particle ratios
that are growing with energy was analyzed in the framework of QGSM, where the
growing ratios are the result of local leading asymmetry between the production
spectra of baryons and antibaryons in the kinematical region of proton target
fragmentation. In the laboratory system of cosmic ray measurements this
spectrum asymmetry will be seen as growing ratio of secondary
antiparticle-to-particle spectra until the certain energy of secondaries. This
conclusion makes the particle production at the sources of very high energy
cosmic protons important, if the interactions with positive target matter would
have place in proximity of these sources.


  Globular clusters are prone to lose stars while moving around the Milky Way.
These stars escape the clusters and are distributed throughout extended
envelopes or tidal tails. However, such extra-tidal structures are not observed
in all globular clusters, and yet there is no structural or dynamical
parameters that can predict their presence or absence. NGC\,6864 is an outer
halo globular cluster with reported no observed tidal tails. We used Dark
Energy Camera (DECam) photometry reaching $\sim$ 4 mag underneath its main
sequence turnoff to confidently detect an extra-tidal envelope, and stellar
debris spread across the cluster outskirts. These features emerged once robust
field star filtering techniques were applied to the fainter end of the observed
cluster main sequence. NGC\,6864 is associated to the {\it Gaia}-Enceladus
dwarf galaxy, among others 28 globular clusters. Up-to-date, nearly 64$\%$ of
them have been targeted looking for tidal tails and most of them have been
confirmed to exhibit tidal tails. Thus, the present outcomes allow us to
speculate on the possibility that {\it Gaia}-Enceladus globular clusters share
a common pattern of mass loss by tidal disruption.


  Given an ergodic dynamical system $(X,T,\mu)$, and $U\subset X$ measurable
with $\mu (U)>0$, let $\mu (U)\tau_U(x)$ denote the normalized hitting time of
$x\in X$ to $U$. We prove that given a sequence $(U_n)$ with $\mu (U_n)\to 0$,
the distribution function of the normalized hitting times to $U_n$ converges
weakly to some sub-probability distribution $F$ if and only if the distribution
function of the normalized return time converges weakly to some distribution
function $\tilde F$, and that in the converging case, $$ F(t)=\int_0^t(1-\tilde
F(s))ds, t\ge 0.\tag$\diamondsuit$ $$ This in particular characterizes
asymptotics for hitting times, and shows that the asymptotics for return times
is exponential if and only if the one for hitting times is too.


  We study the asymptotic behavior of the simple random walk on oriented
version of $\mathbb{Z}^2$. The considered latticesare not directed on the
vertical axis but unidirectional on the horizontal one, with symmetric random
orientations which are positively correlated. We prove that the simple random
walk is transient and also prove a functionnal limit theorem in the space of
cadlag functions, with an unconventional normalization.


  The longitudinal spin transfer represents the probability density of
producing longitudinally polarized hadrons from longitudinally polarized quarks
or circularly polarized gluons. It thus was usually measured in polarized
reactions or high-energy collisions where weak interaction dominates. In this
work, we propose the dihadron polarization correlation as a novel probe of this
quantity. Such an observable does not require the fragmenting partons to be
polarized and therefore can be measured in the currently available experimental
facilities, such as Belle, RHIC, Tevatron, and the LHC. We make quantitative
predictions for these experiments. In light of the data already harvested, the
experimental investigation of this observable provides more opportunity for the
quantitative study of the longitudinal spin transfer. In particular, the
measurements in pp collisions can significantly constrain the fragmentation
function of a circularly polarized gluon.


  A large class of supersymmetric quantum field theories, including all
theories with $\mathcal{N} = 2$ supersymmetry in three dimensions and theories
with $\mathcal{N} = 2$ supersymmetry in four dimensions, possess
topological-holomorphic sectors. We formulate Poisson vertex algebras in such
topological-holomorphic sectors and discuss some examples. For a
four-dimensional $\mathcal{N} = 2$ superconformal field theory, the associated
Poisson vertex algebra is the classical limit of a vertex algebra generated by
a subset of local operators of the theory.


  We present new H and K bands spectroscopy of 15 high luminosity active
galactic nuclei (AGNs) at redshifts 2.3-3.4 obtained on Gemini South. We
combined the data with spectra of additional 29 high-luminosity sources to
obtain a sample with 10^{45.2}<\lambda L_{\lambda}(5100A)<10^{47.3} ergs/sec
and black hole (BH) mass range, using reverberation mapping relationships based
on the H_beta method, of 10^{8.8}-10^{10.7} M_sun. We do not find a correlation
of L/L_Edd with M_BH but find a correlation with \lambda L_{\lambda}(5100A)
which might be due to selection effects. The L/L_Edd distribution is broad and
covers the range ~0.07-1.6, similar to what is observed in lower redshift,
lower luminosity AGNs. We suggest that this consistently measured and
calibrated sample gives the best representation of L/L_Edd at those redshifts
and note potential discrepancies with recent theoretical and observational
studies. The lower accretion rates are not in accord with growth scenarios for
BHs at such redshifts and the growth times of many of the sources are longer
than the age of the universe at the corresponding epochs. This suggests earlier
episodes of faster growth at z>~3 for those sources. The use of the C IV method
gives considerably different results and a larger scatter; this method seems to
be a poor M_BH and L/L_Edd estimator at very high luminosity.


  We report recent simulation results which might indicate the existence of a
new low-temperature "phase" in an Ising lattice gas, driven into a
non-equilibrium steady state by an external field. It appears that this
"phase", characterized by multiple-strip configurations, is selected when
square systems are used to approach the thermodynamic limit. We propose a
quantitative criterion for the existence of such a "phase". If confirmed, its
observation may resolve a long-standing controversy over the critical
properties of the driven Ising lattice gas.


  Let $p$ be an odd prime number, $D_p$ be the dihedral group of order $2p$,
$h_p$ and $h^+_p$ be the class numbers of $\bm{Q}(\zeta_p)$ and
$\bm{Q}(\zeta_p+ \zeta_p^{-1})$ respectively. Theorem. $h_p^+=1$ if and only
if, for any field $k$ admitting a $D_p$-extension, all the algebraic $D_p$-tori
over $k$ are stably rational. A similar result for $h_p=1$ and $C_p$-tori is
valid also.


  The Weyl semimetal NbP exhibits a very small Fermi surface consisting of two
electron and two hole pockets, whose fourfold degeneracy in $k$ space is tied
to the rotational symmetry of the underlying tetragonal crystal lattice. By
applying uniaxial stress, the crystal symmetry can be reduced, which
successively leads to a degeneracy lifting of the Fermi-surface pockets. This
is reflected by a splitting of the Shubnikov-de Haas frequencies when the
magnetic field is aligned along the $c$ axis of the tetragonal lattice. In this
study, we present the measurement of Shubnikov-de Haas oscillations of
single-crystalline NbP samples under uniaxial tension, combined with
state-of-the-art calculations of the electronic band structure. Our results
show qualitative agreement between calculated and experimentally determined
Shubnikov-de Haas frequencies, demonstrating the robustness of the
band-structure calculations upon introducing strain. Furthermore, we predict a
significant shift of the Weyl points with increasing uniaxial tension, allowing
for an effective tuning to the Fermi level at only 0.8% of strain along the $a$
axis.


  Online voting is attractive for convenience and accessibility, but is more
susceptible to voter coercion and vote buying than in-person voting. One
mitigation is to give voters fake voting credentials that they can yield to a
coercer. Fake credentials appear identical to real ones, but cast votes that
are silently omitted from the final tally. An important unanswered question is
how ordinary voters perceive such a mitigation: whether they could understand
and use fake credentials, and whether the coercion risks justify the costs of
mitigation. We present the first systematic study of these questions, involving
150 diverse individuals in Boston, Massachusetts. All participants "registered"
and "voted" in a mock election: 120 were exposed to coercion resistance via
fake credentials, the rest forming a control group. Of the 120 participants
exposed to fake credentials, 96% understood their use. 53% reported that they
would create fake credentials in a real-world voting scenario, given the
opportunity. 10% mistakenly voted with a fake credential, however. 22% reported
either personal experience with or direct knowledge of coercion or vote-buying
incidents. These latter participants rated the coercion-resistant system
essentially as trustworthy as in-person voting via hand-marked paper ballots.
Of the 150 total participants to use the system, 87% successfully created their
credentials without assistance; 83% both successfully created and properly used
their credentials. Participants give a System Usability Scale score of 70.4,
which is slightly above the industry's average score of 68. Our findings appear
to support the importance of the coercion problem in general, and the promise
of fake credentials as a possible mitigation, but user error rates remain an
important usability challenge for future work.


  Many lighting methods used in computer graphics such as indirect illumination
can have very high computational costs and need to be approximated for
real-time applications. These costs can be reduced by means of upsampling
techniques which tend to introduce artifacts and affect the visual quality of
the rendered image. This paper suggests a versatile approach for accelerating
the rendering of screen space methods while maintaining the visual quality.
This is achieved by exploiting the low frequency nature of many of these
illumination methods and the geometrical continuity of the scene. First the
screen space is dynamically divided into separate sub-images, then the
illumination is rendered for each sub-image in an adequate resolution and
finally the sub-images are put together in order to compose the final image.
Therefore we identify edges in the scene and generate masks precisely
specifying which part of the image is included in which sub-image. The masks
therefore determine which part of the image is rendered in which resolution. A
step wise upsampling and merging process then allows optically soft transitions
between the different resolution levels. For this paper, the introduced
multi-resolution rendering method was implemented and tested on three commonly
used lighting methods. These are screen space ambient occlusion, soft shadow
mapping and screen space global illumination.


  Being one of the most popular generative framework, variational
autoencoders(VAE) are known to suffer from a phenomenon termed posterior
collapse, i.e. the latent variational distributions collapse to the prior,
especially when a strong decoder network is used. In this work, we analyze the
latent representation of collapsed VAEs, and proposed a novel model, neighbor
embedding VAE(NE-VAE), which explicitly constraints the encoder to encode
inputs close in the input space to be close in the latent space. We observed
that for VAE variants that report similar ELBO, KL divergence or even mutual
information scores may still behave quite differently in the latent
organization. In our experiments, NE-VAE can produce qualitatively different
latent representations with majority of the latent dimensions remained active,
which may benefit downstream latent space optimization tasks. NE-VAE can
prevent posterior collapse to a much greater extent than it's predecessors, and
can be easily plugged into any autoencoder framework, without introducing
addition model components and complex training routines.


  Binaural reproduction for headphone-based listening is an active research
area due to its widespread use in evolving technologies such as augmented and
virtual reality (AR and VR). On the one hand, these applications demand high
quality spatial audio perception to preserve the sense of immersion. On the
other hand, recording devices may only have a few microphones, leading to
low-order representations such as first-order Ambisonics (FOA). However,
first-order Ambisonics leads to limited externalization and spatial resolution.
In this paper, a novel head-related transfer function (HRTF) preprocessing
optimization loss is proposed, and is minimized using nonlinear programming.
The new method, denoted iMagLS, involves the introduction of an interaural
level difference (ILD) error term to the now widely used MagLS optimization
loss for the lateral plane angles. Results indicate that the ILD error could be
substantially reduced, while the HRTF magnitude error remains similar to that
obtained with MagLS. These results could prove beneficial to the overall
spatial quality of first-order Ambisonics, while other reproduction methods
could also benefit from considering this modified loss.


  We present a global analysis of available data on inclusive structure
functions and reduced cross sections measured in electron-proton scattering at
small values of Bjorken-x, x<0.01, including the latest data from HERA on
reduced cross sections. Our approach relies on the dipole formulation of DIS
together with the use of the non-linear running coupling BK equation for the
description of the small-x dynamics. We improve our previous studies by
including the heavy quark (charm and beauty) contribution to the reduced cross
sections, and also by considering a variable flavor scheme for the running of
the coupling. We obtain a good description of data, the fit parameters
remaining stable with respect to our previous analyses where only light quarks
were considered. The inclusion of the heavy quark contributions resulted in a
good description of available experimental data for the charm component of the
structure function and reduced cross section provide the initial transverse
distribution of heavy quarks was allowed to differ (more specifically, to have
a smaller radius) from that of the light flavors.


  The mechanism of backbending is semi-phenomenologically investigated based on
the hybridization of two rotational bands. These bands are defined by treating
a model Hamiltonian describing two interacting subsystems: a set of particles
moving in a deformed mean field and interacting among themselves through an
effective pairing force and a phenomenological deformed core whose intrinsic
ground state is an axially symmetric coherent boson state. The two components
interact with each other by a quadrupole-quadrupole and a spin-spin
interaction. The total Hamiltonian is considered in the space of states with
good angular momentum, projected from a quadrupole deformed product function.
The single-particle factor function defines the nature of the rotational bands,
one corresponding to the ground band in which all particles are paired and
another one built upon a $i_{13/2}$ neutron broken pair. The formalism is
applied to six deformed even-even nuclei, known as being good backbenders.
Agreement between theory and experiment is fairly good.


  We investigate the correlation between the integrated low-frequency and
infrared (IR) emissions of star-forming galaxies extracted from the {\sl
Herschel} Reference Survey. By taking advantage of the GaLactic Extragalactic
All-sky MWA (GLEAM) survey operated by the Murchison Widefield Array (MWA) we
examine how this correlation varies at a function of frequency across the 20
GLEAM narrow bands at $72\mbox{--}231\; [\mbox{MHz}]$. These examinations are
important for ensuring the reliability of the radio luminosity as a SFR
indicator. In this study, we focus on 18 star-forming galaxies whose radio
emission is detected by the GLEAM survey. These galaxies show that a single
power-law is sufficient to characterise the far-infrared-to-radio correlation
across the GLEAM frequency bands and up to $1.5\; [\mbox{GHz}]$. Thus, the
radio continuum in this wavelength range can serve as a good dust
extinction-free SFR estimator. This is particularly important for future
investigation of the cosmic SFR independently from other estimators, since the
radio continuum can be detected from $z=0$ to high redshifts ($z \sim
5\mbox{--}10$) in a coherent manner.


  We study the nature of the scalar D_0 meson from the viewpoint of chiral
symmetry. With the linear representation of chiral symmetry, we construct the D
pi scattering amplitude satisfying the chiral low-energy theorem, in which the
D_0 meson appears as an s-wave resonance. We show that the properties of the
D_0 meson can be successfully reproduced as the chiral partner of the D meson
coupled with the D pi scattering states. At the same time, we find that the
spectral function and the pole position of D_0 are not very sensitive to the
reduction of the chiral condensate, indicating the importance of the dressing
of the bare state by the D pi molecular component.


  We investigate tree tensor network states for quantum chemistry. Tree tensor
network states represent one of the simplest generalizations of matrix product
states and the density matrix renormalization group. While matrix product
states encode a one-dimensional entanglement structure, tree tensor network
states encode a tree entanglement structure, allowing for a more flexible
description of general molecules. We describe an optimal tree tensor network
state algorithm for quantum chemistry. We introduce the concept of
half-renormalization which greatly improves the efficiency of the calculations.
Using our efficient formulation we demonstrate the strengths and weaknesses of
tree tensor network states versus matrix product states. We carry out benchmark
calculations both on tree systems (hydrogen trees and \pi-conjugated
dendrimers) as well as non-tree molecules (hydrogen chains, nitrogen dimer, and
chromium dimer). In general, tree tensor network states require much fewer
renormalized states to achieve the same accuracy as matrix product states. In
non-tree molecules, whether this translates into a computational savings is
system dependent, due to the higher prefactor and computational scaling
associated with tree algorithms. In tree like molecules, tree network states
are easily superior to matrix product states. As an ilustration, our largest
dendrimer calculation with tree tensor network states correlates 110 electrons
in 110 active orbitals.


  The nonlinear Zeeman effect can induce splitting and asymmetries of
magnetic-resonance lines in the geophysical magnetic field range. This is a
major source of "heading error" for scalar atomic magnetometers. We demonstrate
a method to suppress the nonlinear Zeeman effect and heading error based on
spin locking. In an all-optical synchronously pumped magnetometer with separate
pump and probe beams, we apply a radio-frequency field which is in-phase with
the precessing magnetization. In an earth-range field, a multi-component
asymmetric magnetic-resonance line with ? 60 Hz width collapses into a single
peak with a width of 22 Hz, whose position is largely independent of the
orientation of the sensor. The technique is expected to be broadly applicable
in practical magnetometry, potentially boosting the sensitivity and accuracy of
earth-surveying magnetometers by increasing the magnetic resonance amplitude,
decreasing its width and removing the important and limiting heading-error
systematic.


  We present a quantum localization phenomenon that exists in periodically
kicked 3D rotors, but is absent in the commonly studied 2D ones: edge
localization. We show that under the condition of a fractional quantum
resonance there are states of the kicked rotor that are strongly localized near
the edge of the angular momentum space at $J=0$. These states are analogs of
surface states in crystalline solids, and they significantly affect resonant
excitation of molecular rotation by laser pulse trains.


  We present a novel technique for the determination of the topological
susceptibility (related to the variance of the distribution of global
topological charge) from lattice gauge theory simulations, based on
maximum-likelihood analysis of the Markov-chain Monte Carlo time series. This
technique is expected to be particularly useful in situations where relatively
few tunneling events are observed. Restriction to a lattice subvolume on which
topological charge is not quantized is explored, and may lead to further
improvement when the global topology is poorly sampled. We test our proposed
method on a set of lattice data, and compare it to traditional methods.


  This study conducts a comparative analysis of national policies on Generative
AI across four countries: China, Japan, Mongolia, and the USA. Employing the
Qualitative Comparative Analysis (QCA) method, it examines the responses of
these nations to Generative AI in higher education settings, scrutinizing the
diversity in their approaches within this group. While all four countries
exhibit a positive attitude toward Generative AI in higher education, Japan and
the USA prioritize a human-centered approach and provide direct guidance in
teaching and learning. In contrast, China and Mongolia prioritize national
security concerns, with their guidelines focusing more on the societal level
rather than being specifically tailored to education. Additionally, despite all
four countries emphasizing diversity, equity, and inclusion, they consistently
fail to clearly discuss or implement measures to address the digital divide. By
offering a comprehensive comparative analysis of attitudes and policies
regarding Generative AI in higher education across these countries, this study
enriches existing literature and provides policymakers with a global
perspective, ensuring that policies in this domain promote inclusion rather
than exclusion.


  In this paper, we consider a dynamic viscoelastic contact problem with
friction and wear, and describe it as a system of nonlinear partial
differential equations. We formulate the previous problem as a hyperbolic
quasi-variational inequality by employing the variational method. We adopt the
Rothe method to show the existence and uniqueness of weak solution for the
hyperbolic quasi-variational inequality under mild conditions. We also give a
fully discrete scheme for solving the hyperbolic quasi-variational inequality
and obtain error estimates for the fully discrete scheme.


  This paper discusses the Higgs and spinor fermion terms of the D4-D5-E6 model
of a series of papers (hep-ph/9301210, hep-th/9302030, hep-th/9306011, and
hep-th/9402003) an 8-dimensional spacetime is reduced to 4-dimensions. The
gauge boson terms give SU(3)xSU(2)xU(1) for the color, weak, and
electromagnetic forces and gravity of the MacDowell-Mansouri type, which has
recently been shown by Nieto, Obregon, and Socorro (gr-qc/9402029) to be
equivalent, up to a Pontrjagin topological term, to the Ashtekar formulation.


  A DPMJET-III model (DPMJET-III-2011) with chain fusion adjusted to include
energy.dependent parameters is used to calculate inclusive distributions in p-p
collisions at LHC energies. Presented are charged hadrons rapidity
distributions, transverse momentum distributions, multiplicity distributions as
well as multiplicities at mid-rapidity as function of the collision energy. For
hadrons with strangeness we present cms-rapidity distributions and transverse
momentum distributions. With the considered merely energy-dependent adjustments
the obtained agreement with the transversal \Lambda and \Xi distribution is not
satisfactory.


  Given a smooth bounded planar domain, we construct a compact set on the
boundary s.t. its characteristic function is not the trace of a least gradient
function. This generalize the construction of Spradlin and Tamasan [ST14] on
the disc.


  We develop an approach to construct local bulk operators in a CFT to order
$1/N^2$. Since 4-point functions are not fixed by conformal invariance we use
the OPE to categorize possible forms for a bulk operator. Using previous
results on 3-point functions we construct a local bulk operator in each OPE
channel. We then impose the condition that the bulk operators constructed in
different channels agree, and hence give rise to a well-defined bulk operator.
We refer to this condition as the "bulk bootstrap." We argue and explicitly
show in some examples that the bulk bootstrap leads to some of the same results
as the regular conformal bootstrap. In fact the bulk bootstrap provides an
easier way to determine some CFT data, since it does not require knowing the
form of the conformal blocks. This analysis clarifies previous results on the
relation between bulk locality and the bootstrap for theories with a $1/N$
expansion, and it identifies a simple and direct way in which OPE coefficients
and anomalous dimensions determine the bulk equations of motion to order
$1/N^2$.


  We present MBIS (Multivariate Bayesian Image Segmentation tool), a clustering
tool based on the mixture of multivariate normal distributions model. MBIS
supports multi-channel bias field correction based on a B-spline model. A
second methodological novelty is the inclusion of graph-cuts optimization for
the stationary anisotropic hidden Markov random field model. Along with MBIS,
we release an evaluation framework that contains three different experiments on
multi-site data. We first validate the accuracy of segmentation and the
estimated bias field for each channel. MBIS outperforms a widely used
segmentation tool in a cross-comparison evaluation. The second experiment
demonstrates the robustness of results on atlas-free segmentation of two image
sets from scan-rescan protocols on 21 healthy subjects. Multivariate
segmentation is more replicable than the monospectral counterpart on
T1-weighted images. Finally, we provide a third experiment to illustrate how
MBIS can be used in a large-scale study of tissue volume change with increasing
age in 584 healthy subjects. This last result is meaningful as multivariate
segmentation performs robustly without the need for prior knowledge


  Motivation: Deep learning models deployed for use on medical tasks can be
equipped with Out-of-Distribution Detection (OoDD) methods in order to avoid
erroneous predictions. However it is unclear which OoDD method should be used
in practice. Specific Problem: Systems trained for one particular domain of
images cannot be expected to perform accurately on images of a different
domain. These images should be flagged by an OoDD method prior to diagnosis.
Our approach: This paper defines 3 categories of OoD examples and benchmarks
popular OoDD methods in three domains of medical imaging: chest X-ray, fundus
imaging, and histology slides. Results: Our experiments show that despite
methods yielding good results on some categories of out-of-distribution
samples, they fail to recognize images close to the training distribution.
Conclusion: We find a simple binary classifier on the feature representation
has the best accuracy and AUPRC on average. Users of diagnostic tools which
employ these OoDD methods should still remain vigilant that images very close
to the training distribution yet not in it could yield unexpected results.


  The height of an algebraic number $\alpha$ is a measure of how arithmetically
complicated $\alpha$ is. We say $\alpha$ is totally $p$-adic if the minimal
polynomial of $\alpha$ splits completely over the field $\mathbb{Q}_p$ of
$p$-adic numbers. In this paper, we investigate what can be said about the
smallest nonzero height of a degree $3$ totally $p$-adic number. In particular,
we provide an algorithm to determine, given a prime $p$, the smallest height of
a degree $3$ totally $p$-adic number.


  Statistical hypothesis testing serves as statistical evidence for scientific
innovation. However, if the reported results are intentionally biased,
hypothesis testing no longer controls the rate of false discovery. In
particular, we study such selection bias in machine learning models where the
reporter is motivated to promote an algorithmic innovation. When the number of
possible configurations (e.g., datasets) is large, we show that the reporter
can falsely report an innovation even if there is no improvement at all. We
propose a `post-reporting' solution to this issue where the bias of the
reported results is verified by another set of results. The theoretical
findings are supported by experimental results with synthetic and real-world
datasets.


  Large-scale pre-trained text-image models with dual-encoder architectures
(such as CLIP) are typically adopted for various vision-language applications,
including text-image retrieval. However,these models are still less practical
on edge devices or for real-time situations, due to the substantial indexing
and inference time and the large consumption of computational resources.
Although knowledge distillation techniques have been widely utilized for
uni-modal model compression, how to expand them to the situation when the
numbers of modalities and teachers/students are doubled has been rarely
studied. In this paper, we conduct comprehensive experiments on this topic and
propose the fully-Connected knowledge interaction graph (Cona) technique for
cross-modal pre-training distillation. Based on our findings, the resulting
ConaCLIP achieves SOTA performances on the widely-used Flickr30K and MSCOCO
benchmarks under the lightweight setting. An industry application of our method
on an e-commercial platform further demonstrates the significant effectiveness
of ConaCLIP.


  We propose an arrangement of the most commonly invoked version of the
two-nucleon chiral potential such that the low-lying amplitude zero of the 1S0
partial wave is captured at leading order of the effective expansion. Adopting
other partial waves from the LENPIC interaction, we show how this modification
yields an improved description of ground-state energies and point-proton radii
of three test nuclei.


  Spectral response functions are central quantities in the analysis of quantum
many-body states, since they describe the response of many-body systems to
external perturbations and hence directly correspond to observables in
experiments. In this paper, we evaluate a momentum-averaged dynamical density
structure factor for the fermionic $\nu=1/3$ fractional quantum Hall state on a
torus, using the continued fraction method to compute the dynamical correlation
function. We establish the scaling behavior of the screened Coulomb structure
factor with respect to interaction range, and expose an inherent
self-similarity of structure factors in the frequency domain. These results
highlight the statistical properties of spectral response functions for
fractional quantum Hall states and show how they can be efficiently
approximated in numerical models.


  The most widely used technology to identify the proteins present in a complex
biological sample is tandem mass spectrometry, which quickly produces a large
collection of spectra representative of the peptides (i.e., protein
subsequences) present in the original sample. In this work, we greatly expand
the parameter learning capabilities of a dynamic Bayesian network (DBN)
peptide-scoring algorithm, Didea, by deriving emission distributions for which
its conditional log-likelihood scoring function remains concave. We show that
this class of emission distributions, called Convex Virtual Emissions (CVEs),
naturally generalizes the log-sum-exp function while rendering both maximum
likelihood estimation and conditional maximum likelihood estimation concave for
a wide range of Bayesian networks. Utilizing CVEs in Didea allows efficient
learning of a large number of parameters while ensuring global convergence, in
stark contrast to Didea's previous parameter learning framework (which could
only learn a single parameter using a costly grid search) and other trainable
models (which only ensure convergence to local optima). The newly trained
scoring function substantially outperforms the state-of-the-art in both scoring
function accuracy and downstream Fisher kernel analysis. Furthermore, we
significantly improve Didea's runtime performance through successive
optimizations to its message passing schedule and derive explicit connections
between Didea's new concave score and related MS/MS scoring functions.


  Leptoquarks have been proposed as a possible explanation of anomalies in
$\bar{B}\mapsto D^{*} \tau \bar{\nu } $ decays, the apparent anomalies in
$(g-2)_\mu$ experiments and a violation of lepton universality. Motivated by
this, we examine other motivations of leptoquarks: radiatively induced neutrino
masses in the presence of a discrete symmetry that prevents a tree level
see-saw mechanism, gauge coupling unification, and vacuum stability at least up
to the unification scale. We present a new model for radiatively generating a
neutrino mass which can significantly improve gauge coupling unification at one
loop. We discuss this, and other models in the light of recent work on flavour
anomalies.


  We introduce an experimental test for ruling out classical explanations for
the statistics obtained when measuring arbitrary observables at arbitrary times
using individual detectors. This test requires some trust in the measurements,
represented by a few natural assumptions on the detectors. In quantum theory,
the considered scenarios are well captured by von Neumann measurements. These
can be described naturally in terms of the Keldysh quasi-probability
distribution (KQPD), and the imprecision and backaction exerted by the
measurement apparatus. We find that classical descriptions can be ruled out
from measured data if and only if the KQPD exhibits negative values. We provide
examples based on simulated data, considering the influence of a finite amount
of statistics. In addition to providing an experimental tool for certifying
non-classicality, our results bestow an operational meaning upon the
non-classical nature of negative quasi-probability distributions such as the
Wigner function and the full counting statistics.


  Leveraging Large Language Models (LLMs) as judges for judging the performance
of LLMs has recently garnered attention. However, this type of approach is
affected by the potential biases in LLMs, raising concerns about the
reliability of the evaluation results. To mitigate this issue, we propose and
study two versions of many-shot in-context prompts, which rely on two existing
settings of many-shot ICL for helping GPT-4o-as-a-Judge in single answer
grading to mitigate the potential biases in LLMs, Reinforced ICL and
Unsupervised ICL. Concretely, the former utilizes in-context examples with
model-generated rationales, and the latter without. Based on the designed
prompts, we investigate the impact of scaling the number of in-context examples
on the consistency and quality of the judgment results. Furthermore, we reveal
the symbol bias hidden in the pairwise comparison of GPT-4o-as-a-Judge and
propose a simple yet effective approach to mitigate it. Experimental results
show that advanced long-context LLMs, such as GPT-4o, perform better in the
many-shot regime than in the zero-shot regime. Meanwhile, the experimental
results further verify the effectiveness of the symbol bias mitigation
approach.


  We aim at understanding the formation of cloud layers in quasi-static
substellar atmospheres. The time-dependent description presented in (Helling &
Woitke 2006) is a kinetic model describing nucleation, growth and evaporation.
It is extended to treat gravitational settling and is applied to the
static-stationary case of substellar model atmospheres. From the solution for
the dust moments, we determine the grain size distribution function which,
together with the calculated material volume fractions, provides the basis to
calculate the opacities of the composite dust grains. The cloud particles in
brown dwarfs and hot giant-gas planets are found to be small in the high
atmospheric layers (0.01mum), and composed of a rich mixture of all considered
condensates, in particular the abundant MgSiO3[s], Mg2SiO4[s] and SiO2[s]. As
the particles settle downward, they increase in size and reach several 100mum
in the deepest layers. The more volatile parts of the grains evaporate and the
particles stepwise purify to form composite particles of high-temperature
condensates in the deeper layers, mainly Fe[s] and Al2O3[s]. The gas phase
abundances of the elements involved in the dust formation process vary by
orders of magnitudes throughout the atmosphere. The grain size distribution is
found to be relatively broad in the upper atmospheric layers but often strongly
peaked in the deeper layers. The spectral appearance of the cloud layers in the
mid IR (7-20mum) is close to a grey body with only weak broad features on a few
percent level, mainly caused by MgSiO3[s], and Mg2SiO4[s]. Our models predict
that the gas phase depletion is much weaker as compared to phase-equilibrium
calculations in the high atmospheric layers. [abridged]


  The simplest interpretation of the global success of the Standard Model is
that new physics decouples well above the electroweak scale. Supersymmetric
extension of the Standard Model offers the possibility of light chargino and
the right-handed stop (with masses below $M_Z$), and still maintaining the
successful predictions of the Standard Model. The value of $R_b$ can then be
enhanced up to $\sim 0.218$ (the Standard Model value is $\sim 0.216$). Light
chargino and stop give important contribution to rare processes such as
$b\rightarrow s \gamma$, $\overline K^0-K^0$ and $\overline B^0-B^0$ mixing but
consistency with experimental results is maintained in a large region of the
parameter space. The exotic four-jet events reported by ALEPH (if confirmed)
may constitute a signal for supersymmetry with such a light spectrum and with
explicitly broken $R-$parity. Their interpretation as pair production of
charginos with $m_C\sim 60$ GeV, with subsequent decay $C\rightarrow \tilde t_R
b \rightarrow dsb$ (where $m_{\tilde t}\sim 55$ GeV) leads to signatures very
close to the experimental observations.


  Chae's analyses on GAIA observations of wide binary stars have fortified the
paradigm of extended gravity with particular attention to MOND-like theories.
We recall that, starting from the origin of Einstein's general relativity, the
request of Mach on the structure of the theory has been the core of the
foundational debate. This issue is strictly connected with the nature of the
mass-energy equivalence. This was exactly the key point that Einstein used to
derive the same general relativity. On the other hand, the current requirements
of particle physics and the open questions within extended gravity theories,
which have recently been further strengthened by analyses of GAIA observations,
request a better understanding of the Equivalence Principle. By considering a
direct coupling between the Ricci curvature scalar and the matter Lagrangian a
non geodesic ratio between the inertial and the gravitational mass can be fixed
and MOND-like theories are retrieved at low energies.


  This work proposes a two-dimensional electrophysiological model for
describing neuronal responses to external electric stimuli under patch-clamped
conditions. Our proposed model successfully captures the key features of the
Hodgkin-Huxley model, while offering improved informativeness and numerical
efficiency.
  By analysing bifurcation diagrams from various reduced models, we describe
the contributions of different ionic channels to the stability or instability
of the neurones' response. We also explore the influence of various cell
parameters in the neurone's spiking frequency, including the membrane
capacitance and the ionic channels' conductivities and Nerst potentials.
  Additionally, we suggest a spatial model for the axon that effectively
simulates unidirectional signal transmission along neurons unaffected by
membrane potential perturbations. After analysing the characteristics of this
compartmental model, including the impact of intracellular resistance and
membrane capacitance on the signal's velocity, we observed considerable
discrepancies between our findings and those predicted by the cable equation
model for signal propagation.
  Moreover, our investigation reveals that when the transmission of neuronal
signals occurs in multiple peaks, there is a transient variation in their
wavelength and frequency, resulting in different peak velocities. Furthermore,
our findings consistently demonstrate that the first peak - in some cases, the
only peak observed - maintains a relatively constant velocity along the axon
regardless of the stimulus intensity and is always faster than the subsequent
peaks.


  We demonstrate that the distribution of betweenness centrality (BC), a global
structural metric based on network flow, is an invariant quantity in most
planar graphs. We confirm this invariance through an empirical analysis of
street networks from 97 of the most populous cities worldwide, at scales
significantly larger than previous studies. We also find that the BC
distribution is robust to major alterations in the network, including
significant changes to its topology and edge weight structure, indicating that
the only relevant factors shaping the distribution are the number of nodes and
edges as well as the constraint of planarity. Through simulations of random
planar graph models and analytical calculations on Cayley trees, this
invariance is demonstrated to be a consequence of a bimodal regime consisting
of an underlying tree structure for high BC nodes, and a low BC regime arising
from the presence of loops providing local path alternatives. Furthermore, the
high BC nodes display a non-trivial spatial dependence, with increasing spatial
correlation as a function of the number of edges, leading them to cluster
around the barycenter at large densities. Our results suggest that the spatial
distribution of the BC is a more accurate discriminator when comparing patterns
across cities. Moreover, the BC being a static predictor of congestion in
planar graphs, the observed invariance and spatial dependence has practical
implications for infrastructural and biological networks. In particular, for
the case of street networks, as long as planarity is conserved, bottlenecks
continue to persist, and the effect of planned interventions to alleviate
structural congestion will be limited primarily to load redistribution, a
feature confirmed by analyzing 200 years of data for central Paris.


  We study Sims-Yeend's product system C*-algebras and topological higher-rank
graph C*-algebras by Yeend. We give a relation between Katsura's Cuntz-Pimsner
covariance and Sims-Yeend's one by a direct approach and an explicit form of
the core of product system C*-algebras. Finally, we prove Cuntz-Krieger type
uniqueness theorem for topological higher-rank graph C*-algebras under certain
aperiodic condition.


  Improving software performance through configuration parameter tuning is a
common activity during software maintenance. Beyond traditional performance
metrics like latency, mobile app developers are interested in reducing app
energy usage. Some mobile apps have centralized locations for parameter tuning,
similar to databases and operating systems, but it is common for mobile apps to
have hundreds of parameters scattered around the source code. The correlation
between these "deep" parameters and app energy usage is unclear. Researchers
have studied the energy effects of deep parameters in specific modules, but we
lack a systematic understanding of the energy impact of mobile deep parameters.
  In this paper we empirically investigate this topic, combining a developer
survey with systematic energy measurements. Our motivational survey of 25
Android developers suggests that developers do not understand, and largely
ignore, the energy impact of deep parameters. To assess the potential
implications of this practice, we propose a deep parameter energy profiling
framework that can analyze the energy impact of deep parameters in an app. Our
framework identifies deep parameters, mutates them based on our parameter value
selection scheme, and performs reliable energy impact analysis. Applying the
framework to 16 popular Android apps, we discovered that deep parameter-induced
energy inefficiency is rare. We found only 2 out of 1644 deep parameters for
which a different value would significantly improve its app's energy
efficiency. A detailed analysis found that most deep parameters have either no
energy impact, limited energy impact, or an energy impact only under extreme
values. Our study suggests that it is generally safe for developers to ignore
the energy impact when choosing deep parameter values in mobile apps.


  We present the software library libCreme which we have previously used to
successfully calculate convex-roof entanglement measures of mixed quantum
states appearing in realistic physical systems. Evaluating the amount of
entanglement in such states is in general a non-trivial task requiring to solve
a highly non-linear complex optimization problem. The algorithms provided here
are able to achieve to do this for a large and important class of entanglement
measures. The library is mostly written in the Matlab programming language, but
is fully compatible to the free and open-source Octave platform. Some
inefficient subroutines are written in C/C++ for better performance. This
manuscript discusses the most important theoretical concepts and workings of
the algorithms, focussing on the actual implementation and usage within the
library. Detailed examples in the end should make it easy for the user to apply
libCreme to specific problems.


  We present the results of a search for dark matter production in the monojet
signature. We analyze a sample of Tevatron pp-bar collisions at sqrt(s)=1.96
TeV corresponding to an integrated luminosity of 6.7/fb recorded by the CDF II
detector. In events with large missing transverse energy and one energetic jet,
we find good agreement between the standard model prediction and the observed
data. We set 90% confidence level upper limits on the dark matter production
rate. The limits are translated into bounds on nucleon-dark matter scattering
rates which are competitive with current direct detection bounds on
spin-independent interaction below a dark matter candidate mass of 5 GeV/c^2,
and on spin-dependent interactions up to masses of 200 GeV/c^2.


In this article we derive some polynomial inequalities for Mertens functions.


  Automatic Speech Recognition (ASR) is a technology that converts spoken words
into text, facilitating interaction between humans and machines. One of the
most common applications of ASR is Speech-To-Text (STT) technology, which
simplifies user workflows by transcribing spoken words into text. In the
medical field, STT has the potential to significantly reduce the workload of
clinicians who rely on typists to transcribe their voice recordings. However,
developing an STT model for the medical domain is challenging due to the lack
of sufficient speech and text datasets. To address this issue, we propose a
medical-domain text correction method that modifies the output text of a
general STT system using the Vision Language Pre-training (VLP) method. VLP
combines textual and visual information to correct text based on image
knowledge. Our extensive experiments demonstrate that the proposed method
offers quantitatively and clinically significant improvements in STT
performance in the medical field. We further show that multi-modal
understanding of image and text information outperforms single-modal
understanding using only text information.


  We show that for each countable simplicial complex P the following conditions
are equivalent: (1) $P \in AE(X)$ iff $P \in AE(\beta X)$ for any space X; (2)
There exists a P-invertible map of a metrizable compactum X with $P \in AE(X)$
onto the Hilbert cube.


  Graph data has a unique structure that deviates from standard data
assumptions, often necessitating modifications to existing methods or the
development of new ones to ensure valid statistical analysis. In this paper, we
explore the notion of correlation and dependence between two binary graphs.
Given vertex communities, we propose community correlations to measure the edge
association, which equals zero if and only if the two graphs are conditionally
independent within a specific pair of communities. The set of community
correlations naturally leads to the maximum community correlation, indicating
conditional independence on all possible pairs of communities, and to the
overall graph correlation, which equals zero if and only if the two binary
graphs are unconditionally independent. We then compute the sample community
correlations via graph encoder embedding, proving they converge to their
respective population versions, and derive the asymptotic null distribution to
enable a fast, valid, and consistent test for conditional or unconditional
independence between two binary graphs. The theoretical results are validated
through comprehensive simulations, and we provide two real-data examples: one
using Enron email networks and another using mouse connectome graphs, to
demonstrate the utility of the proposed correlation measures.


  Both axial and radial junction nanowire solar cells have their challenges and
advantages. However, so far, there is no review that explicitly provides a
detailed comparative analysis of both axial and radial junction solar cells.
This article reviews some of the recent results on axial and radial junction
nanowire solar cells with an attempt to perform a comparative study between the
optical and device behavior of these cells. In particular, we start by
reviewing different results on how the absorption can be tuned in axial and
radial junction solar cells. We also discuss results on some of the critical
device concepts that are required to achieve high efficiency in axial and
radial junction solar cells. We include a section on new device concepts that
can be realized in nanowire structures. Finally, we conclude this review by
discussing a few of the standing challenges of nanowire solar cells.


  Jeffries & Binks (2014) and Malo et al. (2014) have recently reported Li
depletion boundary (LDB) ages for the {\beta} Pictoris moving group (BPMG)
which are twice as old as the oft-cited kinematic age of $\sim$12 Myr. In this
study we present (1) a new evaluation of the internal kinematics of the BPMG
using the revised Hipparcos astrometry and best available published radial
velocities, and assess whether a useful kinematic age can be derived, and (2)
derive an isochronal age based on the placement of the A-, F- and G-type stars
in the colour-magnitude diagram (CMD). We explore the kinematics of the BPMG
looking at velocity trends along Galactic axes, and conducting traceback
analyses assuming linear trajectories, epicyclic orbit approximation, and orbit
integration using a realistic gravitational potential. None of the
methodologies yield a kinematic age with small uncertainties using modern
velocity data. Expansion in the Galactic X and Y directions is significant only
at the 1.7{\sigma} and 2.7{\sigma} levels, and together yields an overall
kinematic age with a wide range (13-58 Myr; 95 per cent CL). The A-type members
are all on the zero age-main-sequence, suggestive of an age of $>$20Myr, and
the loci of the CMD positions for the late-F- and G-type pre-main-sequence BPMG
members have a median isochronal age of 22 Myr ($\pm$ 3 Myr stat., $\pm$ 1 Myr
sys.) when considering four sets of modern theoretical isochrones. The results
from recent LDB and isochronal age analyses are now in agreement with a median
BPMG age of 23 $\pm$ 3 Myr (overall 1{\sigma} uncertainty, including $\pm$2 Myr
statistical and $\pm$2 Myr systematic uncertainties).


  The emerging field of entanglement or nonseparability in classical optics is
reviewed, and its similarities with and differences from quantum entanglement
clearly pointed out through a recapitulation of Hilbert spaces in general, the
special restrictions on Hilbert spaces imposed in quantum mechanics and the
role of Hilbert spaces in classical polarization optics. The production of
Bell-like states in classical polarization optics is discussed, and new
theorems are proved to discriminate between separable and nonseparable states
in classical wave optics where no discreteness is involved. The influence of
the Pancharatnam phase on a classical Bell-like state is deived. Finally, to
what extent classical polarization optics can be used to simulate quantum
information processing tasks is also discussed. This should be of great
practical importance because coherence and entanglement are robust in classical
optics but not in quantum systems.