  In wireless packet-forwarding networks with selfish nodes, application of a
repeated game can induce the nodes to forward each others' packets, so that the
network performance can be improved. However, the nodes on the boundary of such
networks cannot benefit from this strategy, as the other nodes do not depend on
them. This problem is sometimes known as {\em the curse of the boundary nodes}.
To overcome this problem, an approach based on coalition games is proposed, in
which the boundary nodes can use cooperative transmission to help the backbone
nodes in the middle of the network. In return, the backbone nodes are willing
to forward the boundary nodes' packets. Here, the concept of core is used to
study the stability of the coalitions in such games. Then three types of
fairness are investigated, namely, min-max fairness using nucleolus, average
fairness using the Shapley function, and a newly proposed market fairness.
Based on the specific problem addressed in this paper, market fairness is a new
fairness concept involving fairness between multiple backbone nodes and
multiple boundary nodes. Finally, a protocol is designed using both repeated
games and coalition games. Simulation results show how boundary nodes and
backbone nodes form coalitions according to different fairness criteria. The
proposed protocol can improve the network connectivity by about 50%, compared
with pure repeated game schemes.


  An accident is unexpected, unusual, unintended and identifiable external
event which occurs at any place and at any time. The major concern faced by the
government and traffic officials is over speeding at limited speed zones like
hospitals, schools or residential places leading to causalities and more deaths
on the roads. Hence the speed of the vehicles is to be regulated and confined
to the limits as prescribed by the traffic regulations. In this paper we
propose a solution in the form of providing E-speed governor fitted with a
wireless communication system consisting of a Rx which receives the information
regarding the speed regulation for their zones. The TX will be made highly
intelligent and decide when receiver should be made active to regulate the
speed and unwarranted honking from the vehicles which can be deactivated in the
silent zones.


  The norm of Cartan torsion plays an important role for studying of immersion
theory in Finsler geometry. Indeed, Finsler manifold with unbounded Cartan
torsion can not be isometrically imbedded into any Minkowski space. In this
paper, we find two subclasses of (?, ?)-metrics which have bounded Cartan
torsion. Then, we give two subclasses of (?, ?)-metrics whose bound on the
Cartan torsions are independent of the norm of ?.


  We report the first single crystal growth of the correlated metal LaNiO3
using a high-pressure optical-image floating zone furnace. The crystals were
studied using single crystal/powder x-ray diffraction, resistivity, specific
heat, and magnetic susceptibility. The availability of bulk LaNiO3 crystals
will (i) promote deep understanding in this correlated material, including the
mechanism of enhanced paramagnetic susceptibility, and (ii) provide rich
opportunities as a substrate for thin film growth such as important
ferroelectric and/or multiferroic materials. This study demonstrates the power
of high pO2 single crystal growth of nickelate perovskites and correlated
electron oxides more generally.


  We present a spectropolarimetric snapshot survey of solar-type planet hosting
stars. In addition to 14 planet-hosting stars observed as part of the BCool
magnetic snapshot survey, we obtained magnetic observations of a further 19
planet-hosting solar-type stars in order to see if the presence of close-in
planets had an effect on the measured surface magnetic field (|B$_{\ell}$|).
Our results indicate that the magnetic activity of this sample is congruent
with that of the overall BCool sample. The effects of the planetary systems on
the magnetic activity of the parent star, if any, are too subtle to detect
compared to the intrinsic dispersion and correlations with rotation, age and
stellar activity proxies in our sample. Four of the 19 newly observed stars,
two of which are subgiants, have unambiguously detected magnetic fields and are
future targets for Zeeman Doppler Mapping.


  Anomaly Detection is a relevant problem that arises in numerous real-world
applications, especially when dealing with images. However, there has been
little research for this task in the Continual Learning setting. In this work,
we introduce a novel approach called SCALE (SCALing is Enough) to perform
Compressed Replay in a framework for Anomaly Detection in Continual Learning
setting. The proposed technique scales and compresses the original images using
a Super Resolution model which, to the best of our knowledge, is studied for
the first time in the Continual Learning setting. SCALE can achieve a high
level of compression while maintaining a high level of image reconstruction
quality. In conjunction with other Anomaly Detection approaches, it can achieve
optimal results. To validate the proposed approach, we use a real-world dataset
of images with pixel-based anomalies, with the scope to provide a reliable
benchmark for Anomaly Detection in the context of Continual Learning, serving
as a foundation for further advancements in the field.


  We analyze theoretically the effect of friction on quartz crystal
microbalance (QCM) measurements that probe soft (viscoelastic) films and
biomolecular layers adsorbed from aqueous solutions. While water provides a
natural environment for biomolecules, an interface with unknown rheological
properties forms between the adsorbed soft molecular layer and the quartz
substrate in the latter case. We investigate therefore the dynamics of soft
films adsorbed onto a solid quartz surface within a continuum mechanics
approach using both the Maxwell and the Voight/Kelvin models of viscoelasticity
and their combination. The rigorous expressions derived for the acoustic
response of a quartz crystal oscillator, accounting for both interfacial
(sliding) friction and internal friction (viscosity), demonstrate that the QCM
can be used as a sensor for quantitative characteristization of friction
effects as well as for ``in situ'' measurements of mechanical properties of
adsorbed biomolecular films.


  We give an example of a domain in dimension $N \geq 3$, homeomorphic to a
ball and with analytic boundary, for which the second eigenvalue of the
Dirichlet Laplacian has an eigenfunction with a closed nodal surface. The
domain is constructed via a sequence of perturbations of the domain of S.
Fournais [J. Differential Equations \textbf{173} (2001), 145-159].


  In this paper, collaborative use of relays to form a beamforming system with
the aid of perfect channel state information (CSI) and to provide
physical-layer security is investigated. In particular, a
decode-and-forward-based relay beamforming design subject to total and
individual relay power constraints is studied with the goal of maximizing the
secrecy rate. It is shown that the total power constraint leads to a
closed-form solution. The design under individual relay power constraints is
formulated as an optimization problem which is shown to be easily solved using
two different approaches, namely semidefinite programming and second-order cone
programming. Furthermore, a simplified and suboptimal technique which reduces
the computation complexity under individual power constraints is presented.


  Let X be the base locus of a linear system W of k quadrics. Let also S be the
intersection of W with the discriminant hypersurface in the space of all
homogeneous polynomials of degree two. We prove a formula relating the topology
of X with the one of S and its (iterated) singular points. As a corollary we
prove the sharp bound b(X)\leq O(n)^{k-1}.


  A novel photonics-assisted method based on presampling and MDA technique is
proposed for significantly improving the frequency estimation precision without
introducing other complex algorithms. This method is also compatible with
existing FFT-based high-precision estimation algorithms


  In shared spaces, motorized and non-motorized road users share the same space
with equal priority. Their movements are not regulated by traffic rules, hence
they interact more frequently to negotiate priority over the shared space. To
estimate the safeness and efficiency of shared spaces, reproducing the traffic
behavior in such traffic places is important. In this paper, we consider and
combine different levels of interaction between pedestrians and cars in shared
space environments. Our proposed model consists of three layers: a layer to
plan trajectories of road users; a force-based modeling layer to reproduce free
flow movement and simple interactions; and a game-theoretic decision layer to
handle complex situations where road users need to make a decision over
different alternatives. We validate our model by simulating scenarios involving
various interactions between pedestrians and cars and also car-to-car
interaction. The results indicate that simulated behaviors match observed
behaviors well.


  The world's digital transformation has influenced not only the way we do
business, but also the way we perform daily activities. In fact, the past
Presidential elections in the United States as well as those in Great Britain
(Brexit) and in Colombia (peace agreement referendum) are proof that social
media play an important part in modern politics. In fact, this digital
political field is filled by political movements and political candidates
looking for popular support (number of followers), regular citizens' messages
discussing social issues (trending topics flooding social media), or even
political propaganda in favor or against politicians or political movements
(advertisement). One of the issues with social media in this era is the
presence of automatic accounts (bots) that artificially fill accounts with fake
followers, create false trending topics, and share fake news or simply flood
the net with propaganda. All this artificial information may influence people
and sometimes may even censor people's real opinions undermining their freedom
of speech. In this paper, we propose a methodology to track elections and a set
of tools used to collect and analyze election data. In particular, this paper
discusses our experiences during the Presidential Elections in Ecuador held in
2017. In fact, we show how all candidates prepared an online campaign in social
media (Twitter) and how the political campaign altered a common follower rate
subscription. We discuss that the high presence of followers during the period
between the first and second round of elections may be altered by automatic
accounts. Finally, we use bot detection systems and gathered more than 30,000
political motivated bots. In our data analysis, we show that these bots were
mainly used for propaganda purposes in favor or against a particular candidate.


  Uniform dipole magnetic fields from 1.9 to 22.4 kOe were permanently trapped,
with high fidelity to the original field, transversely to the axes of hollow
Nb3Sn superconducting cylinders. These cylinders were constructed by helically
wrapping multiple layers of superconducting ribbon around a mandrel. This is
the highest field yet trapped, the first time trapping has been reported in
such helically wound taped cylinders, and the first time the maximum trappable
field has been experimentally determined as a function of cylinder wall
thickness.


  Computational memory (CM) is a promising approach for accelerating inference
on neural networks (NN) by using enhanced memories that, in addition to storing
data, allow computations on them. One of the main challenges of this approach
is defining a hardware/software interface that allows a compiler to map NN
models for efficient execution on the underlying CM accelerator. This is a
non-trivial task because efficiency dictates that the CM accelerator is
explicitly programmed as a dataflow engine where the execution of the different
NN layers form a pipeline. In this paper, we present our work towards a
software stack for executing ML models on such a multi-core CM accelerator. We
describe an architecture for the hardware and software, and focus on the
problem of implementing the appropriate control logic so that data dependencies
are respected. We propose a solution to the latter that is based on polyhedral
compilation.


  In this paper we propose two different primal-dual splitting algorithms for
solving inclusions involving mixtures of composite and parallel-sum type
monotone operators which rely on an inexact Douglas-Rachford splitting method,
however applied in different underlying Hilbert spaces. Most importantly, the
algorithms allow to process the bounded linear operators and the set-valued
operators occurring in the formulation of the monotone inclusion problem
separately at each iteration, the latter being individually accessed via their
resolvents. The performances of the primal-dual algorithms are emphasized via
some numerical experiments on location and image deblurring problems.


  We study surfaces in Euclidean space constructed by the sum of two curves or
that are graphs of the product of two functions. We consider the problem to
determine all these surfaces with constant Gauss curvature. We extend the
results to non degenerate surfaces in Lorentz-Minkowski space.


  We consider the problem of devising a suitable Quantum Error Correction (QEC)
procedures for a generic quantum noise acting on a quantum circuit. In general,
there is no analytic universal procedure to obtain the encoding and correction
unitary gates, and the problem is even harder if the noise is unknown and has
to be reconstructed. The existing procedures rely on Variational Quantum
Algorithms (VQAs) and are very difficult to train since the size of the
gradient of the cost function decays exponentially with the number of qubits.
We address this problem using a cost function based on the Quantum Wasserstein
distance of order 1 ($QW_1$). At variance with other quantum distances
typically adopted in quantum information processing, $QW_1$ lacks the unitary
invariance property which makes it a suitable tool to avoid to get trapped in
local minima. Focusing on a simple noise model for which an exact QEC solution
is known and can be used as a theoretical benchmark, we run a series of
numerical tests that show how, guiding the VQA search through the $QW_1$, can
indeed significantly increase both the probability of a successful training and
the fidelity of the recovered state, with respect to the results one obtains
when using conventional approaches.


  We report the detection of two exoplanets and a further tentative candidate
around the M-dwarf stars Gl96 and Gl617A, based on radial velocity measurements
obtained with the SOPHIE spectrograph at the Observatoire de Haute-Provence.
Both stars were observed in the context of the SOPHIE exoplanet consortium's
dedicated M-dwarf subprogramme, which aims to detect exoplanets around nearby
M-dwarf stars through a systematic survey. For Gl96, we present the discovery
of a new exoplanet at 73.9 d with a minimum mass of 19.66 earth masses. Gl96 b
has an eccentricity of 0.44, placing it among the most eccentric planets
orbiting M stars. For Gl617A we independently confirm a recently reported
exoplanet at 86.7 d with a minimum mass of 31.29 earth masses. Both Gl96 b and
Gl617A b are potentially within the habitable zone, though Gl96 b's high
eccentricity may take it too close to the star at periapsis.


  We have first succeefully synthesized the sodium cobalt oxyhydrate
superconductors using KMnO4 as a de-intercalating and oxidizing agent. It is a
novel route to form the superconductive phase of NaxCoO2.yH2O without resorting
to the commonly used Br2/CH3CN solution. The role of the KMnO4 is to
de-intercalate the Na+ from the parent compound Na0.7CoO2 and oxidize the Co
ion as a result. The higher molar ratio of KMnO4 relative to the sodium content
tends to remove more Na+ from the parent compound and results in a slight
expansion of the c-axis in the unit cell. The superconducting transition
temperature is 4.6-3.8 K for samples treated by the aqueous KMnO4 solution with
the molar ratio of KMnO4 relative to the sodium content in the range of 0.3 and
2.29.


  The chemically peculiar (CP) stars HD 98851 and HD 102480 have been
discovered to be unusual pulsators during the ``Naini Tal Cape Survey''
programme to search for pulsational variability in CP stars. Time series
photometric and spectroscopic observations of these newly discovered stars are
reported here. Fourier analyses of the time series photometry reveal that HD
98851 is pulsating mainly with frequencies 0.208 mHz and 0.103 mHz, and HD
102480 is pulsating with frequencies 0.107 mHz, 0.156 mHz and 0.198 mHz. The
frequency identifications are all subject to 1 d$^{-1}$ cycle count
ambiguities. We have matched the observed low resolution spectra of HD 98851
and HD 102480 in the range 3500-7400 \AA with theoretical synthetic spectra
using Kurucz models with solar metallicity and a micro-turbulent velocity 2 km
s$^{-1}$. These yield $T_{eff}=7000\pm250$ K, log $g=3.5 \pm 0.5$ for HD 98851
and $T_{eff} = 6750 \pm 250$ K, log $g = 3.0 \pm 0.5$ for HD 102480. We
determined the equivalent H-line spectral class of these stars to be F1 IV and
F3 III/IV, respectively. A comparison of the location of HD 98851 and HD 102480
in the HR diagram with theoretical stellar evolutionary tracks indicates that
both stars are about 1-Gyr-old, 2-$M_{\odot}$ stars that lie towards the red
edge of the $\delta$ Sct instability strip. We conclude that HD 98851 and HD
102480 are cool, evolved Am pulsators. The light curves of these pulsating
stars have alternating high and low amplitudes, nearly harmonic (or
sub-harmonic) period ratios, high pulsational overtones and Am spectral types.
This is unusual for both Am and $\delta$ Sct pulsators, making these stars
interesting objects.


  Intensive concerns about the biosafety of nanomaterials demand the systematic
study of the mechanisms about their biological effects. Many biological effects
can be attributed to the interaction of nanomaterials with protein and their
impacts on protein function. On the other hand, nanomaterials exhibit the
potential in a variety of biomedical applications, many of which also involve
the direct interaction with protein. In this paper, we review some recent
computational studies about this subject, especially the interaction of carbon
and gold nanomaterials. Besides the hydrophobic and {\pi}-stacking
interactions, the interaction mode of carbon nanomaterials can be regulated by
their functional groups. And the coating of gold nanomaterials also adjusts
their interaction mode, in addition to the coordination interaction with
cysteine's sulfur group and histidine's imidazole group. Moreover,
nanomaterials can interact with multiple proteins and the impacts on protein
activity are attributed to a wide spectrum of mechanisms. The findings about
the mechanisms of nanomaterial-protein interaction can further guide the design
and development of nanomaterial to realize the applications in disease
diagnosis and treatment.


  Background independence of noncommutative Yang-Mills theory on $\mathbb R^n$
is discussed. The quantity $\theta \hat F \theta - \theta$ is found to be
background dependent at subleading order, and it becomes background independent
only when the ordinary gauge field strength $F$ is constant. It is shown that,
at small values of $B$, the noncommutative Dirac-Born-Infeld action possesses
$\Lambda$-symmetry at least to subleading order in $\theta$ if $F$ damps fast
enough at infinity.


  This is a paper in smooth $4$-manifold topology, inspired by the Mordell-Weil
Theorem in number theory. More precisely, we prove a smooth version of the
Mordell-Weil Theorem and apply it to the `unipotent radical' case of a
Thurston-type classification of mapping classes of simply-connected
$4$-manifolds $M_d$ that admit the structure of an elliptic complex surface of
arithmetic genus $d\geq 1$. Applications include Nielsen realization theorems
for $M_d$.
  By combining this with known results, we obtain the following remarkable
consequence: if the singular fibers of such an elliptic fibration are of the
simplest (i.e.\ nodal) type, then the fibered structure is unique up
topological isotopy. In particular, any diffeomorphism of $M_d,d\geq 3$ is
topologically isotopic to a diffeomorphism taking fibers to fibers.


  There are good reasons to suspect that spacetime at Planck scales is
noncommutative. Typically this noncommutativity is controlled by fixed
"vectors" or "tensors" with numerical entries. For the Moyal spacetime, it is
the antisymmetric matrix $\theta_{\mu\nu}$. In approaches enforcing Poincar\'e
invariance, these deform or twist the method of (anti-)symmetrization of
identical particle state vectors. We argue that the earth's rotation and
movements in the cosmos are "sudden" events to Pauli-forbidden processes. They
induce (twisted) bosonic components in state vectors of identical spinorial
particles in the presence of a twist. These components induce non-Pauli
transitions. From known limits on such transitions, we infer that the energy
scale for noncommutativity is $\gtrsim 10^{24}\textrm{TeV}$. This suggests a
new energy scale beyond Planck scale.


  We prove that, under a mild summability condition on the growth of the
derivative on critical orbits any piecewise monotone interval map possibly
containing discontinuities and singularities with infinite derivative (cusp
map) admits an ergodic invariant probability measures which is absolutely
continuous with respect to Lebesgue measure.


  Hierarchical Petri nets allow a more abstract view and reconfigurable Petri
nets model dynamic structural adaptation. In this contribution we present the
combination of reconfigurable Petri nets and hierarchical Petri nets yielding
hierarchical structure for reconfigurable Petri nets. Hierarchies are
established by substituting transitions by subnets. These subnets are
themselves reconfigurable, so they are supplied with their own set of rules.
Moreover, global rules that can be applied in all of the net, are provided.


  In this paper we construct all the primitive idempotents of the restricted
quantum group $\overline{U}_q (sl_2)$ and also determine the multiplication
rules among a basis given by the action of generators of $\bar{U}_q (sl_2)$ to
the idempotents. By using this result we construct a basis of the space of
symmetric linear functions of $\overline{U}_q (sl_2)$ and determine the
decomposition of the integral of the dual of $\overline{U}_q (sl_2)$ twisted by
the balancing element to the basis of the space of symmetric linear functions.


  In part I of [1] we have developed the tensor and spin representation of
SO(4) in order to apply it to the simplicial decomposition of the Barrett-Crane
model. We attach to each face of a triangle the spherical function constructed
from the Dolginov-Biedenharn function.
  In part II we apply the same technique to the Lorentz invariant state sum
model. We need three new ingredients: the classification of the edges and the
corresponding subspaces that arises in the simplicial decomposition, the irreps
of SL(2,C) and its isomorphism to the bivectors appearing in the 4-simplices,
the need of a zonal spherical function from the intertwining condition of the
tensor product for the simple representations attached to the faces of the
simplicial decomposition.


  In recent years, many recommender systems have utilized textual data for
topic extraction to enhance interpretability. However, our findings reveal a
noticeable deficiency in the coherence of keywords within topics, resulting in
low explainability of the model. This paper introduces a novel approach called
entropy regularization to address the issue, leading to more interpretable
topics extracted from recommender systems, while ensuring that the performance
of the primary task stays competitively strong. The effectiveness of the
strategy is validated through experiments on a variation of the probabilistic
matrix factorization model that utilizes textual data to extract item
embeddings. The experiment results show a significant improvement in topic
coherence, which is quantified by cosine similarity on word embeddings.


  The potential held by the gargantuan volumes of data being generated across
networks worldwide has been truly unlocked by machine learning techniques and
more recently Deep Learning. The advantages offered by the latter have seen it
rapidly becoming a framework of choice for various applications. However, the
centralization of computational resources and the need for data aggregation
have long been limiting factors in the democratization of Deep Learning
applications. Edge Computing is an emerging paradigm that aims to utilize the
hitherto untapped processing resources available at the network periphery. Edge
Intelligence (EI) has quickly emerged as a powerful alternative to enable
learning using the concepts of Edge Computing. Deep Learning-based Edge
Intelligence or Deep Edge Intelligence (DEI) lies in this rapidly evolving
domain. In this article, we provide an overview of the major constraints in
operationalizing DEI. The major research avenues in DEI have been consolidated
under Federated Learning, Distributed Computation, Compression Schemes and
Conditional Computation. We also present some of the prevalent challenges and
highlight prospective research avenues.


  Recently, the higher-order topological phases from the chiral AIII symmetry
classes are characterized by a Z topological invariant known as the multipole
chiral numbers, which indicate the number of degenerate zero-energy corner
states at each corner. Here, we report the first experimental realization of
higher-order topological insulators protected by multipole chiral numbers with
using acoustic crystals. Our acoustic measurements demonstrate unambiguously
the emergence of multiple corner states in the middle of the gap, as predicted
by the quantized multipole chiral numbers. Our study may provoke new
possibilities for controlling sound, such as acoustic sensing and energy
trapping.


  Image representation is a fundamental task in computer vision. However, most
of the existing approaches for image representation ignore the relations
between images and consider each input image independently. Intuitively,
relations between images can help to understand the images and maintain model
consistency over related images, leading to better explainability. In this
paper, we consider modeling the image-level relations to generate more
informative image representations, and propose ImageGCN, an end-to-end graph
convolutional network framework for inductive multi-relational image modeling.
We apply ImageGCN to chest X-ray images where rich relational information is
available for disease identification. Unlike previous image representation
models, ImageGCN learns the representation of an image using both its original
pixel features and its relationship with other images. Besides learning
informative representations for images, ImageGCN can also be used for object
detection in a weakly supervised manner. The experimental results on 3
open-source x-ray datasets, ChestX-ray14, CheXpert and MIMIC-CXR demonstrate
that ImageGCN can outperform respective baselines in both disease
identification and localization tasks and can achieve comparable and often
better results than the state-of-the-art methods.


  In this study, we investigate a novel "dimerized" dielectric metasurface
featuring dual-mode resonances governed by symmetry-protected bound states in
the continuum (BICs). The metasurface design offers advantages such as
insensitivity to incident light polarization and exceptionally high quality
factors exceeding 10$^5$ for low and moderate structural deviations from the
monoatomic array. By introducing mastered perturbations in the metasurface via
the Brillouin zone folding method, without reducing symmetry, we explore the
behavior of symmetry-protected BIC states and their polarization-independent
responses. Through numerical simulations and analysis, we demonstrate the
superiority of Q factors for specific BIC-based resonances, leading to precise
control over interaction behaviors and light engineering in both near and far
fields. Our findings contribute to the understanding of BIC resonance
interactions and offer insights into the design of high-performance sensing
applications and meta-devices with enhanced functionalities.


  Context. High contrast imaging has thoroughly combed through the limited
search space accessible with first-generation ground-based adaptive optics
instruments and the Hubble Space Telescope. Only a few objects were discovered,
and many non-detections reported and statistically interpreted. The field is
now in need of a technological breakthrough.
  Aim. Our aim is to open a new search space with first-generation systems such
as NACO at the Very Large Telescope, by providing ground-breaking inner working
angle (IWA) capabilities in the L' band. The L' band is a sweet spot for high
contrast coronagraphy since the planet-to-star brightness ratio is favorable,
while the Strehl ratio is naturally higher.
  Methods. An annular groove phase mask (AGPM) vector vortex coronagraph
optimized for the L' band, made from diamond subwavelength gratings was
manufactured and qualified in the lab. The AGPM enables high contrast imaging
at very small IWA, potentially being the key to unexplored discovery space.
  Results. Here we present the installation and successful on-sky tests of an
L'-band AGPM coronagraph on NACO. Using angular differential imaging, which is
well suited to the rotational symmetry of the AGPM, we demonstrated a \Delta L'
> 7.5 mag contrast from an IWA ~ 0".09 onwards, during average seeing
conditions, and for total integration times of a few hundred seconds.


  We study a likelihood ratio test for the location of the mode of a
log-concave density. Our test is based on comparison of the log-likelihoods
corresponding to the unconstrained maximum likelihood estimator of a
log-concave density and the constrained maximum likelihood estimator where the
constraint is that the mode of the density is fixed, say at $m$. The
constrained estimation problem is studied in detail in Doss and Wellner [2018].
Here the results of that paper are used to show that, under the null hypothesis
(and strict curvature of $-\log f$ at the mode), the likelihood ratio statistic
is asymptotically pivotal: that is, it converges in distribution to a limiting
distribution which is free of nuisance parameters, thus playing the role of the
$\chi_1^2$ distribution in classical parametric statistical problems. By
inverting this family of tests we obtain new (likelihood ratio based)
confidence intervals for the mode of a log-concave density $f$. These new
intervals do not depend on any smoothing parameters. We study the new
confidence intervals via Monte Carlo methods and illustrate them with two real
data sets. The new intervals seem to have several advantages over existing
procedures. Software implementing the test and confidence intervals is
available in the R package \verb+logcondens.mode+.


  Solar cells based on a light absorbing layer of the organometal halide
perovskite CH$_3$NH$_3$PbI$_3$ have recently reached 15% conversion efficiency,
though how these materials work remains largely unknown. We analyse the
electronic structure and optical properties within the quasiparticle
self-consistent GW approximation. While this compound bears some similarity to
conventional sp semiconductors, it also displays unique features. Quasiparticle
self-consistency is essential for an accurate description of the band
structure: bandgaps are much larger than what is predicted by the local density
approximation (LDA) or GW based on the LDA. Valence band dispersions are
modified in a very unusual manner. In addition, spin orbit coupling strongly
modifies the band structure and gives rise to unconventional dispersion
relations and a Dresselhaus splitting at the band edges. The average hole mass
is small, which accounts for the long diffusion lengths recently observed. The
surface ionisation potential (workfunction) is calculated to be 5.7 eV with
respect to the vacuum level, explaining efficient carrier transfer to TiO$_2$
and Au electrical contacts.


  Dislocations in soft condensed matter systems such as lamellar systems of
polymers, liquid crystals and ternary mixtures of oil, water and surfactant
(amphiphilic systems) are described in the framework of continuum elastic
theory. These systems are the subject of studies of physics, chemistry and
biology. They also find applications in the industry. Here we will discuss in
detail the influence of dislocations on the bulk and surface properties of
these lamellar phases. Especially the latter properties have only been recently
studied in detail. We will present the experimental evidence of the existence
of screw and edge dislocations in the systems and study their static properties
such as: energy, line tension and core structure. Next we will show how does
the surface influence the equilibrium position of dislocations in the system.
We will give the theoretical predictions and present the experimental results
on thin copolymer films, free standing films of liquid crystals and smectic
droplets shapes. The surface is deformed by dislocations. These deformations
are known as edge profiles. Surface deformations induce elastic interactions
between edge dislocations. A new phenonenon discussed in our paper is the
fluctuations induced interactions between edge dislocations.At suitable
conditions edge dislocations can undergo an unbinding transition. Also a single
dislocation loop in a smectic freely suspended film can undergo an unbinding
transition. We shall also compute the equilibrium size of the loop contained
between two hard walls. Finally we will discuss the dynamical bulk properties
of dislocations such as: mobility (climb and glide),permeation, and helical
instability of screw dislocations. Lubrication theory will also be discussed.


  The $^1 S_0$ pairing of symmetric nuclear matter is discussed in the frame
work of relativistic nuclear theory with Dyson-Schwinger equations (DSEs). The
in-medium nucleon and meson propagators are treated in a more self-consistent
way through meson polarizations. The screening effects on mesons due to
in-medium nucleon excitation are found to reduce the $^1S_0$ pairing gap and
shift remarkably the gap peak to low density region.


  We report on early stages of submonolayer Ag island coarsening on Ag(111)
surface at room temperature ($300$ K) carried out using realistic kinetic Monte
Carlo (KMC) simulations. We find that during early stages, coarsening proceeds
as a sequence of selected island sizes creating peaks and valleys in the island
size distribution. We find that island-size selectivity is due to formation of
kinetically stable islands for certain sizes because of adatom
detachment/attachment processes and large activation barrier for kink
detachment.
  In addition, we find that the ratio of number of adatom attachment to
detachment processes to be independent of parameters of initial configuration
and also on the initial shapes of the islands confirming that island-size
selectivity is independent of initial conditions.These simulations were carried
out using a very large database of processes identified by their local
environment and whose activation barriers were calculated using the
embedded-atom method.


  Cappell's unitary nilpotent groups UNil(R;R,R) are calculated for the
integral group ring R=Z[C_2] of the cyclic group C_2 of order two.
Specifically, they are determined as modules over the Verschiebung algebra V
using the Connolly--Ranicki isomorphism and the Connolly--Davis relations.


  We show that the only transitive and generically $4$-transitive action of a
group of finite Morley rank on a set of Morley rank $2$ is the natural action
of $\operatorname{PGL}_3$ on the projective plane.


  We evaluate the sensitivity of a dual cloud atom interferometer to the
measurement of vertical gravity gradient. We study the influence of most
relevant experimental parameters on noise and long-term drifts. Results are
also applied to the case of doubly differential measurements of the
gravitational signal from local source masses. We achieve a short term
sensitivity of 3*10^(-9) g/Hz^(-1/2) to differential gravity acceleration,
limited by the quantum projection noise of the instrument. Active control of
the most critical parameters allows to reach a resolution of 5*10^(-11) g after
8000 s on the measurement of differential gravity acceleration. The long term
stability is compatible with a measurement of the gravitational constant G at
the level of 10^(-4) after an integration time of about 100 hours.


  In this paper, we propose a multiscale method for the Darcy-Forchheimer model
in highly heterogeneous porous media. The problem is solved in the framework of
generalized multiscale finite element methods (GMsFEM) combined with a
multipoint flux mixed finite element (MFMFE) method. %In the MFMFE methods,
appropriate mixed finite element spaces and suitable quadrature rules are
employed, which allow for local velocity elimination and lead to a
cell-centered system for the pressure. We consider the MFMFE method that
utilizes the lowest order Brezzi-Douglas-Marini ($\textrm{BDM}_1$) mixed finite
element spaces for the velocity and pressure approximation. The symmetric
trapezoidal quadrature rule is employed for the integration of bilinear forms
relating to the velocity variables so that the local velocity elimination is
allowed and leads to a cell-centered system for the pressure. %on meshes
composed of simplices and $h^2$-perturbed parallelograms. We construct
multiscale space for the pressure and solve the problem on the coarse grid
following the GMsFEM framework. In the offline stage, we construct local
snapshot spaces and perform spectral decompositions to get the offline space
with a smaller dimension. In the online stage, we use the Newton iterative
algorithm to solve the nonlinear problem and obtain the offline solution, which
reduces the iteration times greatly comparing to the standard Picard iteration.
Based on the offline space and offline solution, we calculate online basis
functions which contain important global information to enrich the multiscale
space iteratively. The online basis functions are efficient and accurate to
reduce relative errors substantially. Numerical examples are provided to
highlight the performance of the proposed multiscale method.


  A consistent notation for the Weierstrass elliptic function
$\wp(z;g_{2},g_{3})$, for $g_{2} > 0$ and arbitrary values of $g_{3}$ and
$\Delta \equiv g_{2}^{3} - 27 g_{3}^{2}$, is introduced based on the parametric
solution for the motion of a particle in a cubic potential. These notes provide
a roadmap for the use of {\sf Mathematica} to calculate the half-periods
$(\omega_{1},\omega_{3},\omega_{2} \equiv \omega_{1} + \omega_{3})$ of the
Weierstrass elliptic function.


  We present simulation results for the dynamics of a schematic model based on
the frustration-limited domain picture of glass-forming liquids. These results
are compared with approximate theoretical predictions analogous to those
commonly used for supercooled liquid dynamics. Although model relaxation times
increase by several orders of magnitude in a non-Arrhenius manner as a
microphase separation transition is approached, the slow relaxation is in many
ways dissimilar to that of a liquid. In particular, structural relaxation is
nearly exponential in time at each wave vector, indicating that the mode
coupling effects dominating liquid relaxation are comparatively weak within
this model. Relaxation properties of the model are instead well reproduced by
the simplest dynamical extension of a static Hartree approximation. This
approach is qualitatively accurate even for temperatures at which the mode
coupling approximation predicts loss of ergodicity. These results suggest that
the thermodynamically disordered phase of such a minimal model poorly
caricatures the slow dynamics of a liquid near its glass transition.


  In this paper, we first introduce a lower bound technique for the state
complexity of transformations of automata. Namely we suggest first considering
the class of full automata in lower bound analysis, and later reducing the size
of the large alphabet via alphabet substitutions. Then we apply such technique
to the complementation of nondeterministic \omega-automata, and obtain several
lower bound results. Particularly, we prove an \omega((0.76n)^n) lower bound
for B\"uchi complementation, which also holds for almost every complementation
or determinization transformation of nondeterministic omega-automata, and prove
an optimal (\omega(nk))^n lower bound for the complementation of generalized
B\"uchi automata, which holds for Streett automata as well.


  Few-shot learning (FSL) aims to develop a learning model with the ability to
generalize to new classes using a few support samples. For transductive FSL
tasks, prototype learning and label propagation methods are commonly employed.
Prototype methods generally first learn the representative prototypes from the
support set and then determine the labels of queries based on the metric
between query samples and prototypes. Label propagation methods try to
propagate the labels of support samples on the constructed graph encoding the
relationships between both support and query samples. This paper aims to
integrate these two principles together and develop an efficient and robust
transductive FSL approach, termed Prototype-based Soft-label Propagation
(PSLP). Specifically, we first estimate the soft-label presentation for each
query sample by leveraging prototypes. Then, we conduct soft-label propagation
on our learned query-support graph. Both steps are conducted progressively to
boost their respective performance. Moreover, to learn effective prototypes for
soft-label estimation as well as the desirable query-support graph for
soft-label propagation, we design a new joint message passing scheme to learn
sample presentation and relational graph jointly. Our PSLP method is
parameter-free and can be implemented very efficiently. On four popular
datasets, our method achieves competitive results on both balanced and
imbalanced settings compared to the state-of-the-art methods. The code will be
released upon acceptance.


  The so-called semi-relativistic expansion of the weak charged current in
powers of the initial nucleon momentum is performed to describe
charge-changing, quasielastic neutrino reactions $(\nu_\mu,\mu^-)$ at
intermediate energies. The quality of the expansion is tested by comparing with
the relativistic Fermi gas model using several choices of kinematics of
interest for ongoing neutrino oscillation experiments. The new current is then
implemented in a continuum shell model together with relativistic kinematics to
investigate the scaling properties of $(e,e')$ and $(\nu_\mu,\mu^-)$ cross
sections.


  In this article, we study optimal control of dynamics in a linear chain of
three spin 1/2, weakly coupled with unequal Ising couplings. We address the
problem of time-optimal synthesis of multiple spin quantum coherences. We
derive time-optimal pulse sequence for creating a desired spin order by
computing geodesics on a sphere under a special metric. The solution to the
geodesic equation is related to the nonlinear oscillator equation and the
minimum time to create multiple spin order can be expressed in terms of an
elliptic integral. These techniques are used for efficient creation of multiple
spin coherences in Ising spin-chains with unequal couplings.


  Registration of point clouds collected from a pair of distant vehicles
provides a comprehensive and accurate 3D view of the driving scenario, which is
vital for driving safety related applications, yet existing literature suffers
from the expensive pose label acquisition and the deficiency to generalize to
new data distributions. In this paper, we propose EYOC, an unsupervised distant
point cloud registration method that adapts to new point cloud distributions on
the fly, requiring no global pose labels. The core idea of EYOC is to train a
feature extractor in a progressive fashion, where in each round, the feature
extractor, trained with near point cloud pairs, can label slightly farther
point cloud pairs, enabling self-supervision on such far point cloud pairs.
This process continues until the derived extractor can be used to register
distant point clouds. Particularly, to enable high-fidelity correspondence
label generation, we devise an effective spatial filtering scheme to select the
most representative correspondences to register a point cloud pair, and then
utilize the aligned point clouds to discover more correct correspondences.
Experiments show that EYOC can achieve comparable performance with
state-of-the-art supervised methods at a lower training cost. Moreover, it
outwits supervised methods regarding generalization performance on new data
distributions.


  For $1<p\leqslant \infty$, we study the complexity and the existence of
universal spaces for two classes of separable Banach spaces, denoted
$\textsf{A}_p$ and $\textsf{N}_p$, and related to asymptotic smoothness in
Banach spaces. We show that each of these classes is Borel in the class of
separable Banach spaces. Then we build small families of Banach spaces that are
both injectively and surjectively universal for these classes. Finally, we
prove the optimality of this universality result, by proving in particular that
none of these classes admits a universal space.


  In this short note we shall demonstrate that given a smooth solution $\gamma$
to the linearised Einstein equations on Schwarzschild which is supported on the
$l\geq 2$ spherical harmonics and expressed relative to a transverse and
traceless gauge then one can construct from it a smooth solution to the sourced
Maxwell equations expressed relative to a generalised Lorentz gauge. Here the
Maxwell current is constructed from those gauge-invariant combinations of the
components of $\gamma$ which are determined by solutions to the Regge--Wheeler
and Zerilli equations. The result thus provides an elegant link between the
spin 1 and spin 2 equations on Schwarzschild.


  We present several results relating to the contraction of generic tensor
networks and discuss their application to the simulation of quantum many-body
systems using variational approaches based upon tensor network states. Given a
closed tensor network $\mathcal{T}$, we prove that if the environment of a
single tensor from the network can be evaluated with computational cost
$\kappa$, then the environment of any other tensor from $\mathcal{T}$ can be
evaluated with identical cost $\kappa$. Moreover, we describe how the set of
all single tensor environments from $\mathcal{T}$ can be simultaneously
evaluated with fixed cost $3\kappa$. The usefulness of these results, which are
applicable to a variety of tensor network methods, is demonstrated for the
optimization of a Multi-scale Entanglement Renormalization Ansatz (MERA) for
the ground state of a 1D quantum system, where they are shown to substantially
reduce the computation time.


  We investigate the low-energy dynamics of $SU(N)$ gauge theories with one
antisymmetric tensor field, $N - 4 + N_f$ antifundamentals and $N_f$
fundamentals, for $N_f \le 3$. For $N_f = 3$ we construct the quantum moduli
space, and for $N_f < 3$ we find the exact quantum superpotentials. We find two
large classes of models with dynamical supersymmetry breaking. The odd $N$
theories break supersymmetry once appropriate mass terms are added in the
superpotential.
  The even $N$ theories break supersymmetry after gauging an extra chiral
$U(1)$ symmetry.


  With one exception, our previous work on recurrence extraction and
denotational semantics has focused on a source language that supports inductive
types and structural recursion. The exception handles general recursion via an
initial translation into call-by-push-value. In this note we give an extraction
function from a language with general recursive function definitions and
recursive types directly to a PCF-like recurrence language. We prove the main
soundness result (that the syntactic recurrences in fact bound the operational
cost) without the use of a logical relation, thereby significantly simplifying
the proof compared to our previous work (at the cost of placing more demands on
the models of the recurrence language). We then define two models of the
recurrence language, one for analyzing merge sort, and another for analyzing
quick sort, as case studies to understand model definitions for justifying the
extracted recurrences.


  By using isochronous mass spectrometry (IMS) at the experimental cooler
storage ring CSRe, masses of short-lived $^{44}$Cr, $^{46}$Mn, $^{48}$Fe,
$^{50}$Co and $^{52}$Ni were measured for the first time and the precision of
the mass of $^{40}$Ti was improved by a factor of about 2. Relative precisions
of $\delta m/m=(1-2)\times$10$^{-6}$ have been achieved. Details of the
measurements and data analysis are described. The obtained masses are compared
with the Atomic-Mass Evaluation 2016 (AME$^{\prime}$16) and with theoretical
model predictions. The new mass data enable us to extract the higher order
coefficients, $d$ and $e$, of the quartic form of the isobaric multiplet mass
equation (IMME) for the $fp$-shell isospin quintets. Unexpectedly large $d$-
and $e$-values for $A=44$ quintet are found. By re-visiting the previous
experimental data on $\beta$-delayed protons from $^{44}$Cr decay, it is
suggested that the observed anomaly could be due to the misidentification of
the $T=2$, $J^\pi=0^{+}$ isobaric analog state (IAS) in $^{44}$V.


  We study a class of SU(N) Heisenberg models, describing Mott insulators of
fermionic ultra-cold alkaline earth atoms on the three-dimensional simple cubic
lattice. Based on an earlier semiclassical analysis, magnetic order is
unlikely, and we focus instead on a solvable large-N limit designed to address
the competition among non-magnetic ground states. We find a rich phase diagram
as a function of the filling parameter k, composed of a variety of ground
states spontaneously breaking lattice symmetries, and in some cases also time
reversal symmetry. One particularly striking example is a state spontaneously
breaking lattice rotation symmetry, where the cubic lattice breaks up into
bilayers, each of which forms a two-dimensional chiral spin liquid state.


  In this note we re-examine the classic Janssen theory for stresses in bins,
including a randomness in the friction coefficient. The Janssen analysis relies
on assumptions not met in practice; for this reason, we numerically solve the
PDEs expressing balance of momentum in a bin, again including randomness in
friction.


  With the growing constraints on power budget and increasing hardware failure
rates, the operation of future exascale systems faces several challenges.
Towards this, resource awareness and adaptivity by enabling malleable jobs has
been actively researched in the HPC community. Malleable jobs can change their
computing resources at runtime and can significantly improve HPC system
performance. However, due to the rigid nature of popular parallel programming
paradigms such as MPI and lack of support for dynamic resource management in
batch systems, malleable jobs have been largely unrealized. In this paper, we
extend the SLURM batch system to support the execution and batch scheduling of
malleable jobs. The malleable applications are written using a new adaptive
parallel paradigm called Invasive MPI which extends the MPI standard to support
resource-adaptivity at runtime. We propose two malleable job scheduling
strategies to support performance-aware and power-aware dynamic reconfiguration
decisions at runtime. We implement the strategies in SLURM and evaluate them on
a production HPC system. Results for our performance-aware scheduling strategy
show improvements in makespan, average system utilization, average response,
and waiting times as compared to other scheduling strategies. Moreover, we
demonstrate dynamic power corridor management using our power-aware strategy.


  It is known that a species dies out in the long run for small initial data if
its evolution obeys a reaction of bistable nonlinearity. Such a phenomenon,
which is termed as the strong Allee effect, is well supported by numerous
evidence from ecosystems, mainly due to the environmental pollution as well as
unregulated harvesting and hunting. To save an endangered species, in this
paper we introduce a protection zone that is governed by a Fisher-KPP
nonlinearity, and examine the dynamics of a reaction-diffusion model with
strong Allee effect and protection zone. We show the existence of two critical
values $0<L_*\leq L^*$, and prove that a vanishing-transition-spreading
trichotomy result holds when the length of protection zone is smaller than
$L_*$; a transition-spreading dichotomy result holds when the length of
protection zone is between $L_*$ and $L^*$; only spreading happens when the
length of protection zone is larger than $L^*$. This suggests that the
protection zone works when its length is larger than the critical value $L_*$.
Furthermore, we compare two types of protection zone with the same length: a
connected one and a separate one, and our results reveal that the former is
better for species spreading than the latter.


  Collective modes manifest themselves in a variety of different physical
systems ranging from superconductors to superfluid $^{3}$He. The collective
modes are generated via the Higgs-Anderson mechanism that is based on the
symmetry breaking double well potential. Recently collective modes were
explored in superconducting NbN and InO in the presence of a strong terahertz
laser field. In both cases a single collective mode that oscillates with twice
the frequency of the superconducting energy gap $\Delta$ was discovered.
Superfluid $^{3}$He is the host for a whole variety of collective modes. In
particular, in the superfluid $^{3}$He B-phase, two massive collective modes
were found with masses $\sqrt{{8}/{5}}\Delta$ and $\sqrt{{12}/{5}}\Delta$. We
show that for both cases of the superconducting films and for the superfluid
$^{3}$He B-phase, the collective modes satisfy the Nambu identity that relates
the masses of different collective modes to the energy gap parameter $\Delta$.


  Solving large-scale capacity expansion problems (CEPs) is central to
cost-effective decarbonization of regional-scale energy systems. To ensure the
intended outcomes of CEPs, modeling uncertainty due to weather-dependent
variable renewable energy (VRE) supply and energy demand becomes crucially
important. However, the resulting stochastic optimization models are often less
computationally tractable than their deterministic counterparts. Here, we
propose a learning-assisted approximate solution method to tractably solve
two-stage stochastic CEPs. Our method identifies low-cost planning decisions by
constructing and solving a sequence of tractable temporally aggregated
surrogate problems. We adopt a Bayesian optimization approach to searching the
space of time series aggregation hyperparameters and compute approximate
solutions that minimize costs on a validation set of supply-demand projections.
Importantly, we evaluate solved planning outcomes on a held-out set of test
projections. We apply our approach to generation and transmission expansion
planning for a joint power-gas system spanning New England. We show that our
approach yields an estimated cost savings of up to 3.8% in comparison to
benchmark time series aggregation approaches.


  In this paper, we prove a uniform version of Poonen's "Mordell-Lang Plus
Bogomolov" theorem for abelian varieties. We mainly generalize R\'emond's work
on large points to allow an extra $\epsilon$-neighborhood. The part on small
points follows from an earlier paper, joint with Gao and K\"uhne.


  We propose a nanowaveguide platform for collective atom-light interaction
through evanescent field coupling. We have developed a 1cm-long silicon nitride
nanowaveguide can use evanescent fields to trap and probe an ensemble of 87Rb
atoms. The waveguide has a sub-micrometer square mode area and was designed
with tapers for high fiber-to-waveguide coupling efficiencies at near-infrared
wavelengths (750nm to 1100nm). Inverse tapers in the platform adiabatically
transfer a weakly guided mode of fiber-coupled light into a strongly guided
mode with an evanescent field to trap atoms and then back to a weakly guided
mode at the other end of the waveguide. The coupling loss is -1dB per facet
(~80% coupling efficiency) at 760nm and 1064nm, which is estimated by a
propagation loss measurement with waveguides of different lengths. The proposed
platform has good thermal conductance and can guide high optical powers for
trapping atoms in ultra-high vacuum. As an intermediate step, we have observed
thermal atom absorption of the evanescent component of a nanowaveguide, and
have demonstrated the U-wire mirror magneto-optical trap that can transfer
atoms to the proximity of the surface.


  The cosmic microwave background provides constraints on the annihilation and
decay of light dark matter at redshifts between 100 and 1000, the strength of
which depends upon the fraction of energy ending up in the form of electrons
and photons. The resulting constraints are usually presented for a limited
selection of annihilation and decay channels. Here we provide constraints on
the annihilation cross section and decay rate, at discrete values of the dark
matter mass, for all the annihilation and decay channels whose secondary
spectra have been computed using PYTHIA in arXiv:1012.4515 ("PPPC4DMID: A Poor
Particle Physicist Cookbook for Dark Matter Indirect Detection"), namely e, mu,
tau, V -> e, V -> mu, V -> tau, u, d, s, c, b, t, gamma, g, W, Z and h. By
interpolating in mass, these can be used to find the CMB constraints and
likelihood functions from WMAP7 and Planck for a wide range of dark matter
models, including those with annihilation or decay into a linear combination of
different channels.


  Accreting stellar-mass black holes often show a `Type-C' quasi-periodic
oscillation (QPO) in their X-ray flux, and an iron emission line in their X-ray
spectrum. The iron line is generated through continuum photons reflecting off
the accretion disk, and its shape is distorted by relativistic motion of the
orbiting plasma and the gravitational pull of the black hole. The physical
origin of the QPO has long been debated, but is often attributed to
Lense-Thirring precession, a General Relativistic effect causing the inner flow
to precess as the spinning black hole twists up the surrounding space-time.
This predicts a characteristic rocking of the iron line between red and blue
shift as the receding and approaching sides of the disk are respectively
illuminated. Here we report on XMM-Newton and NuSTAR observations of the black
hole binary H 1743-322 in which the line energy varies systematically over the
~4 s QPO cycle (3.70 sigma significance), as predicted. This provides strong
evidence that the QPO is produced by Lense-Thirring precession, constituting
the first detection of this effect in the strong gravitation regime. There are
however elements of our results harder to explain, with one section of data
behaving differently to all the others. Our result enables the future
application of tomographic techniques to map the inner regions of black hole
accretion disks.


  We revisit the interpretation of the cylindrically symmetric, static vacuum
Levi-Civita metric, known in either Weyl, Einstein-Rosen, or Kasner-like
coordinates. Despite the infinite axis source, we derive its Komar mass density
through a compactification and subsequent blowing up of the compactification
radius. We show that, the Komar mass density $\mu_K$ calculated in the
Einstein-Rosen frame, when employed as the metric parameter, has a number of
advantages. It eliminates double coverages of the parameter space, vanishes in
flat spacetime and when small, it corresponds to the mass density of an
infinite string. After a comprehensive analysis of the local and global
geometry, we proceed with the physical interpretation of the Levi-Civita
spacetime. First we show that the Newtonian gravitational force is attractive
and its magnitude increases monotonically with all positive ${\mu}_K$,
asymptoting to the inverse of the the proper distance in the "radial"
direction. Second, we reveal that the tidal force between nearby geodesics
(hence gravity in the Einsteinian sense) attains a maximum at $\mu_K=1/2$ and
then decreases asymptotically to zero. Hence, from a physical point of view the
Komar mass density of the Levi-Civita spacetime encompasses two contributions:
Newtonian gravity and acceleration effects. An increase in $\mu_K$ strengthens
Newtonian gravity but also drags the field lines increasingly parallel,
eventually transforming Newtonian gravity through the equivalence principle
into a pure acceleration field and the Levi-Civita spacetime into a flat
Rindler-like spacetime. In a geometric picture the increase of $\mu_K$ from
zero to $\infty$ deforms the planar sections of the spacetime into ever
deepening funnels, eventually degenerating into cylindrical topology.


  We investigate predictions on the triple Higgs boson couplings with radiative
corrections in the model with an additional real singlet scalar field. In this
model, the second physical scalar state ($H$) appears in addition to the Higgs
boson ($h$) with the mass 125 GeV. The $hhh$ vertex is calculated at the
one-loop level, and its possible deviation from the predictions in the standard
model is evaluated under various theoretical constraints. The decay rate of $H
\to hh$ is also computed at the one-loop level. We also take into account the
bound from the precise measurement of the $W$ boson mass, which gives the upper
limit on the mixing angle $\alpha$ between two physical Higgs bosons for a
given value of the mass of $H$ ($m_H^{}$). We find that the deviation in the
$hhh$ coupling from the prediction in the standard model can maximally be about
250\%, 150\% and 75\% for $m_H^{}=300$, 500 and 1000 GeV, respectively, under
the requirement that the cutoff scale of the model is higher than 3 TeV. We
also discuss deviations from the standard model prediction in double Higgs
boson production from the gluon fusion at the LHC using the one-loop corrected
Higgs boson vertices.


  ASTRO-H, the sixth Japanese X-ray observatory, which is scheduled to be
launched by the end of Japanese fiscal year 2015 has a capability to observe
the prompt emission from Gamma-ray Bursts (GRBs) utilizing BGO active shields
for the soft gamma-ray detector (SGD). The effective area of the SGD shield
detectors is very large and its data acquisition system is optimized for short
transients such as short GRBs. Thus, we expect to perform more detailed
time-resolved spectral analysis with a combination of ASTRO-H and Fermi LAT/GBM
to investigate the gamma-ray emission mechanism of short GRBs. In addition, the
environment of the GRB progenitor should be a remarkable objective from the
point of view of the chemical evolution of high-z universe. If we can maneuver
the spacecraft to the GRBs, we can perform a high-resolution spectroscopy of
the X-ray afterglow of GRBs utilizing the onboard micro calorimeter and X-ray
CCD camera.


  Federated Learning (FL) is an interesting strategy that enables the
collaborative training of an AI model among different data owners without
revealing their private datasets. Even so, FL has some privacy vulnerabilities
that have been tried to be overcome by applying some techniques like
Differential Privacy (DP), Homomorphic Encryption (HE), or Secure Multi-Party
Computation (SMPC). However, these techniques have some important drawbacks
that might narrow their range of application: problems to work with non-linear
functions and to operate large matrix multiplications and high communication
and computational costs to manage semi-honest nodes. In this context, we
propose a solution to guarantee privacy in FL schemes that simultaneously
solves the previously mentioned problems. Our proposal is based on the Berrut
Approximated Coded Computing, a technique from the Coded Distributed Computing
paradigm, adapted to a Secret Sharing configuration, to provide input privacy
to FL in a scalable way. It can be applied for computing non-linear functions
and treats the special case of distributed matrix multiplication, a key
primitive at the core of many automated learning tasks. Because of these
characteristics, it could be applied in a wide range of FL scenarios, since it
is independent of the machine learning models or aggregation algorithms used in
the FL scheme. We provide analysis of the achieve privacy and complexity of our
solution and, due to the extensive numerical results performed, it can be
observed a good trade-off between privacy and precision.


  Using Galois Theory, we construct explicitly absolutely simple (principally
polarized) Prym varieties that are not isomorphic to jacobians of curves even
if we ignore the polarizations. Our approach is based on the previous papers
math/0610138 [math.AG] and math/0605028 [math.AG] .


  We have adopted the multistep shell model in the complex energy plane to
study nuclear excitations occurring in the continuum part of the spectrum. In
this method one proceeds by solving the shell model equations in a successive
manner. That is, in each step one constructs the building blocks to be used in
future steps. We applied this formalism to analyze the unbound nuclei
$^{12,13}$Li starting from the one-particle states in $^{10}$Li and
two-particle states in $^{11}$Li. In the former case the excitations correspond
to the motion of three particles partitioned as the product of a one-particle
and two-particle systems. The ground state of $^{12}$Li is thus calculated to
be an antibound (virtual) state. In the four-particle system $^{13}$Li the
states can be constructed as the coupling of two correlated pairs. We found
that there is no bound or antibound state in $^{13}$Li.


  This paper studies a novel cooperation method in a two-user wireless powered
communication network (WPCN), in which one hybrid access point (HAP) broadcasts
wireless energy to two distributed wireless devices (WDs), while the WDs use
the harvested energy to transmit their independent information to the HAP. To
tackle the user unfairness problem caused by the near-far effect in WPCN, we
allow the WD with the stronger WD-to-HAP channel to use part of its harvested
energy to help relay the other weaker user's information to the HAP. In
particular, we exploit the use of backscatter communication during the wireless
energy transfer phase such that the helping relay user can harvest energy and
receive the information from the weaker user simultaneously. We derive the
maximum common throughput performance by jointly optimizing the time duration
and power allocations on wireless energy and information transmissions. Our
simulation results demonstrate that the backscatter-assisted cooperation scheme
can effectively improve the throughput fairness performance in WPCNs.


  In this letter, we explore electron filtering as a technique to increase
Seebeck coefficient and the thermoelectric power factor of heterostructured
materials over that of the bulk. We present a theoretical model in which
Seebeck coefficient and the power factor can be increased in an InGaAs based
composite material. Experimental measurements of the cross-plane Seebeck
coefficient are presented and confirm the importance of the electron filtering
technique to decouple the electrical conductivity and Seebeck coefficient to
increase the thermoelectric power factor.


  We have published several articles about generalizations and boundary-case
exceptions to the Second Incompleteness Theorem during the last 25 years. The
current paper will review some of our prior results and also introduce an
`enriched' refinement of semantic tableaux deduction. While the Second
Incompleteness Theorem is a strong result, we will emphasize its boundary-case
exceptions are germane to Global Warming's threat because our systems can own a
simultaneous knowledge about their own consistency, together with an
understanding of the $\Pi_1$ implications of Peano Arithmetic.


  We employ a trapped ion to study quantum contextual correlations in a single
qutrit using the 5-observable KCBS inequality, which is arguably the most
fundamental non-contextuality inequality for testing Quantum Mechanics (QM). We
quantify the effect of systematics in our experiment by purposely scanning the
degree of signaling between measurements, which allows us to place realistic
bounds on the non-classicality of the observed correlations. Our results
violate the classical bound for this experiment by up to 25 standard
deviations, while being in agreement with the QM limit. In order to test the
prediction of QM that the contextual fraction increases with the number of
observables, we gradually increase the complexity of our measurements from 5 up
to 121 observables. We find stronger-than-classical correlations in all
prepared scenarios up to 101 observables, beyond which experimental
imperfections blur the quantum-classical divide.


  In this paper, a general theorem on the equivalence of pth moment stability
between stochastic differential delay equations (SDDEs) and their numerical
methods is proved under the assumptions that the numerical methods are strongly
convergent and have the bouneded $p$th moment in the finite time. The truncated
Euler-Maruyama (EM) method is studied as an example to illustrate that the
theorem indeed covers a large ranges of SDDEs. Alongside the investigation of
the truncated EM method, the requirements on the step size of the method are
significantly released compared with the work, where the method was initially
proposed.


  Given two semigroups $\langle A\rangle$ and $\langle B\rangle$ in ${\mathbb
N}^n$, we wonder when they can be glued, i.e., when there exists a semigroup
$\langle C\rangle$ in ${\mathbb N}^n$ such that the defining ideals of the
corresponding semigroup rings satisfy that $I_C=I_A+I_B+\langle\rho\rangle$ for
some binomial $\rho$. If $n\geq 2$ and $k[A]$ and $k[B]$ are Cohen-Macaulay, we
prove that in order to glue them, one of the two semigroups must be degenerate.
Then we study the two most degenerate cases: when one of the semigroups is
generated by one single element (simple split) and the case where it is
generated by at least two elements and all the elements of the semigroup lie on
a line. In both cases we characterize the semigroups that can be glued and say
how to glue them. Further, in these cases, we conclude that the glued $\langle
C\rangle$ is Cohen-Macaulay if and only if both $\langle A\rangle$ and $\langle
B\rangle$ are also Cohen-Macaulay. As an application, we characterize precisely
the Cohen-Macaulay semigroups that can be glued when $n=2$.


  We provide an asymptotic linear representation for the Breslow estimator of
the baseline cumulative hazard function in the Cox model. Our representation
consists of an average of independent random variables and a term involving the
difference between the maximum partial likelihood estimator and the underlying
regression parameter. The order of the remainder term is arbitrarily close to
1/n.


  Most reinforcement learning algorithms are inefficient for learning multiple
tasks in complex robotic systems, where different tasks share a set of actions.
In such environments a compound policy may be learnt with shared neural network
parameters, which performs multiple tasks concurrently. However such compound
policy may get biased towards a task or the gradients from different tasks
negate each other, making the learning unstable and sometimes less data
efficient. In this paper, we propose a new approach for simultaneous training
of multiple tasks sharing a set of common actions in continuous action spaces,
which we call as DiGrad (Differential Policy Gradient). The proposed framework
is based on differential policy gradients and can accommodate multi-task
learning in a single actor-critic network. We also propose a simple heuristic
in the differential policy gradient update to further improve the learning. The
proposed architecture was tested on 8 link planar manipulator and 27 degrees of
freedom(DoF) Humanoid for learning multi-goal reachability tasks for 3 and 2
end effectors respectively. We show that our approach supports efficient
multi-task learning in complex robotic systems, outperforming related methods
in continuous action spaces.


  Numerical simulations predict that some poor groups of galaxies have merged
by the present epoch into giant ellipticals (cf. Barnes 1989). To identify the
possible remnants of such mergers, we have compiled a sample of nearby,
isolated ellipticals (Colbert, Mulchaey, & Zabludoff 1998). ASCA observations
of the first galaxy studied, NGC 1132 reveal an X-ray halo that extends out to
at least 250 kpc. The temperature, metallicity and luminosity of NGC 1132's
X-ray halo are comparable to those of poor group halos. The total mass inferred
from the X-ray emission is also like that of an X-ray detected group. Optical
imaging uncovers a dwarf galaxy population clustered about NGC 1132 that is
consistent in number density and in projected radial distribution with that of
an X-ray group. The similarities of NGC 1132 to poor groups in both the X-ray
band and at the faint end of the galaxy luminosity function, combined with the
deficit of luminous galaxies in the NGC 1132 field, are compatible with the
merged group picture. Another possibility is that the NGC 1132 system is a
`failed' group (i.e., a local overdensity in which other bright galaxies never
formed).


  The migration of U and Th inside a planet is controlled by its oxidation
state imposed by the volatile composition. In the deep interior of a planet, an
absence of oxidative volatiles will cause U and Th to stay in a state of metal
or low valance compounds with a big density. Consequently, they migrate to the
bottom of its mantle first, and then are gradually sequestered to its liquid
metal core. Earth is rich in oxidative volatiles including water, therefore, U
and Th in the core can be moved up by an internal circulation system consisting
of the outer core, hot super plumes, asthenosphere and subduction zone (or cold
super plumes). This internal circulation system is the key for the formation of
plate tectonics, the geodynamo and the consequent geomagnetic field. Moreover,
plentiful oxidative volatiles and water within Earth is the precondition to
form such a circulation system. In the early stage (> 4 Ga), Mars developed an
Earth-like internal circulation system due to relatively large amount of
oxidative volatile compositions coming from its building material. This would
have produced a dynamo and correspondingly an Earth-like magnetic field.
However, this internal circulation system was destroyed by one or several giant
impact events in the early stage, which drove off these volatile compositions.
These events also shaped the striking hemispheric dichotomy structure on the
Martian surface. The other result is that its dynamo and geomagnetic field have
also disappeared. Since then, Mars has been the same as Mercury and Venus in
that the heat release from the U and Th in their cores can not be moved by an
internal circulation system gently, but by sporadically catastrophic
resurfacing events (Venus), or super plumes (Mars) or gradual heat conduction
(Mercury).


  Partial edge drawing (PED) is a drawing style for non-planar graphs, in which
edges are drawn only partially as pairs of opposing stubs on the respective
end-vertices. In a PED, by erasing the central parts of edges, all edge
crossings and the resulting visual clutter are hidden in the undrawn parts of
the edges. In symmetric partial edge drawings (SPEDs), the two stubs of each
edge are required to have the same length. It is known that maximizing the ink
(or the total stub length) when transforming a straight-line graph drawing with
crossings into a SPED is tractable for 2-plane input drawings, but NP-hard for
unrestricted inputs. We show that the problem remains NP-hard even for 3-plane
input drawings and establish NP-hardness of ink maximization for PEDs of
4-plane graphs. Yet, for k-plane input drawings whose edge intersection graph
forms a collection of trees or, more generally, whose intersection graph has
bounded treewidth, we present efficient algorithms for computing maximum-ink
PEDs and SPEDs. We implemented the treewidth-based algorithms and show a brief
experimental evaluation.


  A new criterion for pressure-driven interchange instabilities in cylindrical
geometry is derived, based on an alternate use of the Energy Principle. This
criterion is inequivalent to Suydam's criterion and does not contain the
magnetic shear. In fact, it is shown that Suydam's criterion relates to the
instability of the slow magnetosonic branch, while the present criterion
relates to the Alfv\'enic one, which is the most dangerous of the two. These
findings explain why pressure-driven modes nearly always exist even if Suydam's
criterion is satisfied by a large margin.


  The problem of forecasting conditional probabilities of the next event given
the past is considered in a general probabilistic setting. Given an arbitrary
(large, uncountable) set C of predictors, we would like to construct a single
predictor that performs asymptotically as well as the best predictor in C, on
any data. Here we show that there are sets C for which such predictors exist,
but none of them is a Bayesian predictor with a prior concentrated on C. In
other words, there is a predictor with sublinear regret, but every Bayesian
predictor must have a linear regret. This negative finding is in sharp contrast
with previous results that establish the opposite for the case when one of the
predictors in $C$ achieves asymptotically vanishing error. In such a case, if
there is a predictor that achieves asymptotically vanishing error for any
measure in C, then there is a Bayesian predictor that also has this property,
and whose prior is concentrated on (a countable subset of) C.


  The X-ray source 1E 161348-5055 lies at the centre of the 2-kyr-old supernova
remnant RCW 103. Owing to its 24-ks modulation, orders-of-magnitude flux
variability over a few months/years, and lack of an obvious optical
counterpart, 1E 161348-5055 defies assignment to any known class of X-ray
sources. Starting from April 2006, Swift observed 1E 161348-5055 with its X-ray
telescope for 2 ks approximately once per month. During the five years covered,
the source has remained in a quiescent state, with an average observed flux of
1.7e-12 erg/cm^2/s (1-10 keV), about 20 times lower than the historical maximum
attained in its 1999-2000 outburst. The long time-span of the Swift data allows
us to obtain an accurate measure of the period of 1E 161348-5055 [P =
24030.42(2) s] and to derive the first upper limit on its period derivative
(|dP/dt| < 1.6e-9 s/s at 3 sigma).


  The uniform spanning forest measure ($\mathsf{USF}$) on a locally finite,
infinite connected graph $G$ with conductance $c$ is defined as a weak limit of
uniform spanning tree measure on finite subgraphs. Depending on the underlying
graph and conductances, the corresponding $\mathsf{USF}$ is not necessarily
concentrated on the set of spanning trees. Pemantle~\cite{PR1991} showed that
on $\mathbb{Z}^d$, equipped with the unit conductance $ c=1$, $\mathsf{USF}$ is
concentrated on spanning trees if and only if $d \leq 4$. In this work we study
the $\mathsf{USF}$ associated with conductances induced by $\lambda$--biased
random walk on $\mathbb{Z}^d$, $d \geq 2$, $0 < \lambda < 1$, i.e. conductances
are set to be $c(e) = \lambda^{-|e|}$, where $|e|$ is the graph distance of the
edge $e$ from the origin. Our main result states that in this case
$\mathsf{USF}$ consists of finitely many trees if and only if $d = 2$ or $3$.
More precisely, we prove that the uniform spanning forest has $2^d$ trees if $d
= 2$ or $3$, and infinitely many trees if $d \geq 4$. Our method relies on the
analysis of the spectral radius and the speed of the $\lambda$--biased random
walk on $\mathbb{Z}^d$.


  Whightman function, vacuum expectation values of the field square, and the
energy-momentum tensor are investigated for a scalar field inside a wedge with
and without a coaxial cylindrical boundary. Dirichlet boundary conditions are
assumed on the bounding surfaces. The vacuum energy-momentum tensor is
evaluated in the general case of the curvature coupling parameter. Making use
of a variant of the generalized Abel-Plana formula, expectation values are
presented as the sum of two terms. The first one corresponds to the geometry
without a cylindrical boundary and the second one is induced by the presence of
this boundary. The asymptotic behaviour of the field square, vacuum energy
density and stresses near the boundaries are investigated. The additional
vacuum forces acting on the wedge sides due the presence of the cylindrical
boundary are evaluated and it is shown that these forces are attractive. As a
limiting case, the geometry of two parallel plates perpendicularly intersected
by a third one is analyzed.


  Smart contract, one of the most successful applications of blockchain, is
taking the world by storm, playing an essential role in the blockchain
ecosystem. However, frequent smart contract security incidents not only result
in tremendous economic losses but also destroy the blockchain-based credit
system. The security and reliability of smart contracts thus gain extensive
attention from researchers worldwide. In this survey, we first summarize the
common types and typical cases of smart contract vulnerabilities from three
levels, i.e., Solidity code layer, EVM execution layer, and Block dependency
layer. Further, we review the research progress of smart contract vulnerability
detection and classify existing counterparts into five categories, i.e., formal
verification, symbolic execution, fuzzing detection, intermediate
representation, and deep learning. Empirically, we take 300 real-world smart
contracts deployed on Ethereum as the test samples and compare the
representative methods in terms of accuracy, F1-Score, and average detection
time. Finally, we discuss the challenges in the field of smart contract
vulnerability detection and combine with the deep learning technology to look
forward to future research directions.


  This research hypothesized that a practical approach in the form of a
solution framework known as Natural Language Understanding and Reasoning for
Intelligence (NaLURI), which combines full-discourse natural language
understanding, powerful representation formalism capable of exploiting
ontological information and reasoning approach with advanced features, will
solve the following problems without compromising practicality factors: 1)
restriction on the nature of question and response, and 2) limitation to scale
across domains and to real-life natural language text.


  In a harmonically-trapped rotating Bose-Einstein condensate (BEC), a vortex
of large angular momentum decays to multiple vortices of unit angular momentum
from an energetic consideration. We demonstrate the formation of a robust and
dynamically stable giant vortex of large angular momentum in a harmonically
trapped rotating BEC with a potential hill at the center, thus forming a
Mexican hat like trapping potential. For a small inter-atomic interaction
strength, a highly controllable stable giant vortex appears, whose angular
momentum slowly increases as the angular frequency of rotation is increased. As
the inter-atomic interaction strength is increased beyond a critical value,
only vortices of unit angular momentum are formed, unless the strength of the
potential hill at the center is also increased: for a stronger potential hill
at the center a giant vortex is again formed. The dynamical stability of the
giant vortex is demonstrated by real-time propagation numerically. These giant
vortices of large angular momentum can be observed and studied experimentally
in a highly controlled fashion.


  This article presents an Analysis of Variance model for functional data that
explicitly incorporates phase variability through a time-warping component,
allowing for a unified approach to estimation and inference in presence of
amplitude and time variability. The focus is on single-random-factor models but
the approach can be easily generalized to more complex ANOVA models. The
behavior of the estimators is studied by simulation, and an application to the
analysis of growth curves of flour beetles is presented. Although the model
assumes a smooth latent process behind the observed trajectories, smoothness of
the observed data is not required; the method can be applied to the sparsely
observed data that is often encountered in longitudinal studies.


  We present a unification and generalization of sequentially and
hierarchically semi-separable (SSS and HSS) matrices called tree semi-separable
(TSS) matrices. Our main result is to show that any dense matrix can be
expressed in a TSS format. Here, the dimensions of the generators are specified
by the ranks of the Hankel blocks of the matrix. TSS matrices satisfy a
graph-induced rank structure (GIRS) property. It is shown that TSS matrices
generalize the algebraic properties of SSS and HSS matrices under addition,
products, and inversion. Subsequently, TSS matrices admit linear time
matrix-vector multiply, matrix-matrix multiply, matrix-matrix addition,
inversion, and solvers.


  Porous graphene has high mechanical strength and atomic layer thickness,
which make it a promising material for material separation and biomolecule
sensing. Electrostatic interactions between charges in aqueous solution are a
kind of strong long-range interaction which may have great influence on the
fluid transport through nanopores. Here, molecular dynamics simulations were
conducted to investigate ion and water transport through a 1.05-nm-in-diameter
monolayer graphene nanopore with its edge charge-modified. From the results, it
is found that the nanopores are selective to counterions when they are charged.
As the charge amount increases, the total ionic currents show an
increase-decrease profile while the co-ion currents monotonously decrease. The
co-ions rejection can reach 75% and 90% when the nanopores are negatively and
positively charged, respectively. Cl ions current increases and reaches a
plateau, and Na+ current decreases with the charge amount in the systems where
they act as counterions. Besides, the charge modification can enhance the water
transport through nanopores obviously. This is mainly due to the ion selection
of nanopores. Especially, positive charges on the pore edge facilitate the
water transport much more than negative charges.


  The measurement of proper motions in CSOs is a powerful tool to determine the
dynamical evolution of the newly born extragalactic radio sources. We observed
3 CSOs with the VLBA in 2004 and in 2006 to monitor changes in their structure
and measure the separation velocity of the hot spots. It is important to
increase the size of the samples of CSOs with measured expansion velocity to
test the existance of frustrated objects, and put stringent constraints on the
current models. We found for all the three objects observed a transverse motion
of the hotspots, and we suggest as the more likey explanation a precession in
the jet axis. This behaviour likely inhibits or at least slows down the radio
source growth because the head of the hotspot continuously hits new regions of
the ISM. Therefore these radio sources may represent an old population of
GPS/CSOs.


  We shall prove the universality of the curvature identity for the
4-dimensional Riemannian manifold using a different method than that used by
Gilkey, Park, and Sekigawa \cite{GPS}.


  Classification of ordinal data is one of the most important tasks of relation
learning. In this thesis a novel framework for ordered classes is proposed. The
technique reduces the problem of classifying ordered classes to the standard
two-class problem. The introduced method is then mapped into support vector
machines and neural networks. Compared with a well-known approach using
pairwise objects as training samples, the new algorithm has a reduced
complexity and training time. A second novel model, the unimodal model, is also
introduced and a parametric version is mapped into neural networks. Several
case studies are presented to assert the validity of the proposed models.


  We consider the extension of the thermodynamic Bethe Ansatz (TBA) to cases in
which additional terms involving higher conserved charges are added to the
Hamiltonian, or in which a distinction is made between the Hamiltonian used for
time evolution and that used for defining the density matrix. Writing down
equations describing the saddle-point (pseudo-equilibrium) state of the
infinite system, we prove the existence and uniqueness of solutions for
Lieb-Liniger provided simple requirements are met. We show how a knowledge of
the saddle-point rapidity distribution is equivalent to that of all generalized
chemical potentials, and how the standard equilibrium equations for e.g.
excitations are simply generalized.


  We develop infinite-dimensional Ramsey theory for Fra\"iss\'e limits of
finitely constrained free amalgamation classes in finite binary languages. We
show that our approach is optimal and in particular, recovers the exact big
Ramsey degrees proved in [2] for these structures. A crucial step in the work
develops the new notion of an A.3(2)-ideal and shows that Todorcevic's Abstract
Ramsey Theorem holds when Axiom A.3(2) is replaced by the weaker assumption of
an A.3(2)-ideal.


  We consider a constrained Markov Decision Problem (CMDP) where the goal of an
agent is to maximize the expected discounted sum of rewards over an infinite
horizon while ensuring that the expected discounted sum of costs exceeds a
certain threshold. Building on the idea of momentum-based acceleration, we
develop the Primal-Dual Accelerated Natural Policy Gradient (PD-ANPG) algorithm
that guarantees an $\epsilon$ global optimality gap and $\epsilon$ constraint
violation with $\tilde{\mathcal{O}}(\epsilon^{-2})$ sample complexity for
general parameterized policies. This improves the state-of-the-art sample
complexity in general parameterized CMDPs by a factor of
$\mathcal{O}(\epsilon^{-2})$ and achieves the theoretical lower bound.


  The notion of many-body quantum scars is associated with special eigenstates,
usually concentrated in certain parts of Hilbert space, that give rise to
robust persistent oscillations in a regime that globally exhibits
thermalization. Here we extend these studies to many-body systems possessing a
true classical limit characterized by a high-dimensional chaotic phase space,
which are not subject to any particular dynamical constraint. We demonstrate
genuine quantum scarring of wave functions concentrated in the vicinity of
unstable classical periodic mean-field modes in the paradigmatic Bose-Hubbard
model. These peculiar quantum many-body states exhibit distinct phase-space
localization about those classical modes. Their existence is consistent with
Heller's scar criterion and appears to persist in the thermodynamic
long-lattice limit. Launching quantum wave packets along such scars leads to
observable long-lasting oscillations, featuring periods that scale
asymptotically with classical Lyapunov exponents, and displaying intrinsic
irregularities that reflect the underlying chaotic dynamics, as opposed to
regular tunnel oscillations.


  We investigate the development of the magnetic Rayleigh-Taylor instability at
the inner edge of an astrophysical disk around a spinning central black hole.
We solve the equations of general relativity that govern small amplitude
oscillations of a discontinuous interface in a Keplerian disk threaded by an
ordered magnetic field, and we derive a stability criterion that depends on the
central black hole spin and the accumulated magnetic field. We also compare our
results with the results of GR MHD simulations of black hole accretion flows
that reach a magnetically arrested state (MAD). We found that the instability
growth timescales that correspond to the simulation parameters are comparable
to the corresponding timescales for free-fall accretion from the ISCO onto the
black hole. We thus propose that the Rayleigh-Taylor instability disrupts the
accumulation of magnetic flux onto the black hole horizon as the disk reaches a
MAD state.


  We consider the area and entropy spectra of black holes in topologically
massive gravity with gravitational Chern-Simons term. The examples we consider
are the BTZ black hole and the warped AdS black hole. For the non-rotating BTZ
black hole, the area and entropy spectra are equally spaced and independent of
the coupling constant $\v$ of the Chern-Simons term. For the rotating BTZ black
hole case, the spectra of the inner and outer horizon areas are not equally
spaced in general and dependent of the coupling constant $\v$. However the
entropy spectrum is equally spaced and independent of the coupling constant
$\v$. For the warped AdS black holes for $\v >1$ by using the quasinormal modes
obtained without imposing the boundary condition at radial infinity we find
again that the entropy spectrum is equally spaced and independent of the
coupling constant $\v$, while the spectra of the inner and outer horizon areas
are not equally spaced and dependent of the coupling constant $\v$. Our result
implies that the entropy spectrum has a universal behavior regardless of the
presence of the gravitational Chern-Simons term, and therefore it implies that
the entropy is more `fundamental' than the horizon area.


  The challenge of defining a slot schema to represent the state of a
task-oriented dialogue system is addressed by Slot Schema Induction (SSI),
which aims to automatically induce slots from unlabeled dialogue data. Whereas
previous approaches induce slots by clustering value spans extracted directly
from the dialogue text, we demonstrate the power of discovering slots using a
generative approach. By training a model to generate slot names and values that
summarize key dialogue information with no prior task knowledge, our SSI method
discovers high-quality candidate information for representing dialogue state.
These discovered slot-value candidates can be easily clustered into unified
slot schemas that align well with human-authored schemas. Experimental
comparisons on the MultiWOZ and SGD datasets demonstrate that Generative
Dialogue State Inference (GenDSI) outperforms the previous state-of-the-art on
multiple aspects of the SSI task.


  Crystallization is one of the most important physicochemical processes which
has relevance in material science, biology, and the environment. Decades of
experimental and theoretical efforts have been made to understand this
fundamental symmetry-breaking transition. While experiments provide equilibrium
structures and shapes of crystals, they are limited to unraveling how molecules
aggregate to form crystal nuclei that subsequently transform into bulk
crystals. Computer simulations, mainly molecular dynamics (MD), can provide
such microscopic details during the early stage of a crystallization event.
Crystallization is a rare event that takes place in timescales much longer than
a typical equilibrium MD simulation can sample. This inadequate sampling of the
MD method can be easily circumvented by the use of enhanced sampling (ES)
simulations. An ES method enhances the fluctuations of a system's slow degrees
of freedom, called collective variables (CVs), by applying a bias potential,
and thereby transforms the system from one state to the other within a short
timescale. The most crucial part of an ES method is to find suitable CVs which
often needs intuition and several trial-and-error optimization steps. Over the
years, a plethora of CVs has been developed and applied in the study of
crystallization. In this review, we provide a brief overview of CVs that have
been developed and used in ES simulations to study crystallization from melt or
solution. These CVs can be categorized mainly into four types: (i) spherical
particle-based, (ii) molecular template-based, (iii) physical property-based,
and (iv) CVs obtained from dimensionality reduction techniques. We present the
context-based evolution of CVs, discuss the current challenges, and propose
future directions to further develop effective CVs for the study of
crystallization of complex systems.


  Rate-Splitting (RS) has been proposed recently to enhance the performance of
multi-user multiple-input multiple-output (MU-MIMO) systems. In RS, a user
message is split into a common and a private part, where the common part is
decoded by all users, while the private part is decoded only by the intended
user. In this paper, we study RS under a phase-shift keying (PSK) input
alphabet for multi-user multi-antenna system and propose a constructive
interference (CI) exploitation approach to further enhance the sum-rate
achieved by RS under PSK signaling. To that end, new analytical expressions for
the ergodic sum-rate are derived for two precoding techniques of the private
messages, namely, 1) a traditional interference suppression zero-forcing (ZF)
precoding approach, 2) a closed-form CI precoding approach. Our analysis is
presented for perfect channel state information at the transmitter (CSIT), and
is extended to imperfect CSIT knowledge. A novel power allocation strategy,
specifically suited for the finite alphabet setup, is derived and shown to lead
to superior performance for RS over conventional linear precoding not relying
on RS (NoRS). The results in this work validate the significant sum-rate gain
of RS with CI over the conventional RS with ZF and NoRS.