  The self-similarity hypothesis claims that in classical general relativity,
spherically symmetric solutions may naturally evolve to a self-similar form in
certain circumstances. In this context, the validity of the corresponding
hypothesis in nonspherical geometry is very interesting as there may exist
gravitational waves. We investigate self-similar vacuum solutions to the
Einstein equation in the so-called whole-cylinder symmetry. We find that those
solutions are reduced to part of the Minkowski spacetime with a regular or
conically singular axis and with trivial or nontrivial topology if the
homothetic vector is orthogonal to the cylinders of symmetry. These solutions
are analogous to the Milne universe, but only in the direction parallel to the
axis. Using these solutions, we discuss the nonuniqueness (and nonvanishing
nature) of C energy and the existence of a cylindrical trapping horizon in
Minkowski spacetime. Then, as we generalize the analysis, we find a
two-parameter family of self-similar vacuum solutions, where the homothetic
vector is not orthogonal to the cylinders in general. The family includes the
Minkowski, the Kasner and the cylindrical Milne solutions. The obtained
solutions describe the interior to the exploding (imploding) shell of
gravitational waves or the collapse (explosion) of gravitational waves
involving singularities from nonsingular initial data in general. Since recent
numerical simulations strongly suggest that one of these solutions may describe
the asymptotic behavior of gravitational waves from the collapse of a dust
cylinder, this means that the self-similarity hypothesis is naturally
generalized to cylindrical symmetry.


  We continue here the study of Lax integrable equations. We consider four
three-dimensional equations: (1) the rdDym equation $u_{ty} = u_x u_{xy} - u_y
u_{xx}$, (2) the 3D Pavlov equation $u_{yy} = u_{tx} + u_y u_{xx} - u_x
u_{xy}$; (3) the universal hierarchy equation $u_{yy} = u_t u_{xy} - u_y
u_{tx}$, and (4) the modified Veronese web equation $u_{ty} = u_t u_{xy} - u_y
u_{tx}$. For each equation, using the know Lax pairs and expanding the latter
in formal series in spectral parameter, we construct two infinite-dimensional
differential coverings and give a full description of nonlocal symmetry
algebras associated to these coverings. For all the for pairs of coverings, the
obtained Lie algebras of symmetries manifest similar (but not the same)
structures: the are (semi) direct sums of the Witt algebra, the algebra of
vector fields on the line, and loop algebras; all of them contain a component
of finite grading. We also discuss actions of recursion operators on shadows
(in the sense of [I.S.Krasil'shchik, A.M. Vinogradov, Acta Appl. Math., 15
(1989) 1-2, 161--209.]) of nonlocal symmetries.


  We construct cross sections for the geodesic flow on the orbifolds
$\Gamma\backslash H$ which are tailor-made for the requirements of transfer
operator approaches to Maass cusp forms and Selberg zeta functions. Here, $H$
denotes the hyperbolic plane and $\Gamma$ is a nonuniform geometrically finite
Fuchsian group (not necessarily a lattice, not necessarily arithmetic) which
satisfies an additional condition of geometric nature. The construction of the
cross sections is uniform, geometric, explicit and algorithmic.


  In the Standard Model of particle physics, the strength of the couplings of
the $b$ quark to the $u$ and $c$ quarks, $|V_{ub}|$ and $|V_{cb}|$, are
governed by the coupling of the quarks to the Higgs boson. Using data from the
LHCb experiment at the Large Hadron Collider, the probability for the
$\Lambda^0_b$ baryon to decay into the $p \mu^- \overline{\nu}_\mu$ final state
relative to the $\Lambda^+_c \mu^- \overline{\nu}_\mu$ final state is measured.
Combined with theoretical calculations of the strong interaction and a
previously measured value of $|V_{cb}|$, the first $|V_{ub}|$ measurement to
use a baryonic decay is performed. This measurement is consistent with previous
determinations of $|V_{ub}|$ using $B$ meson decays to specific final states
and confirms the existing incompatibility with those using an inclusive sample
of final states.


  Most deep learning-based point cloud processing methods are supervised and
require large scale of labeled data. However, manual labeling of point cloud
data is laborious and time-consuming. Self-supervised representation learning
can address the aforementioned issue by learning robust and generalized
representations from unlabeled datasets. Nevertheless, the embedded features
obtained by representation learning usually contain redundant information, and
most current methods reduce feature redundancy by linear correlation
constraints. In this paper, we propose PointJEM, a self-supervised
representation learning method applied to the point cloud field. PointJEM
comprises an embedding scheme and a loss function based on joint entropy. The
embedding scheme divides the embedding vector into different parts, each part
can learn a distinctive feature. To reduce redundant information in the
features, PointJEM maximizes the joint entropy between the different parts,
thereby rendering the learned feature variables pairwise independent. To
validate the effectiveness of our method, we conducted experiments on multiple
datasets. The results demonstrate that our method can significantly reduce
feature redundancy beyond linear correlation. Furthermore, PointJEM achieves
competitive performance in downstream tasks such as classification and
segmentation.


  Ultrafast carrier relaxation in the 2D topological insulator (TI) Bi2Se3
[gapped Dirac surface states (SS)] and how it inherits ultrafast relaxation in
the 3D TI Bi2Se3 (gapless Dirac SS) remains a challenge for developing new
optoelectronic devices based on these materials. Here ultrashort (100 fs)
pumping pulses of ~340 nm wavelength (~3.65 eV photon energy) were applied to
study ultrafast electron relaxation in the 2D TI Bi2Se3 films with a thickness
of 2 and 5 quintuple layers (~2 and ~5 nm, respectively) using transient
absorption (TA) spectroscopy in the ultraviolet-visible spectral region (1.65 -
3.85 eV). The negative and positive contributions of TA spectra were attributed
to absorption bleaching that mostly occur in the bulk states and to the inverse
bremsstrahlung type free carrier absorption in the surface states,
respectively. Owing to this direct and selective access to the bulk and surface
carrier dynamics, we were able to monitor coherent longitudinal optical (LO)
phonon oscillations, which were successively launched in the bulk and surface
states by the front of the relaxing electron population within the LO-phonon
cascade emission. We have also recognized the coherent surface-to-bulk
vibrational coupling that appears through the phase-dependent amplitude
variations of coherent LO-phonon oscillations. This unique behavior manifests
itself predominantly for the topologically trivial insulator phase of the 2D TI
Bi2Se3 (2 nm thick film) in the photon energy range (~2.0 - 2.25 eV) where
efficient energy exchange between the bulk and surface states occurs. We also
found that the coherent surface-to-bulk vibrational coupling significantly
weakens with increasing both the Bi2Se3 film thickness and pumping power.


  In the following we stress the advantages of the NICA research programme in
the context of studying the spectator-induced electromagnetic phenomena present
in proton-nucleus and heavy ion collisions. We point at the specific interest
of using these phenomena as a new, independent source of information on the
space-time evolution of the reaction and of the non-perturbative process of
particle production. We propose an extended series of measurements of
well-defined observables to be performed in different types of nuclear
reactions and in the whole range of collision energies available to NICA. We
expect these measurements to bring very valuable new insight into the mechanism
of non-perturbative strong interactions, complementary to the studies made at
the SPS at CERN, RHIC at BNL, and the LHC.


  We experimentally study the behavior of a parametrically pumped nonlinear
oscillator, which is based on a superconducting \lambda /4 resonator, and is
terminated by a flux-tunable SQUID. We extract parameters for two devices. In
particular, we study the effect of the nonlinearities in the system and compare
to theory. The Duffing nonlinearity, \alpha, is determined from the probe-power
dependent frequency shift of the oscillator, and the nonlinearity, \beta,
related to the parametric flux pumping, is determined from the pump amplitude
for the onset of parametric oscillations. Both nonlinearities depend on the
parameters of the device and can be tuned in-situ by the applied dc flux. We
also suggest how to cancel the effect of \beta by adding a small dc flux and a
pump tone at twice the pump frequency.


  Control and characterization of networks is a paramount step for the
development of many quantum technologies. Even for moderate-sized networks,
this amounts to explore an extremely vast parameters space in search for the
couplings defining the network topology. Here we explore the use of a genetic
algorithm to retrieve the topology of a network from the measured probability
distribution obtained from the evolution of a continuous-time quantum walk on
the network. Our result shows that the algorithm is capable of efficiently
retrieving the required information even in the presence of noise.


  The investigation of the wind in the solar corona initiated with the
observations of the resonantly scattered UV emission of the coronal plasma
obtained with UVCS-SOHO, designed to measure the wind outflow speed by applying
the Doppler dimming diagnostics. Metis on Solar Orbiter complements the UVCS
spectroscopic observations, performed during solar activity cycle 23, by
simultaneously imaging the polarized visible light and the HI Ly-alpha corona
in order to obtain high-spatial and temporal resolution maps of the outward
velocity of the continuously expanding solar atmosphere. The Metis
observations, on May 15, 2020, provide the first HI Ly-alpha images of the
extended corona and the first instantaneous map of the speed of the coronal
plasma outflows during the minimum of solar activity and allow us to identify
the layer where the slow wind flow is observed. The polarized visible light
(580-640 nm), and the UV HI Ly-alpha (121.6 nm) coronal emissions, obtained
with the two Metis channels, are combined in order to measure the dimming of
the UV emission relative to a static corona. This effect is caused by the
outward motion of the coronal plasma along the direction of incidence of the
chromospheric photons on the coronal neutral hydrogen. The plasma outflow
velocity is then derived as a function of the measured Doppler dimming. The
static corona UV emission is simulated on the basis of the plasma electron
density inferred from the polarized visible light. This study leads to the
identification, in the velocity maps of the solar corona, of the high-density
layer about +/-10 deg wide, centered on the extension of a quiet equatorial
streamer present at the East limb where the slowest wind flows at about (160
+/- 18) km/s from 4 Rs to 6 Rs. Beyond the boundaries of the high-density
layer, the wind velocity rapidly increases, marking the transition between slow
and fast wind in the corona.


  We discuss the role of lightest neutrino mass (m_0) in the neutrino mass
matrix, defined in a flavor basis, through a bottom-up approach using the
current neutrino oscillation data. We find that if m_0 < 10^{-3} eV, then the
deviation \delta M_\nu in the neutrino mass matrix from a tree-level, say
tribimaximal neutrino mass matrix, does not depend on m_0. As a result \delta
M_\nu's are exactly predicted in terms of the experimentally determined
quantities such as solar and atmospheric mass squared differences and the
mixing angles. On the other hand for m_0 \gsim 10^{-3} eV, \delta M_\nu
strongly depends on m_0 and hence can not be determined within the knowledge of
oscillation parameters alone. In this limit, we provide an exponential
parameterization for \delta M_\nu for all values of m_0 such that it can
factorize the m_0 dependency of \delta M_\nu from rest of the oscillation
parameters. This helps us in finding \delta M_\nu as a function of the solar
and atmospheric mass squared differences and the mixing angles for all values
of m_0. We use this information to build up a model of neutrino masses and
mixings in a top-down scenario which can predict large \theta_{13}
perturbatively.


  Charge transfer in oxide heterostructures can be tuned to promote emergent
interfacial states, and accordingly, has been the subject of intense study in
recent years. However, accessing the physics at these interfaces, which are
often buried deep below the sample surface, remains difficult. Addressing this
challenge requires techniques capable of measuring the local electronic
structure with high-resolution depth dependence. Here, we have used
linearly-polarized resonant X-ray reflectometry (RXR) as a means to visualize
charge transfer in oxide superlattices with atomic layer precision. From our
RXR measurements, we extract valence depth profiles of SmTiO$_3$
(SmTO)/SrTiO$_3$ (STO) heterostructures with STO quantum wells varying in
thickness from 5 SrO planes down to a single, atomically thin SrO plane. At the
polar-nonpolar SmTO/STO interface, an electrostatic discontinuity leads to
approximately half an electron per areal unit cell transferred from the
interfacial SmO layer into the neighboring STO quantum well. We observe this
charge transfer as a suppression of the t$_{2g}$ absorption peaks that
minimizes contrast with the neighboring SmTO layers at those energies and leads
to a pronounced absence of superlattice peaks in the reflectivity data. Our
results demonstrate the sensitivity of RXR to electronic reconstruction at the
atomic scale, and establish RXR as a powerful means of characterizing charge
transfer at buried oxide interfaces.


  A comparison of the 2MASS flux dipole to the CMB dipole can serve as a method
to constrain a combination of the cosmological parameter Omega_m and the
luminosity bias of the 2MASS survey. For this constraint to be as tight as
possible, it is necessary to maximize the correlation between the two dipoles.
This can be achieved by optimizing the survey window through which the flux
dipole is measured. Here we explicitly construct such a window for the 2MASS
survey. The optimization in essence reduces to excluding from the calculation
of the flux dipole galaxies brighter than some limiting magnitude K_min of the
near-infrared K_s band. This exclusion mitigates nonlinear effects and shot
noise from small scales, which decorrelate the 2MASS dipole from the CMB
dipole. Under the assumption of negligible shot noise we find that the optimal
value of K_min is about five. Inclusion of shot noise shifts the optimal K_min
to larger values. We present an analytical formula for shot noise for the 2MASS
flux dipole, to be used in follow-up work with 2MASS data.
  The misalignment angle between the two dipoles is a sensitive measure of
their correlation: the higher the correlation, the smaller the expectation
value of the angle. A minimum of the misalignment is thus a sign of the optimal
gravity window. We model analytically the distribution function for the
misalignment angle and show that the misalignment estimated by Maller et al. is
consistent with the assumed underlying model (though it is greater than the
expectation value). We predict with about 90% confidence that the misalignment
will decrease if 2MASS galaxies brighter than K_min = 5 mag are excluded from
the calculation of the flux dipole. This prediction has been indirectly
confirmed by the results of Erdogdu et al. (ABRIDGED)


  Monolayer transition metal dichalcogenides have recently attracted great
interests because the quantum dots embedded in monolayer can serve as optically
active single photon emitters. Here, we provide an interpretation of the
recombination mechanisms of these quantum emitters through
polarization-resolved and magneto-optical spectroscopy at low temperature.
Three types of defect-related quantum emitters in monolayer tungsten diselenide
(WSe$_2$) are observed, with different exciton g factors of 2.02, 9.36 and
unobservable Zeeman shift, respectively. The various magnetic response of the
spatially localized excitons strongly indicate that the radiative recombination
stems from the different transitions between defect-induced energy levels,
valance and conduction bands. Furthermore, the different g factors and
zero-field splittings of the three types of emitters strongly show that quantum
dots embedded in monolayer have various types of confining potentials for
localized excitons, resulting in electron-hole exchange interaction with a
range of values in the presence of anisotropy. Our work further sheds light on
the recombination mechanisms of defect-related quantum emitters and paves a way
toward understanding the role of defects in single photon emitters in
atomically thin semiconductors.


  Infinitely many new examples of compact Lorentzian surfaces without conjugate
points are given. Further, we study the existence and the stability of this
property among Lorentzian metrics with a Killing field. We obtain a new
obstruction and prove that the Clifton- Pohl torus and some of our examples are
as stable as possible. This shows that in constrast with the Riemannian Hopf
theorem, the absence of conjugate points in the Lorentzian setting is neither
"special" nor rigid.


  Signed graphs are an emergent way of representing data in a variety of
contexts were conflicting interactions exist. These include data from
biological, ecological, and social systems. Here we propose the concept of
communicability geometry for signed graphs, proving that metrics in this space,
such as the communicability distance and angles, are Euclidean and spherical.
We then apply these metrics to solve several problems in data analysis of
signed graphs in a unified way. They include the partitioning of signed graphs,
dimensionality reduction, finding hierarchies of alliances in signed networks
as well as the quantification of the degree of polarization between the
existing factions in systems represented by this type of graphs.


  We analyze the singular spectrum of selfadjoint operators which arise from
pasting a finite number of boundary relations with a standard interface
condition. A model example for this situation is a Schroedinger operator on a
star-shaped graph with continuity and Kirchhoff conditions at the interior
vertex. We compute the multiplicity of the singular spectrum in terms of the
spectral measures of the Weyl functions associated with the single
(independently considered) boundary relations. This result is a generalization
and refinement of Theorem of I.S. Kac.


  Embedding knowledge graphs (KGs) into continuous vector spaces is a focus of
current research. Early works performed this task via simple models developed
over KG triples. Recent attempts focused on either designing more complicated
triple scoring models, or incorporating extra information beyond triples. This
paper, by contrast, investigates the potential of using very simple constraints
to improve KG embedding. We examine non-negativity constraints on entity
representations and approximate entailment constraints on relation
representations. The former help to learn compact and interpretable
representations for entities. The latter further encode regularities of logical
entailment between relations into their distributed representations. These
constraints impose prior beliefs upon the structure of the embedding space,
without negative impacts on efficiency or scalability. Evaluation on WordNet,
Freebase, and DBpedia shows that our approach is simple yet surprisingly
effective, significantly and consistently outperforming competitive baselines.
The constraints imposed indeed improve model interpretability, leading to a
substantially increased structuring of the embedding space. Code and data are
available at https://github.com/iieir-km/ComplEx-NNE_AER.


  This paper studies the multi-antenna multicast channel with integrated
sensing and communication (ISAC), in which a multi-antenna base station (BS)
sends common messages to a set of single-antenna communication users (CUs) and
simultaneously estimates the parameters of an extended target via radar
sensing. We investigate the fundamental performance limits of this ISAC system,
in terms of the achievable rate for communication and the estimation
Cram\'er-Rao bound (CRB) for sensing. First, we derive the optimal transmit
covariance in semi-closed form to balance the CRB-rate (C-R) tradeoff, and
accordingly characterize the outer bound of a so-called C-R region. It is shown
that the optimal transmit covariance should be of full rank, consisting of both
information-carrying and dedicated sensing signals in general. Next, we
consider a practical joint information and sensing beamforming design, and
propose an efficient approach to optimize the joint beamforming for balancing
the C-R tradeoff. Numerical results are presented to show the C-R region
achieved by the optimal transmit covariance and the joint beamforming, as
compared to other benchmark schemes.


  We obtain refined generating series formulae for equivariant characteristic
classes of external and symmetric products of singular complex quasi-projective
varieties. More concretely, we study equivariant versions of Todd, Chern and
Hirzebruch classes for singular spaces, with values in delocalized Borel-Moore
homology of external and symmetric products. As a byproduct, we recover our
previous characteristic class formulae for symmetric products, and obtain new
equivariant generalizations of these results, in particular also in the context
of twisting by representations of the symmetric group.


  Many physical and physiological signals exhibit complex scale-invariant
features characterized by $1/f$ scaling and long-range power-law correlations,
suggesting a possibly common control mechanism. Specifically, it has been
suggested that dynamical processes influenced by inputs and feedback on
multiple time scales may be sufficient to give rise to $1/f$ scaling and scale
invariance. Two examples of physiologic signals that are the output of
hierarchical, multi-scale physiologic systems under neural control are the
human heartbeat and human gait. Here we show that while both cardiac interbeat
interval and gait interstride interval time series under healthy conditions
have comparable $1/f$ scaling, they still may belong to different complexity
classes. Our analysis of the magnitude series correlations and multifractal
scaling exponents of the fluctuations in these two signals demonstrates that in
contrast with the nonlinear multifractal behavior found in healthy heartbeat
dynamics, gait time series exhibit less complex, close to monofractal behavior
and a low degree of nonlinearity. These findings are of interest because they
underscore the limitations of traditional two-point correlation methods in
fully characterizing physiologic and physical dynamics. In addition, these
results suggest that different mechanisms of control may be responsible for
varying levels of complexity observed in physiological systems under neural
regulation and in physical systems that possess similar $1/f$ scaling.


  Current video cards (GPUs - Graphics Processing Units) are very programmable,
have become much more powerful than the CPUs and they are very affordable. In
this paper, we present an implementation for the AES algorithm using Direct3D
10 certified GPUs. The graphics API Direct3D 10 is the first version that
allows the use of integer operations, making from the traditional GPUs (that
works only with floating point numbers), General Purpose GPUs that can be used
for a large number of algorithms, including encryption. We present the
performance of the symmetric key encryption algorithm - AES, on a middle range
GPU and on a middle range quad core CPU. On the testing system, the developed
solution is almost 3 times faster on the GPU than on one single core CPU,
showing that the GPU can perform as an efficient cryptographic accelerator.


  We propose a new Q-learning variant, called 2RA Q-learning, that addresses
some weaknesses of existing Q-learning methods in a principled manner. One such
weakness is an underlying estimation bias which cannot be controlled and often
results in poor performance. We propose a distributionally robust estimator for
the maximum expected value term, which allows us to precisely control the level
of estimation bias introduced. The distributionally robust estimator admits a
closed-form solution such that the proposed algorithm has a computational cost
per iteration comparable to Watkins' Q-learning. For the tabular case, we show
that 2RA Q-learning converges to the optimal policy and analyze its asymptotic
mean-squared error. Lastly, we conduct numerical experiments for various
settings, which corroborate our theoretical findings and indicate that 2RA
Q-learning often performs better than existing methods.


  Astronomy has entered the multi-messenger data era and Machine Learning has
found widespread use in a large variety of applications. The exploitation of
synoptic (multi-band and multi-epoch) surveys, like LSST (Legacy Survey of
Space and Time), requires an extensive use of automatic methods for data
processing and interpretation. With data volumes in the petabyte domain, the
discrimination of time-critical information has already exceeded the
capabilities of human operators and crowds of scientists have extreme
difficulty to manage such amounts of data in multi-dimensional domains. This
work is focused on an analysis of critical aspects related to the approach,
based on Machine Learning, to variable sky sources classification, with special
care to the various types of Supernovae, one of the most important subjects of
Time Domain Astronomy, due to their crucial role in Cosmology. The work is
based on a test campaign performed on simulated data. The classification was
carried out by comparing the performances among several Machine Learning
algorithms on statistical parameters extracted from the light curves. The
results make in evidence some critical aspects related to the data quality and
their parameter space characterization, propaedeutic to the preparation of
processing machinery for the real data exploitation in the incoming decade.


  The angular power spectrum of a stationary random field on the sphere is
estimated from the needlet coefficients of a single realization, observed with
increasingly fine resolution. The estimator we consider is similar to the one
recently used in practice by (Fa\"{y} et al. 2008) to estimate the power
spectrum of the Cosmic Microwave Background. The consistency of the estimator,
in the asymptotics of high frequencies, is proved for a model with a stationary
Gaussian field corrupted by heteroscedastic noise and missing data.


  We present J=2-1, J=3-2, J=4-3 12CO maps as well as J=2-1, J=3-2 13CO and 492
GHz [CI] measurements of the central region in M51. The distribution of CO is
strongly concentrated towards the spiral arms. The center itself is poor in,
though not devoid of, CO emission. The observed line intensities require
modelling with a multi-component molecular gas. A dense component must be
present with n(H2) = 1000 cm-3 and kinetic temperature T(kin)= 100 K, combined
with either a less dense (about 100 cm-3) component of the same temperature, or
a more dense (n(H2) = 3000 cm-3) and much cooler (T(kin) = 10-30 K) component.
Atomic carbon amounts are between 5 and 10 times those of CO. Much of the
molecular gas mass is associated with the hot PDR phase. The center of M 51 has
a face-on gas mass density of about 40+/-20 M(O) pc-2, and a well-established
CO-to-H2 conversion ratio X four to five times lower than the standard Galactic
value.


  Orbit separation dimension (OSD), previously introduced as amorphic
complexity, is a powerful complexity measure for topological dynamical systems
with pure-point spectrum. Here, we develop methods and tools for it that allow
a systematic application to translation dynamical systems of tiling spaces that
are generated by primitive inflation rules. These systems share many nice
properties that permit the explicit computation of the OSD, thus providing a
rich class of examples with non-trivial OSD.


  We prove that, for a primitive permutation group G acting on a set of size n,
other than the alternating group, the probability that Aut(X,Y^G) = G for a
random subset Y of X, tends to 1 as n tends to infinity. So the property of the
title holds for all primitive groups except the alternating groups and finitely
many others. This answers a question of M. Klin. Moreover, we give an upper
bound n^{1/2+\epsilon} for the minimum size of the edges in such a hypergraph.
This is essentially best possible.


  In this article, we present a new model for a synchronous generator based on
phasor measurement units (PMUs) data. The proposed sub-transient model allows
to estimate the dynamic state variables as well as to calibrate model
parameters. The motivation for this new model is to use more efficiently the
PMU measurements which are becoming widely available in power grids. The
concept of phasor derivative is applied, which not only includes the signal
phase derivative but also its amplitude derivative. Applying known non-linear
estimation techniques, we study the merits of this new model. In particular, we
test robustness by considering a generator with different mechanical power
controls.


  We present a telepresence system based on a custom-made simulated holographic
display that produces a full 3D model of the remote participants using
commodity depth sensors. Our display is composed of a video projector and a
quadrangular pyramid made of acrylic, that allows the user to experience an
omnidirectional visualization of a remote person without the need for
head-mounted displays. To obtain a precise representation of the participants,
we fuse together multiple views extracted using a deep background subtraction
method. Our system represents an attempt to democratize high-fidelity 3D
telepresence using off-the-shelf components.


  For a commutative ring $R$, in contrast to the completion in the sense of
Bousfield and Kan at just a prime integer, there cannot exist spaces which are
good and bad in an arbitrary way.


  Knowledge Distillation (KD) has made remarkable progress in the last few
years and become a popular paradigm for model compression and knowledge
transfer. However, almost all existing KD algorithms are data-driven, i.e.,
relying on a large amount of original training data or alternative data, which
is usually unavailable in real-world scenarios. In this paper, we devote
ourselves to this challenging problem and propose a novel adversarial
distillation mechanism to craft a compact student model without any real-world
data. We introduce a model discrepancy to quantificationally measure the
difference between student and teacher models and construct an optimizable
upper bound. In our work, the student and the teacher jointly act the role of
the discriminator to reduce this discrepancy, when a generator adversarially
produces some "hard samples" to enlarge it. Extensive experiments demonstrate
that the proposed data-free method yields comparable performance to existing
data-driven methods. More strikingly, our approach can be directly extended to
semantic segmentation, which is more complicated than classification, and our
approach achieves state-of-the-art results. Code and pretrained models are
available at https://github.com/VainF/Data-Free-Adversarial-Distillation.


  Using well-calibrated experimental data we validate theoretical X-ray
absorption spectroscopy (XAS) as well as X-ray emission spectroscopy (XES)
calculations for titanium (Ti), titanium oxide (TiO), and titanium dioxide
(TiO$_2$) at the Ti K- and L-edges as well as O K-edge. XAS and XES in
combination with a multi-edge approach offer a detailed insight into the
electronic structure of materials since both the occupied and unoccupied
states, are probed. The experimental results are compared with ab initio
calculations from the OCEAN package which uses the Bethe-Salpeter equation
(BSE) approach. Using the same set of input parameters for each compound for
calculations at different edges, the transferability of the OCEAN calculations
across different spectroscopy methods and energy ranges is validated. Thus, the
broad applicability for analysing and interpreting the electronic structure of
materials with the OCEAN package is shown.


  The structure of protostellar cores can often be approximated by isothermal
Bonnor-Ebert spheres (BES) which are stabilized by an external pressure. For
the typical pressure of $10^4k_B\,\mathrm{K\,cm^{-3}}$ to
$10^5k_B\,\mathrm{K\,cm^{-3}}$ found in molecular clouds, cores with masses
below $1.5\,{\rm M_\odot}$ are stable against gravitational collapse. In this
paper, we analyze the efficiency of triggering a gravitational collapse by a
nearby stellar wind, which represents an interesting scenario for triggered
low-mass star formation. We derive analytically a new stability criterion for a
BES compressed by a stellar wind, which depends on its initial nondimensional
radius $\xi_{max}$. If the stability limit is violated the wind triggers a core
collapse. Otherwise, the core is destroyed by the wind. We estimate its
validity range to $2.5<\xi_{max}<4.2$ and confirm this in simulations with the
SPH Code GADGET-3. The efficiency to trigger a gravitational collapse strongly
decreases for $\xi_{max}<2.5$ since in this case destruction and acceleration
of the whole sphere begin to dominate. We were unable to trigger a collapse for
$\xi_{max}<2$, which leads to the conclusion that a stellar wind can move the
smallest unstable stellar mass to $0.5\,\mathrm{M_\odot}$ and destabilizing
even smaller cores would require an external pressure larger than
$10^5k_B\,\mathrm{K\,cm^{-3}}$. For $\xi_{max}>4.2$ the expected wind strength
according to our criterion is small enough so that the compression is slower
than the sound speed of the BES and sound waves can be triggered. In this case
our criterion underestimates somewhat the onset of collapse and detailed
numerical analyses are required.


  We show that a $2k$-current $T$ on a complex manifold is a real holomorphic
$k$-chain if and only if $T$ is locally real rectifiable, $d$-closed and has
$\mathcal{H}^{2k}$-locally finite support. This result is applied to study
homology classes represented by algebraic cycles.


  Our series of articles is devoted to high-precision molecular dynamics
simulation of mixed actinide-oxide (MOX) fuel in the approximation of rigid
ions and pair interactions (RIPI) using high-performance graphics processors
(GPU). In this article we study self-diffusion mechanisms of oxygen anions in
uranium dioxide (UO2) with the ten recent and widely used sets of interatomic
pair potentials (SPP) under periodic (PBC) and isolated (IBC) boundary
conditions. Wide range of measured diffusion coefficients (from 10^-3 cm^2/s at
melting point down to 10^-12 cm^2/s at 1400 K) made possible a direct
comparison (without extrapolation) of the simulation results with the
experimental data, which have been known only at low temperatures (T < 1500 K).
A highly detailed (with the temperature step of 1 K) calculation of the
diffusion coefficient allowed us to plot temperature dependences of the
diffusion activation energy and its derivative, both of which show a wide
(~1000 K) superionic transition region confirming the broad lambda-peaks of
heat capacity obtained by us earlier. It is shown that regardless of SPP the
anion self-diffusion in model crystals without surface or artificially embedded
defects goes on via exchange mechanism, rather than interstitial or vacancy
mechanisms suggested by the previous works. The activation energy of exchange
diffusion turned out to coincide with the anti-Frenkel defect formation energy
calculated by the lattice statics.


  In this correspondence, first-tier indirect (direct) discernible
constellation expansions are defined for generalized orthogonal designs. The
expanded signal constellation, leading to so-called super-orthogonal codes,
allows the achievement of coding gains in addition to diversity gains enabled
by orthogonal designs. Conditions that allow the shape of an expanded
multidimensional constellation to be preserved at the channel output, on an
instantaneous basis, are derived. It is further shown that, for such
constellations, the channel alters neither the relative distances nor the
angles between signal points in the expanded signal constellation.


  We study the electromagnetic Helmholtz equation \notag (\nabla +
ib(x))^{2}u(x) + n(x)u(x) = f(x), \quad x\in\Rd with the magnetic vector
potential $b(x)$ and $n(x)$ a variable index of refraction that does not
necessarily converge to a constant at infinity, but can have an angular
dependency like $n(x) \to n_{\infty}(\frac{x}{|x|})$ as $|x|\to\infty$. We
prove an explicit Sommerfeld radiation condition \notag \int_{\Rd} |\D u -
in_{\infty}^{1/2}\frac{x}{|x|}u|^{2} \frac{dx}{1+|x)} < + \infty for solutions
obtained from the limiting absorption principle and we also give a new energy
estimate \notag \int_{\Rd}|
\nabla_{\omega}n_{\infty}(\frac{x}{|x|})|^{2}\frac{|u|^{2}}{1+|x|} dx <
+\infty, which explains the main physical effect of the angular dependence of
$n$ at infinity and deduces that the energy concentrates in the directions
given by the critical points of the potential.


  We discuss the states which contribute in the thermodynamic limit of the
mirror theory, the latter is obtained from the light-cone gauge-fixed string
theory in the AdS_5 x S^5 background by the double-Wick rotation. We analyze
the Bethe-Yang equations for the mirror theory and formulate the string
hypothesis. We show that in the thermodynamic limit solutions of the Bethe-Yang
equations arrange themselves into Bethe string configurations similar to the
ones appearing in the Hubbard model. We also derive a set of equations
describing the bound states and the Bethe string configurations of the mirror
theory.


  Dependence on the parameter is continuous when perturbations of the parameter
preserves strict preference for one alternative over another. We characterise
this property via a utility function over alternatives that depends
continuously on the parameter. The class of parameter spaces where such a
representation is guaranteed to exist is also identified. When the parameter is
the type or belief of a player, these results have implications for Bayesian
and psychological games. When alternatives are discrete, the representation is
jointly continuous and an extension of Berge's theorem of the maximum yields a
continuous value function. We apply this result to generalise a standard
consumer choice problem where parameters are price-wealth vectors. When the
parameter space is lexicographically ordered, a novel application to
reference-dependent preferences is possible.


  In large-scale domain classification, an utterance can be handled by multiple
domains with overlapped capabilities. However, only a limited number of
ground-truth domains are provided for each training utterance in practice while
knowing as many as correct target labels is helpful for improving the model
performance. In this paper, given one ground-truth domain for each training
utterance, we regard domains consistently predicted with the highest
confidences as additional pseudo labels for the training. In order to reduce
prediction errors due to incorrect pseudo labels, we leverage utterances with
negative system responses to decrease the confidences of the incorrectly
predicted domains. Evaluating on user utterances from an intelligent
conversational system, we show that the proposed approach significantly
improves the performance of domain classification with hypothesis reranking.


  Large Language Models (LLMs) have been demonstrated to generate illegal or
unethical responses, particularly when subjected to "jailbreak." Research on
jailbreak has highlighted the safety issues of LLMs. However, prior studies
have predominantly focused on single-turn dialogue, ignoring the potential
complexities and risks presented by multi-turn dialogue, a crucial mode through
which humans derive information from LLMs. In this paper, we argue that humans
could exploit multi-turn dialogue to induce LLMs into generating harmful
information. LLMs may not intend to reject cautionary or borderline unsafe
queries, even if each turn is closely served for one malicious purpose in a
multi-turn dialogue. Therefore, by decomposing an unsafe query into several
sub-queries for multi-turn dialogue, we induced LLMs to answer harmful
sub-questions incrementally, culminating in an overall harmful response. Our
experiments, conducted across a wide range of LLMs, indicate current
inadequacies in the safety mechanisms of LLMs in multi-turn dialogue. Our
findings expose vulnerabilities of LLMs in complex scenarios involving
multi-turn dialogue, presenting new challenges for the safety of LLMs.


  This paper introduces an efficient algorithm for persistence diagram
computation, given an input piecewise linear scalar field $f$ defined on a
$d$-dimensional simplicial complex $K$, with $d \leq 3$. Our work revisits the
seminal algorithm "PairSimplices" [31], [103] with discrete Morse theory (DMT)
[34], [80], which greatly reduces the number of input simplices to consider.
Further, we also extend to DMT and accelerate the stratification strategy
described in "PairSimplices" for the fast computation of the $0^{th}$ and $(d -
1)^{th}$ diagrams, noted $D_0(f)$ and $D_{d-1}(f)$. Minima-saddle persistence
pairs ($D_0(f)$) and saddle-maximum persistence pairs ($D_{d-1}(f)$) are
efficiently computed by processing, with a Union-Find, the unstable sets of
$1$-saddles and the stable sets of $(d - 1)$-saddles. This fast pre-computation
for the dimensions $0$ and $(d - 1)$ enables an aggressive specialization of
[4] to the 3D case, which results in a drastic reduction of the number of input
simplices for the computation of $D_1(f)$, the intermediate layer of the
sandwich. Finally, we document several performance improvements via
shared-memory parallelism. We provide an open-source implementation of our
algorithm for reproducibility purposes. We also contribute a reproducible
benchmark package, which exploits three-dimensional data from a public
repository and compares our algorithm to a variety of publicly available
implementations. Extensive experiments indicate that our algorithm improves by
two orders of magnitude the time performance of the seminal "PairSimplices"
algorithm it extends. Moreover, it also improves memory footprint and time
performance over a selection of 14 competing approaches, with a substantial
gain over the fastest available approaches, while producing a strictly
identical output.


  Recent studies have demonstrated the diversity in type Ia supernovae (SNe Ia)
at early times and highlighted a need for a better understanding of the
explosion physics as manifested by observations soon after explosion. To this
end, we present a Monte Carlo code designed to model the light curves of
radioactively driven, hydrogen-free transients from explosion to approximately
maximum light. In this initial study, we have used a parametrised description
of the ejecta in SNe Ia, and performed a parameter study of the effects of the
$^{56}$Ni distribution on the observed colours and light curves for a fixed
$^{56}$Ni mass of 0.6 $M_\odot$. For a given density profile, we find that
models with $^{56}$Ni extending throughout the entirety of the ejecta are
typically brighter and bluer shortly after explosion. Additionally, the shape
of the density profile itself also plays an important role in determining the
shape, rise time, and colours of observed light curves. We find that the
multi-band light curves of at least one SNe Ia (SN 2009ig) are inconsistent
with less extended $^{56}$Ni distributions, but show good agreement with models
that incorporate $^{56}$Ni throughout the entire ejecta. We further demonstrate
that comparisons with full $UVOIR$ colour light curves are powerful tools in
discriminating various $^{56}$Ni distributions, and hence explosion models.


  Elastic turbulence is a chaotic flow state observed in dilute polymer
solutions in the absence of inertia. It was discovered experimentally in
circular geometries and has long been thought to require a finite amplitude
perturbation in parallel flows. Here we demonstrate, within the commonly-used
Oldroyd-B and FENE-P models, that a self-sustaining chaotic state can be
initiated via a linear instability in a simple inertialess shear flow caused by
the presence of small but non-zero diffusivity of the polymer stress. Numerical
simulations show that the instability leads to a three-dimensional
selfsustaining chaotic state, which we believe is the first reported in a
wall-bounded, parallel, inertialess viscoelastic flow.


  Decomposition of the solvable Lie algebras of maximal supergravities in D=4,
5 and 6 indicates, at least at the geometrical level, the existence of an
N=(4,2) chiral supergravity theory in D=6 dimensions. This theory, with 24
supercharges, reduces to the known N=6 supergravity after a toroidal
compactification to D=5 and D=4. Evidence for this theory was given long ago by
B. Julia. We show that this theory suffers from a gravitational anomaly equal
to 4/7 of the pure N=(4,0) supergravity anomaly. However, unlike the latter,
the absence of N=(4,2) matter to cancel the anomaly presumably makes this
theory inconsistent. We discuss the obstruction in defining this theory in D=6,
starting from an N=6 five-dimensional string model in the decompactification
limit. The set of massless states necessary for the anomaly cancellation
appears in this limit; as a result the N=(4,2) supergravity in D=6 is extended
to N=(4,4) maximal supergravity theory.


  In this paper, we study matrix functions of bounded type from the viewpoint
of describing an interplay between function theory and operator theory. \ We
first establish a criterion on the coprime-ness of two singular inner functions
and obtain several properties of the Douglas-Shapiro-Shields factorizations of
matrix functions of bounded type. \ We propose a new notion of tensored-scalar
singularity, and then answer questions on Hankel operators with matrix-valued
bounded type symbols. \ We also examine an interpolation problem related to a
certain functional equation on matrix functions of bounded type; this can be
seen as an extension of the classical Hermite-Fej\' er Interpolation Problem
for matrix rational functions. \ We then extend the $H^\infty$-functional
calculus to an $\overline{H^\infty}+H^\infty$-functional calculus for the
compressions of the shift. \ Next, we consider the subnormality of Toeplitz
operators with matrix-valued bounded type symbols and, in particular, the
matrix-valued version of Halmos's Problem 5; we then establish a matrix-valued
version of Abrahamse's Theorem. \ We also solve a subnormal Toeplitz completion
problem of $2\times 2$ partial block Toeplitz matrices. \ Further, we establish
a characterization of hyponormal Toeplitz pairs with matrix-valued bounded type
symbols, and then derive rank formulae for the self-commutators of hyponormal
Toeplitz pairs.


  Neutron diffraction measurement on the spin glass double perovskite
Sr$_2$FeCoO$_6$ reveals site disorder as well as Co$^{3+}$ intermediate spin
state. In addition, multiple valence states of Fe and Co are confirmed through
M\"{o}ssbauer and X-ray photoelectron spectroscopy. The structural disorder and
multiple valence lead to competing ferromagnetic and antiferromagnetic
interactions and subsequently to a spin glass state, which is reflected in the
form of an additional $T$-linear contribution at low temperatures in specific
heat. A clear evidence of Jahn-Teller distortion at the Co$^{3+}$-O$_6$ complex
is observed and incorporating the physics of Jahn-Teller effect, the presence
of localized magnetic moment is shown. A large, negative and anomalous
magnetoresistance of $\approx$ 63% at 14K in 12T applied field is observed for
Sr$_2$FeCoO$_6$. The observed magnetoresistance could be explained by applying
a semi-empirical fit consisting of a negative and a positive contribution and
show that the negative magnetoresistance is due to spin scattering of carriers
by localized magnetic moments in the spin glass phase.


  Unconditional and conditional statistics is used for studying the histograms
of magnetic field multi-scale fluctuations in the solar wind near the solar
cycle minimum in 2008. The unconditional statistics involves the magnetic data
during the whole year 2008. The conditional statistics involves the magnetic
field time series splitted into concatenated subsets of data according to a
threshold in dynamic pressure. The threshold separates fast stream leading edge
compressional and trailing edge uncompressional fluctuations. The histograms
obtained from these data sets are associated with both large-scale (B) and
small-scale ({\delta}B) magnetic fluctuations, the latter corresponding to
time-delayed differences. It is shown here that, by keeping flexibility but
avoiding the unnecessary redundancy in modeling, the histograms can be
effectively described by a limited set of theoretical probability distribution
functions (PDFs), such as the normal, log-normal, kappa and logkappa functions.
In a statistical sense the model PDFs correspond to additive and multiplicative
processes exhibiting correlations. It is demonstrated here that the skewed
small-scale histograms inherent in turbulent cascades are better described by
the skewed log-kappa than by the symmetric kappa model. Nevertheless, the
observed skewness is rather small, resulting in potential difficulties of
estimation of the third-order moments. This paper also investigates the
dependence of the statistical convergence of PDF model parameters, goodness of
fit and skewness on the data sample size. It is shown that the minimum lengths
of data intervals required for the robust estimation of parameters is scale,
process and model dependent.


  Machine learning (ML) models can memorize training datasets. As a result,
training ML models over private datasets can lead to the violation of
individuals' privacy. Differential privacy (DP) is a rigorous privacy notion to
preserve the privacy of underlying training datasets. Yet, training ML models
in a DP framework usually degrades the accuracy of ML models. This paper aims
to boost the accuracy of a DP logistic regression (LR) via a pre-training
module. In more detail, we initially pre-train our LR model on a public
training dataset that there is no privacy concern about it. Then, we fine-tune
our DP-LR model with the private dataset. In the numerical results, we show
that adding a pre-training module significantly improves the accuracy of the
DP-LR model.


  We perform a global analysis of curved Friedmann-Robertson-Walker cosmologies
in the presence of a viscous fluid. The fluid's bulk viscosity is governed by a
first order theory recently proposed in [M. M. Disconzi, T. W. Kephart, and R.
J. Scherrer, Phys. Rev. D 91, 043532 (2015)], and the analysis is carried out
in a compactified parameter space with dimensionless coordinates. We provide
stability properties, cosmological interpretation and thermodynamic features of
the critical points.


  Classical r-matrices with carriers g_c containing the Borel subalgebra b(+,g)
of simple Lie algebra g are studied. Using the graphycal presentation of the
dual Lie algebra g#(r) we show that such solutions of the CYBE always exist. To
obtain the explicit form of these r-matrices we find the dual coordinates in
which the adjoint action of g_c can be reduced. This gives us the detailed
structure of the Jordanian r-matrices that are the candidates for enlarging the
initial full chain r-matrix. We search the desired solution in the factorized
form. This leads to the unique transformation: the initial chain is to be
substituted by a special kind of peripheric r-matrice. To illustrate the method
we consider the case of g=sl(11) in full details.


  We apply the multi-particle fields model to calculate the differential
cross-section d{\sigma}/dt of elastic proton-proton scattering. This problem
includes the calculation of multidimensional integrals arising from the loop
Feynman diagrams. We demonstrated how these integrals can be reduced with
Laplace's method to one- and two-dimensional integrals which can be calculated
numerically. The obtained result qualitatively describe the minimum in
differential cross-section dependency d{\sigma}/dt(t).


  We report on Raman sideband cooling of ${^{25}\text{Mg}^+}$ to
sympathetically cool the secular modes of motion in a
$^{25}\text{Mg}^+$-$^{27}\!\text{Al}^+$ two-ion pair to near the
three-dimensional (3D) ground state. The evolution of the Fock-state
distribution during the cooling process is studied using a rate-equation
simulation, and various heating sources that limit the efficiency of 3D
sideband cooling in our system are discussed. We characterize the residual
energy and heating rates of all of the secular modes of motion and estimate a
secular motion time-dilation shift of ${-(1.9 \pm 0.1)\times 10^{-18}}$ for an
${^{27}\text{Al}^+}$ clock at a typical clock probe duration of $150$ ms. This
is a 50-fold reduction in the secular motion time-dilation shift uncertainty in
comparison with previous ${^{27}\text{Al}^+}$ clocks.


  We reported the optical observations of GRB 121011A by 0.8-m TNT telescope at
Xinglong observatory, China. The light curve of optical afterglow shows a
smooth and featureless bump during the epoch of $\sim$130 sec and $\sim$5000
sec with a rising index of $1.57\pm0.28$ before the break time of $539\pm44$
sec, and a decaying index of about $1.29\pm0.07$ up to the end of our
observations. Meanwhile, the X-ray light curve decays in a single power-law
with a slop of about $1.51\pm0.03$ observed by $XRT$ onboard ${\rm} Swift$ from
100 sec to about 10000 sec after the burst trigger. The featureless optical
light curve could be understood as an onset process under the external-shock
model. The typical frequency has been below or near the optical one before the
deceleration time, and the cooling frequency is located between the optical and
X-ray wavelengths. The external medium density has a transition from a mixed
stage of ISM and wind-type medium before the peak time to the ISM at the later
phase. The joint-analysis of X-ray and optical light curves shows that the
emission from both frequencies are consistent with the prediction of the
standard afterglow model without any energy injections, indicating that the
central engine has stopped its activity and does not restart anymore after the
prompt phase.


  We report a new, cleavable, strong-topological-metal, Zr2Te2P, which has the
same tetradymite-type crystal structure as the topological insulator Bi2Te2Se.
Instead of being a semiconductor, however, Zr2Te2P is metallic with a pseudogap
between 0.2 and 0.7 eV above the fermi energy (EF). Inside this pseudogap, two
Dirac dispersions are predicted: one is a surface-originated Dirac cone
protected by time-reversal symmetry (TRS), while the other is a bulk-originated
and slightly gapped Dirac cone with a largely linear dispersion over a 2 eV
energy range. A third surface TRS-protected Dirac cone is predicted, and
observed using ARPES, making Zr2Te2P the first system to realize TRS-protected
Dirac cones at M points. The high anisotropy of this Dirac cone is similar to
the one in the hypothetical Dirac semimetal BiO2. We propose that if EF can be
tuned into the pseudogap where the Dirac dispersions exist, it may be possible
to observe ultrahigh carrier mobility and large magnetoresistance in this
material.


  A large number of $(\alpha,p)$ and $(\alpha,n)$ reactions are known to play a
fundamental role in nuclear astrophysics. This work presents a novel technique
to study these reactions with the active target system MUSIC whose segmented
anode allows the investigation of a large energy range of the excitation
function with a single beam energy. In order to verify the method, we performed
a direct measurements of the previously measured reactions
$^{17}$O$(\alpha,n)^{20}$Ne, $^{23}$Na$(\alpha,p)^{26}$Mg, and
$^{23}$Na$(\alpha,n)^{26}$Al. These reactions were investigated in inverse
kinematics using $^{4}$He gas in the detector to study the excitation function
in the range of about 2 to 6 MeV in the center of mass. We found good agreement
between the cross sections of the $^{17}$O$(\alpha,n)^{20}$Ne reaction measured
in this work and previous measurements. Furthermore we have successfully
performed a simultaneous measurement of the $^{23}$Na$(\alpha,p)^{26}$Mg and
$^{23}$Na$(\alpha,n)^{26}$Al reactions.


  Unidirectional light emission from planar photonic structures is highly
advantageous for a wide range of optoelectronic applications. Recently, it has
been demonstrated that unidirectional guided resonances (UGRs) can be realized
by utilizing topological polarization singularities in momentum space. However,
the practical application of these topological unidirectional emitters has been
limited due to their intricate geometric configurations, requiring special
efforts with high-cost fabrication processes. In this study, we show that
unidirectional light emission can be achieved in conventional one-dimensional
zero-contrast gratings (ZCGs), which can be easily fabricated using current
nanofabrication technologies. In ZCGs, the interband coupling between even-like
and odd-like waveguide modes leads to the formation of quasi-UGRs,
characterized by significantly higher decay rates in either the upward or
downward direction compared to the opposite direction. We demonstrate that
these quasi-UGRs evolve into genuine UGRs with an gradual increase in grating
thickness. Moreover, the emission direction of UGRs can be selectively steered
either upward or downward by adjusting the lattice parameters. In addition to
quasi-UGRs and UGRs, our study also reveals additional topological phenomena in
ZCGs, including exceptional points and quasi-BICs.


  We discuss the state of the assembly of the Hubble Sequence in the mix of
bright galaxies at redshift 1.4< z \le 2.5 with a large sample of 1,671
galaxies down to H_{AB}~26, selected from the HST/ACS and WFC3 images of the
GOODS--South field obtained as part of the GOODS and CANDELS observations. We
investigate the relationship between the star formation properties and
morphology using various parametric diagnostics, such as the Sersic light
profile, Gini (G), M_{20}, Concentration (C), Asymmetry (A) and multiplicity
parameters. Our sample clearly separates into massive, red and passive galaxies
versus less massive, blue and star forming ones, and this dichotomy correlates
very well with the galaxies' morphological properties. Star--forming galaxies
show a broad variety of morphological features, including clumpy structures and
bulges mixed with faint low surface brightness features, generally
characterized by disky-type light profiles. Passively evolving galaxies, on the
other hand, very often have compact light distribution and morphology typical
of today's spheroidal systems. We also find that artificially redshifted local
galaxies have a similar distribution with z~2galaxies in a G-M_{20} plane.
Visual inspection between the rest-frame optical and UV images show that there
is a generally weak morphological k-correction for galaxies at z~2, but the
comparison with non-parametric measures show that galaxies in the rest-frame UV
are somewhat clumpier than rest-frame optical. Similar general trends are
observed in the local universe among massive galaxies, suggesting that the
backbone of the Hubble sequence was already in place at z~2.


  I propose a sharp form of Thorne's hoop conjecture which relates Birkhoff's
invariant $\beta$ for an outermost apparent horizon to its $ADM$ mass, $ \beta
\le 4 \pi M_{ADM}$. I prove the conjecture in the case of collapsing null
shells and provide further evidence from exact rotating black hole solutions.
Since $\beta$ is bounded below by the length $l$ of the shortest non-trivial
geodesic lying in the apparent horizon, the conjecture implies $l \le 4 \pi
M_{ADM}$. The Penrose conjecture, $\sqrt{\pi A} \le 4 \pi M_{ADM}$, and Pu's
theorem imply this latter consequence for horizons admitting an antipodal
isometry. Quite generally, Penrose's inequality and Berger's isembolic
inequality, $\sqrt{\pi A} \ge {2\over\sqrt\pi} i$, where $i$ is the injectivity
radius, imply $ 4c \le 2 i \le 4 \pi M_{ADM}$, where $c$ is the convexity
radius.


  In this paper, we classify three-locally-symmetric spaces for a connected,
compact and simple Lie group. Furthermore, we give the classification of
invariant Einstein metrics on these spaces.


  We construct a Beurling generalized number system satisfying the Riemann
hypothesis and whose integer counting function displays extremal oscillation in
the following sense. The prime counting function of this number system
satisfies $\pi(x)= \operatorname*{Li} (x)+ O(\sqrt{x})$, while its integer
counting function satisfies the oscillation estimate $N(x) = \rho x +
\Omega_{\pm}\bigl(x\exp(-c\sqrt{\log x\log\log x})\bigr)$ for some $c>0$, where
$\rho>0$ is its asymptotic density. The construction is inspired by a classical
example of H. Bohr for optimality of the convexity bound for Dirichlet series,
and combines saddle-point analysis with the Diamond-Montgomery-Vorhauer
probabilistic method via random prime number system approximations.


  In general relativity, nonsingular black holes contain (at least) a Cauchy
horizon, a null hypersurface beyond which determinism breaks down. Even though
the strong cosmic censorship conjecture establishes the impossibility of
extending spacetime beyond this region, in this paper we investigate how far we
can go, without invoking this conjecture, in the building of a physically
reasonable black hole without a Cauchy hypersurface. Following this reasoning,
we find a black hole lacking of Cauchy horizon, asymptotically flat and
satisfying either the strong or dominant energy condition. The above is
possible by demanding integrable singularity for the Ricci scalar, whose direct
consequence is the appearance of finite tidal forces. We show that the
spacetime inside the event horizon represents a warped anti-de Sitter
spacetime, which might be interpreted in terms of a finite superposition of
configurations.


  Charge-coupled device (CCD), along with the complementary
metal-oxide-semiconductor (CMOS), is one of the major imaging technologies.
Traditional CCDs rely on the charge transfer between potential wells, which
gives them advantages of simple pixel structure, high sensitivity, and low
noise. However, the serial transfer requires fabrication incompatible with
CMOS, and leads to slower, more complex, and less flexible readout than random
access. Here, we report a new-concept CCD called field-effect CCD (FE-CCD),
which is based on the capacitive "coupling" between the semiconductor substrate
and the 2D material. The strong field effect of the 2D material enables
amplification, and non-destructive readout of the integrated charges in one
pixel without transfer. We demonstrated the broadband response of our CCD (up
to 1870 nm) and the successful integration of 2D hetero-structures for reducing
the power consumption. The demonstrated FE-CCD provides a valuable strategy for
versatile 2D materials to be monolithically integrated into the semiconductor
imaging technology.


  The pre-coloring extension problem consists, given a graph $G$ and a subset
of nodes to which some colors are already assigned, in finding a coloring of
$G$ with the minimum number of colors which respects the pre-coloring
assignment. This can be reduced to the usual coloring problem on a certain
contracted graph. We prove that pre-coloring extension is polynomial for
complements of Meyniel graphs. We answer a question of Hujter and Tuza by
showing that ``PrExt perfect'' graphs are exactly the co-Meyniel graphs, which
also generalizes results of Hujter and Tuza and of Hertz. Moreover we show
that, given a co-Meyniel graph, the corresponding contracted graph belongs to a
restricted class of perfect graphs (``co-Artemis'' graphs, which are
``co-perfectly contractile'' graphs), whose perfectness is easier to establish
than the strong perfect graph theorem. However, the polynomiality of our
algorithm still depends on the ellipsoid method for coloring perfect graphs.


  We used x-ray absorption spectroscopy to study the orbital symmetry and the
energy band splitting of (111) LaAlO${_3}$/SrTiO${_3}$ and
LaAlO${_3}$/EuTiO${_3}$/SrTiO${_3}$ heterostructures, hosting a quasi
two-dimensional electron system (q2DES), and of a Ti-terminated (111)
SrTiO${_3}$ single crystal, also known to form a q2DES at its surface. We
demonstrate that the bulk tetragonal Ti-3d D${_4}$${_h}$ crystal field is
turned into trigonal D${_3}$${_d}$ crystal field in all cases. The symmetry
adapted a${_1}$${_g}$ and e${^\pi_g}$ orbitals are non-degenerate in energy and
their splitting, \Delta, is positive at the bare STO surface but negative in
the heterostructures, where the a${_1}$${_g}$ orbital is lowest in energy.
These results demonstrate that the interfacial symmetry breaking induced by
epitaxial engineering of oxide interfaces has a dramatic effect on their
electronic properties, and it can be used to manipulate the ground state of the
q2DES.


  We discuss the properties of three upsilon transforms, which are related to
the class of $p$-tempered $\alpha$-stable ($TS^p_\alpha$) distributions. In
particular, we characterize their domains and show how they can be represented
as compositions of each other. Further, we show that if
$-\infty<\beta<\alpha<2$ and $0<q<p<\infty$ then they can be used to transform
the L\'evy measures of $TS^p_\beta$ distributions into those of $TS^q_\alpha$.


  We examine carefully bottomonia hadroproduction in proton colliders,
especially focusing on the LHC, as a way of probing the gluon density in
protons. To this end we develop some previous work, getting quantitative
predictions and concluding that our proposal can be useful to perform
consistency checks of the parameterization sets of different parton
distribution functions.


  While a large body of research has formally identified apolipoprotein E
(APOE) as a major genetic risk marker for Alzheimer disease, accumulating
evidence supports the notion that other risk markers may exist. The traditional
Alzheimer-specific signature analysis methods, however, have not been able to
make full use of rich protein expression data, especially the interaction
between attributes. This paper develops a novel feature selection method to
identify pathogenic factors of Alzheimer disease using the proteomic and
clinical data. This approach has taken the weights of network nodes as the
importance order of signaling protein expression values. After generating and
evaluating the candidate subset, the method helps to select an optimal subset
of proteins that achieved an accuracy greater than 90%, which is superior to
traditional machine learning methods for clinical Alzheimer disease diagnosis.
Besides identifying a proteomic risk marker and further reinforce the link
between metabolic risk factors and Alzheimer disease, this paper also suggests
that apidonectin-linked pathways are a possible therapeutic drug target.


  In this paper, we consider several possible ways to set up Heterogeneous
Multiscale Methods for the Landau-Lifshitz equation with a highly oscillatory
diffusion coefficient, which can be seen as a means to modeling rapidly varying
ferromagnetic materials. We then prove estimates for the errors introduced when
approximating the relevant quantity in each of the models given a periodic
problem, using averaging in time and space of the solution to a corresponding
micro problem. In our setup, the Landau-Lifshitz equation with highly
oscillatory coefficient is chosen as the micro problem for all models. We then
show that the averaging errors only depend on $\varepsilon$, the size of the
microscopic oscillations, as well as the size of the averaging domain in time
and space and the choice of averaging kernels.


  We present the result of IR observations in the K band of 39 bright AeBe
stars in the northern hemisphere. Using the shift-and-add technique, we were
able to detect nearby objects as close as 0.4'' from the primary star. We found
9 stars that have one or more companions. Adjusting for completeness, we
compute that the AeBe star binary rate is 85%. The binary rate of AeBe stars is
therefore greater than that of near solar type MS stars (57%) and similar to
that found in T Tauri stars (80%).


  We examine the gauge generating nature of the translational subgroup of
Wigner's little group for the case of massless tensor gauge theories and show
that the gauge transformations generated by the translational group is only a
subset of the complete set of gauge transformations. We also show that, just
like the case of topologically massive gauge theories, translational groups act
as generators of gauge transformations in gauge theories obtained by extending
massive gauge noninvariant theories by a Stuckelberg mechanism. The
representations of the translational groups that generate gauge transformations
in such Stuckelberg extended theories can be obtained by the method of
dimensional descent. We illustrate these with the examples of Stuckelberg
extended first class versions of Proca, Einstein-Pauli-Fierz and massive
Kalb-Ramond theories in 3+1 dimensions. A detailed analysis of the partial
gauge generation in massive and massless 2nd rank symmetric gauge theories is
provided. The gauge transformations generated by translational group in 2-form
gauge theories are shown to explicitly manifest the reducibility of gauge
transformations in these theories.


  A finite number of rational functions are compatible if they satisfy the
compatibility conditions of a first-order linear functional system involving
differential, shift and q-shift operators. We present a theorem that describes
the structure of compatible rational functions. The theorem enables us to
decompose a solution of such a system as a product of a rational function,
several symbolic powers, a hyperexponential function, a hypergeometric term,
and a q-hypergeometric term. We outline an algorithm for computing this
product, and present an application.


  The interlace polynomial q was introduced by Arratia, Bollobas, and Sorkin.
It encodes many properties of the orbit of a graph under edge local
complementation (ELC). The interlace polynomial Q, introduced by Aigner and van
der Holst, similarly contains information about the orbit of a graph under
local complementation (LC). We have previously classified LC and ELC orbits,
and now give an enumeration of the corresponding interlace polynomials of all
graphs of order up to 12. An enumeration of all circle graphs of order up to 12
is also given. We show that there exist graphs of all orders greater than 9
with interlace polynomials q whose coefficient sequences are non-unimodal,
thereby disproving a conjecture by Arratia et al. We have verified that for
graphs of order up to 12, all polynomials Q have unimodal coefficients. It has
been shown that LC and ELC orbits of graphs correspond to equivalence classes
of certain error-correcting codes and quantum states. We show that the
properties of these codes and quantum states are related to properties of the
associated interlace polynomials.


  Let $G$ be a nilpotent group and $a\in G$. Let $a^G=\{g^{-1}ag\mid g\in G\}$
be the conjugacy class of $a$ in $G$. Assume that $a^G$ and $b^G$ are conjugacy
classes of $G$ with the property that $|a^G|=|b^G|=p$, where $p$ is an odd
prime number.
  Set $a^G b^G=\{xy\mid x\in a^G, y\in b^G\}$. Then either $a^G b^G=(ab)^G$ or
$a^G b^G$ is the union of at least $\frac{p+1}{2}$ distinct conjugacy classes.
As an application of the previous result, given any nilpotent group $G$ and any
conjugacy class $a^G$ of size $p$, we describe the square $a^G a^G$ of $a^G$ in
terms of conjugacy classes of $G$.


  Integrating sphere (IS) techniques combined with an inverse adding doubling
(IAD) algorithm have been widely used for determination of optical properties
of ex vivo tissues. Semi-infinite samples are required in such cases. The aim
of this study is to develop a methodology for calculating the optical
absorption and reduced scattering of biological tissues of small size from IS
measurements at 400-1800 nm. We propose a two-stage IAD algorithm to mitigate
profound cross-talk effects in the estimation of the reduced scattering in the
case of very high absorption. We developed a small sample adaptor kit to allow
IS measurements of samples with small sizes using a commercial
spectrophotometer. Results showed that: The two-stage IAD substantially
eliminated the cross-talks in the reduced scattering spectra, thus rectifying
absorption accordingly; and the small sized sample measurements led to
systematically overestimated absorption values while the spectrum shape well
preserved as compared to the normal port size measurements.


  The aim of the MuCap experiment is a 1% measurement of the singlet capture
rate Lambda_S for the basic electro-weak reaction mu + p -> n + nu_mu. This
observable is sensitive to the weak form-factors of the nucleon, in particular
to the induced pseudoscalar coupling constant g_P. It will provide a rigorous
test of theoretical predictions based on the Standard Model and effective
theories of QCD. The present method is based on high precision lifetime
measurements of mu^- in hydrogen gas and the comparison with the free mu^+
lifetime. The mu^- experiment will be performed in ultra-clean,
deuterium-depleted H_2 gas at 10 bar. Low density compared to liquid H_2 is
chosen to avoid uncertainties due to ppmu formation. A time projection chamber
acts as a pure hydrogen active target. It defines the muon stop position in 3-D
and detects rare background reactions. Decay electrons are tracked in
cylindrical wire-chambers and a scintillator array covering 75% of 4 pi.


  Deep learning-based person Re-IDentification (ReID) often requires a large
amount of training data to achieve good performance. Thus it appears that
collecting more training data from diverse environments tends to improve the
ReID performance. This paper re-examines this common belief and makes a somehow
surprising observation: using more samples, i.e., training with samples from
multiple datasets, does not necessarily lead to better performance by using the
popular ReID models. In some cases, training with more samples may even hurt
the performance of the evaluation is carried out in one of those datasets. We
postulate that this phenomenon is due to the incapability of the standard
network in adapting to diverse environments. To overcome this issue, we propose
an approach called Domain-Camera-Sample Dynamic network (DCSD) whose parameters
can be adaptive to various factors. Specifically, we consider the internal
domain-related factor that can be identified from the input features, and
external domain-related factors, such as domain information or camera
information. Our discovery is that training with such an adaptive model can
better benefit from more training samples. Experimental results show that our
DCSD can greatly boost the performance (up to 12.3%) while joint training in
multiple datasets.


  The focus of present article is to investigate a supply chain inventory model
of deteriorated items along with inspection and stock dependent demand using
green technology to reduce carbon emissions. Products that are decaying have a
high sensitivity to the environment in terms of temperature, carbon emission,
humidity, waste disposal, etc. This study develops a profit maximization model
in the presence of deterioration, preservation, imperfect production,
inspection error, rework, stock and price-dependent demand. Three carbon
emission strategies are proposed to reduce the expenses in different carbon
emissions scenarios. The suggested approach may be used to determine the
optimal production period, preservation investment, and level of green
investment. The solution of the proposed non-linear constraint optimization is
provided by using a penalty method in metaheuristic approaches. In order to
conduct a sensitivity analysis for the essential model parameters, a numerical
example is presented. The results produced by DE and PSO are compared with the
results obtained by Adaptive Neuro-Fuzzy Inference System (ANFIS) technique.


  Consider an independent site percolation model on $\Z^d,\ d\geq 2$, with
parameter $p \in (0,1)$, where there are only nearest neighbor bonds and long
range bonds of length $k$ parallel to some coordinate axis. We show that the
percolation probability is a non-decreasing function of $k$. We also generalize
this result for models whose long range bonds have several lengths.


  Human pose estimation is a fundamental and challenging task in computer
vision. Larger-scale and more accurate keypoint annotations, while helpful for
improving the accuracy of supervised pose estimation, are often expensive and
difficult to obtain. Semi-supervised pose estimation tries to leverage a large
amount of unlabeled data to improve model performance, which can alleviate the
problem of insufficient labeled samples. The latest semi-supervised learning
usually adopts a strong and weak data augmented teacher-student learning
framework to deal with the challenge of "Human postural diversity and its
long-tailed distribution". Appropriate data augmentation method is one of the
key factors affecting the accuracy and generalization of semi-supervised
models. Aiming at the problem that the difference of sample learning is not
considered in the fixed keypoint masking augmentation method, this paper
proposes an adaptive keypoint masking method, which can fully mine the
information in the samples and obtain better estimation performance. In order
to further improve the generalization and robustness of the model, this paper
proposes a dual-branch data augmentation scheme, which can perform Mixup on
samples and features on the basis of adaptive keypoint masking. The
effectiveness of the proposed method is verified on COCO and MPII,
outperforming the state-of-the-art semi-supervised pose estimation by 5.2% and
0.3%, respectively.


  This article provides a completion to theories of information based on
entropy, resolving a longstanding question in its axiomatization as proposed by
Shannon and pursued by Jaynes. We show that Shannon's entropy function has a
complementary dual function which we call "extropy." The entropy and the
extropy of a binary distribution are identical. However, the measure bifurcates
into a pair of distinct measures for any quantity that is not merely an event
indicator. As with entropy, the maximum extropy distribution is also the
uniform distribution, and both measures are invariant with respect to
permutations of their mass functions. However, they behave quite differently in
their assessments of the refinement of a distribution, the axiom which
concerned Shannon and Jaynes. Their duality is specified via the relationship
among the entropies and extropies of course and fine partitions. We also
analyze the extropy function for densities, showing that relative extropy
constitutes a dual to the Kullback-Leibler divergence, widely recognized as the
continuous entropy measure. These results are unified within the general
structure of Bregman divergences. In this context they identify half the $L_2$
metric as the extropic dual to the entropic directed distance. We describe a
statistical application to the scoring of sequential forecast distributions
which provoked the discovery.


  In this work we discuss how the loss of particle-antiparticle identity due to
CPT violation affects the observables in the decay of two neutral
EPR-correlated $B$-mesons. We study this possible new effect in the context of
equal-sign flavour specific decays and we find a considerable modification in
the $\Delta t$-dependence of the equal-sign dilepton charge asymmetry,
$A_{sl}$. Although the more important changes occur right outside the $\Dt$
region that has been up-to-the-date effectively explored, we show that a deeper
experimental research may be able to distinguish a possible existence of this
new CPT violating parameter, $\w$. In any case, using the available data for
$A_{sl}$, we put the first limits on $\w$.


  In this work we consider a two-user and a three-user slotted ALOHA network
with multi-packet reception (MPR) capabilities. The nodes can adapt their
transmission probabilities and their transmission parameters based on the
status of the other nodes. Each user has external bursty arrivals that are
stored in their infinite capacity queues. For the two- and the three-user cases
we obtain the stability region of the system. For the two-user case we provide
the conditions where the stability region is a convex set. We perform a
detailed mathematical analysis in order to study the queueing delay by
formulating two boundary value problems (a Dirichlet and a Riemann-Hilbert
boundary value problem), the solution of which provides the generating function
of the joint stationary probability distribution of the queue size at user
nodes. Furthermore, for the two-user symmetric case with MPR we obtain a lower
and an upper bound for the average delay without explicitly computing the
generating function for the stationary joint queue length distribution. The
bounds as it is seen in the numerical results appear to be tight. Explicit
expressions for the average delay are obtained for the symmetrical model with
capture effect which is a subclass of MPR models. We also provide the optimal
transmission probability in closed form expression that minimizes the average
delay in the symmetric capture case. Finally, we evaluate numerically the
presented theoretical results.


  We present a measurement of the branching fraction and time-dependent CP
violation parameters in B0 --> a_1^+-(1260) pi^-+ decays. The results are
obtained from the final data sample containing 772x10^6 BBbar pairs collected
at the Upsilon(4S) resonance with the Belle detector at the KEKB
asymmetric-energy e^+e^- collider. We also measure an upper limit on the
product branching fraction for a possible decay with the same final state B0
--> a_2^+-(1320) pi^-+. In a time-dependent measurement to extract CP
asymmetries, we find evidence of mixing-induced CP violation in B0 -->
a_1^+-(1260) pi^-+ decays with a 3.1 sigma significance and the rate where the
a_1^+-(1260) does not contain the spectator quark is found to dominate the rate
where it does at the 4.1 sigma level. However, there is no evidence for either
time and flavor integrated direct CP violation or flavor-dependent direct CP
violation.


  While modern parallel computing systems provide high performance resources,
utilizing them to the highest extent requires advanced programming expertise.
Programming for parallel computing systems is much more difficult than
programming for sequential systems. OpenMP is an extension of C++ programming
language that enables to express parallelism using compiler directives. While
OpenMP alleviates parallel programming by reducing the lines of code that the
programmer needs to write, deciding how and when to use these compiler
directives is up to the programmer. Novice programmers may make mistakes that
may lead to performance degradation or unexpected program behavior. Cognitive
computing has shown impressive results in various domains, such as health or
marketing. In this paper, we describe the use of IBM Watson cognitive system
for education of novice parallel programmers. Using the dialogue service of the
IBM Watson we have developed a solution that assists the programmer in avoiding
common OpenMP mistakes. To evaluate our approach we have conducted a survey
with a number of novice parallel programmers at the Linnaeus University, and
obtained encouraging results with respect to usefulness of our approach.


  For soliton cellular automata, we give a uniform description and proofs of
the solitons, the scattering rule of two solitons, and the phase shift using
rigged configurations in a number of special cases. In particular, we prove
these properties for the soliton cellular automata using $B^{r,1}$ when $r$ is
adjacent to $0$ in the Dynkin diagram or there is a Dynkin diagram automorphism
sending $r$ to $0$.


  Dynamic graph visualization attracts researchers' concentration as it
represents time-varying relationships between entities in multiple domains
(e.g., social media analysis, academic cooperation analysis, team sports
analysis). Integrating visual analytic methods is consequential in presenting,
comparing, and reviewing dynamic graphs. Even though dynamic graph
visualization is developed for many years, how to effectively visualize
large-scale and time-intensive dynamic graph data with subtle changes is still
challenging for researchers. To provide an effective analysis method for this
type of dynamic graph data, we propose a snapshot generation algorithm
involving Human-In-Loop to help users divide the dynamic graphs into
multi-granularity and hierarchical snapshots for further analysis. In addition,
we design a visual analysis prototype system (DGSVis) to assist users in
accessing the dynamic graph insights effectively. DGSVis integrates a graphical
operation interface to help users generate snapshots visually and
interactively. It is equipped with the overview and details for visualizing
hierarchical snapshots of the dynamic graph data. To illustrate the usability
and efficiency of our proposed methods for this type of dynamic graph data, we
introduce two case studies based on basketball player networks in a
competition. In addition, we conduct an evaluation and receive exciting
feedback from experienced visualization experts.


  Detecting out-of-distribution (OOD) instances is crucial for NLP models in
practical applications. Although numerous OOD detection methods exist, most of
them are empirical. Backed by theoretical analysis, this paper advocates for
the measurement of the "OOD-ness" of a test case $\boldsymbol{x}$ through the
likelihood ratio between out-distribution $\mathcal P_{\textit{out}}$ and
in-distribution $\mathcal P_{\textit{in}}$. We argue that the state-of-the-art
(SOTA) feature-based OOD detection methods, such as Maha and KNN, are
suboptimal since they only estimate in-distribution density
$p_{\textit{in}}(\boldsymbol{x})$. To address this issue, we propose FLatS, a
principled solution for OOD detection based on likelihood ratio. Moreover, we
demonstrate that FLatS can serve as a general framework capable of enhancing
other OOD detection methods by incorporating out-distribution density
$p_{\textit{out}}(\boldsymbol{x})$ estimation. Experiments show that FLatS
establishes a new SOTA on popular benchmarks. Our code is publicly available at
https://github.com/linhaowei1/FLatS.


  This paper presents a system of differential equations that describes the
spreading of a rumor when it is propagated by different subgroups of spreaders.
The system that is developed is a generalization of the model proposed by Daley
and Kendall. Finally, the system is applied to the exchange rate of the
parallel dollar in Venezuela, where the source data that was used were obtained
from Google Trends.


  There has been significant research dedicated towards computing the crossing
numbers of families of graphs resulting from the Cartesian products of small
graphs with arbitrarily large paths, cycles and stars. For graphs with four or
fewer vertices, these have all been computed, but there are still various gaps
for graphs with five or more vertices. We contribute to this field by
determining the crossing numbers for fifteen such families.


  Gaussian Process (GP) models are a class of flexible non-parametric models
that have rich representational power. By using a Gaussian process with
additive structure, complex responses can be modelled whilst retaining
interpretability. Previous work showed that additive Gaussian process models
require high-dimensional interaction terms. We propose the orthogonal additive
kernel (OAK), which imposes an orthogonality constraint on the additive
functions, enabling an identifiable, low-dimensional representation of the
functional relationship. We connect the OAK kernel to functional ANOVA
decomposition, and show improved convergence rates for sparse computation
methods. With only a small number of additive low-dimensional terms, we
demonstrate the OAK model achieves similar or better predictive performance
compared to black-box models, while retaining interpretability.


  We propose a practical method for $L_0$ norm regularization for neural
networks: pruning the network during training by encouraging weights to become
exactly zero. Such regularization is interesting since (1) it can greatly speed
up training and inference, and (2) it can improve generalization. AIC and BIC,
well-known model selection criteria, are special cases of $L_0$ regularization.
However, since the $L_0$ norm of weights is non-differentiable, we cannot
incorporate it directly as a regularization term in the objective function. We
propose a solution through the inclusion of a collection of non-negative
stochastic gates, which collectively determine which weights to set to zero. We
show that, somewhat surprisingly, for certain distributions over the gates, the
expected $L_0$ norm of the resulting gated weights is differentiable with
respect to the distribution parameters. We further propose the \emph{hard
concrete} distribution for the gates, which is obtained by "stretching" a
binary concrete distribution and then transforming its samples with a
hard-sigmoid. The parameters of the distribution over the gates can then be
jointly optimized with the original network parameters. As a result our method
allows for straightforward and efficient learning of model structures with
stochastic gradient descent and allows for conditional computation in a
principled way. We perform various experiments to demonstrate the effectiveness
of the resulting approach and regularizer.


  In this article, we introduce the fractional maximal operator on the
Hyperbolic space, a non-doubling measure space, and study the weighted
boundedness. Motivated in the weighted boundedness of Hardy-Littlewood maximal
studied by Antezana and Ombrosi in [1], we give conditions for the weak type
and strong type estimate for fractional maximal. Also, we provide examples of
weights for which the fractional maximal operator satisface weak type $(p,q)$
inequality but strong type $(p,q)$ inequality fails.


  This paper introduces and develops the concept of ``ticketing'', through
which atomic broadcasts are orchestrated by nodes in a distributed system. The
paper studies different ticketing regimes that allow parallelism, yet prevent
slow nodes from hampering overall progress. It introduces a hybrid scheme which
combines managed and unmanaged ticketing regimes, striking a balance between
adaptivity and resilience. The performance evaluation demonstrates how managed
and unmanaged ticketing regimes benefit throughput in systems with
heterogeneous resources both in static and dynamic scenarios, with the managed
ticketing regime performing better among the two as it adapts better. Finally,
it demonstrates how using the hybrid ticketing regime performance can enjoy
both the adaptivity of the managed regime and the liveness guarantees of the
unmanaged regime.


  In scale-invariant theories of gravity the Planck mass $M_P$, which appears
due to spontaneous symmetry breaking, can be the only scale at the classical
level. It was argued that the second scale can be generated by a quantum
non-perturbative gravitational effect. The new scale, associated with the Higgs
vacuum expectation value, can be orders of magnitude below $M_P$, leading to
the hierarchy between the Fermi and the Planck scales. We study a theory in
which the non-perturbative effect is sensitive both to the physics at energy
scales as high as $M_P$ and to the low-energy, Standard Model physics. This
makes it possible to constrain the mechanism from experiment. We find that the
crucial ingredients of the mechanism are non-minimal coupling of the scalar
fields to gravity, the approximate Weyl invariance at high energies, and the
metastability of the low-energy vacuum.


  Orbit determination is possible for a chaotic orbit of a dynamical system,
given a finite set of observations, provided the initial conditions are at the
central time. In a simple discrete model, the standard map, we tackle the
problem of chaotic orbit determination when observations extend beyond the
predictability horizon. If the orbit is hyperbolic, a shadowing orbit is
computed by the least squares orbit determination. We test both the convergence
of the orbit determination iterative procedure and the behaviour of the
uncertainties as a function of the maximum number $n$ of map iterations
observed. When the initial conditions belong to a chaotic orbit, the orbit
determination is made impossible by numerical instability beyond a
computability horizon, which can be approximately predicted by a simple
formula. Moreover, the uncertainty of the results is sharply increased if a
dynamical parameter is added to the initial conditions as parameter to be
estimated. The uncertainty of the dynamical parameter decreases like $n^a$ with
$a<0$ but not large (of the order of unity). If only the initial conditions are
estimated, their uncertainty decreases exponentially with $n$. If they belong
to a non-chaotic orbit the computational horizon is much larger, if it exists
at all, and the decrease of the uncertainty is polynomial in all parameters,
like $n^a$ with $a\simeq 1/2$. The Shadowing Lemma does not dictate what the
asymptotic behaviour of the uncertainties should be. These phenomena have
significant implications, which remain to be studied, in practical problems of
orbit determination involving chaos, such as the chaotic rotation state of a
celestial body and a chaotic orbit of a planet-crossing asteroid undergoing
many close approaches.


  The MultiCoNER II task aims to detect complex, ambiguous, and fine-grained
named entities in low-context situations and noisy scenarios like the presence
of spelling mistakes and typos for multiple languages. The task poses
significant challenges due to the scarcity of contextual information, the high
granularity of the entities(up to 33 classes), and the interference of noisy
data. To address these issues, our team {\bf PAI} proposes a universal Named
Entity Recognition (NER) system that integrates external entity information to
improve performance. Specifically, our system retrieves entities with
properties from the knowledge base (i.e. Wikipedia) for a given text, then
concatenates entity information with the input sentence and feeds it into
Transformer-based models. Finally, our system wins 2 first places, 4 second
places, and 1 third place out of 13 tracks. The code is publicly available at
\url{https://github.com/diqiuzhuanzhuan/semeval-2023}.


  X-ray Fluorescence Computed Tomography(XFCT) is a prevalent experimental
technique which is utilized to investigate the spatial distribution of elements
in sample. The sensitivity of L-shell XFCT of some elements is lower than that
of K-shell XFCT. However, the image reconstruction for this technique has much
more problems than that of transmission tomography, one of which is
self-absorption. In the present work, a novel strategy was developed to deal
with such problems. But few researches are concerned on attenuation correction
of L-shell XFCT that are essential to get accurate reconstructed image. We make
use of the known quantities and the unknown elemental concentration of interest
to express the unknown attenuation maps. And then the attenuation maps are
added in the contribution value of the pixel in MLEM reconstruction method.
Results indicate that the relative error is less than 14.1%, which is proved
this method can correct L-shell XFCT very well.


  We find that variations in the UV emissions of cool M-dwarf stars have a
potentially large impact upon atmospheric biosignatures in simulations of
Earth-like exoplanets i.e. planets with Earths development, and biomass and a
molecular nitrogen-oxygen dominated atmosphere. Starting with an assumed
black-body stellar emission for an M7 class dwarf star, the stellar UV
irradiation was increased stepwise and the resulting climate-photochemical
response of the planetary atmosphere was calculated. Results suggest a
Goldilocks effect with respect to the spectral detection of ozone. At weak UV
levels, the ozone column was weak (due to weaker production from the Chapman
mechanism) hence its spectral detection was challenging. At strong UV levels,
ozone formation is stronger but its associated stratospheric heating leads to a
weakening in temperature gradients between the stratosphere and troposphere,
which results in weakened spectral bands. Also, increased UV levels can lead to
enhanced abundances of hydrogen oxides which oppose the ozone formation effect.
At intermediate UV (i.e. with x10 the stellar UV radiative flux of black body
Planck curves corresponding to spectral class M7) the conditions are just right
for spectral detection. Results suggest that the planetary O3 profile is
sensitive to the UV output of the star from about(200-350) nm. We also
investigated the effect of increasing the top-of-atmosphere incoming
Lyman-alpha radiation but this had only a minimal effect on the biosignatures
since it was efficiently absorbed in the uppermost planetary atmospheric layer,
mainly by abundant methane. Earlier studies have suggested that the planetary
methane is an important stratospheric heater which critically affects the
vertical temperature gradient, hence the strength of spectral emission bands.