  This paper considers a scenario in which the Terahertz (THz) transmitter
equipped with a linear antenna array wishes to focus its beam to a desired
spatial region in the array near-field. The goal is to compute the achievable
spatial region and determine how the system parameters such as the carrier
frequency, the array dimension and the user's location affect its beam focusing
performance. First, based on a theorem from analytic geometry, we show that the
achievable focusing spatial region constitutes a rotated ellipse, with the x
and y coordinates denoting the range and angle, respectively. In this way, the
determination of the spatial region is reduced to a problem of deriving the
coverage of an ellipse. The achievable coverage is then obtained in closed
form, and the construction of carrier frequency offsets that can analytically
control the beam focusing performance is provided. Numerical results validate
the theoretical findings and demonstrate the performance of the proposed
method.


  The analysis of a timeseries can provide many new perspectives if it is
accompanied by the assumption that the timeseries is generated from an
underlying dynamical system. For example, statistical properties of the data
can be related to measure theoretic aspects of the dynamics, and one can try to
recreate the dynamics itself. The underlying dynamics could represent a natural
phenomenon or a physical system, where the timeseries represents a sequence of
measurements. In this paper, we present a completely data-driven framework to
identify and model quasiperiodically driven dynamical systems (Q.P.D.) from the
timeseries it generates. Q.P.D. are a special class of systems that are driven
by a periodic source with multiple base frequencies. Such systems abound in
nature, e.g., astronomy and traffic flow. Our framework reconstructs the
dynamics into two components - the driving quasiperiodic source with generating
frequencies; and the driven nonlinear dynamics. We make a combined use of a
kernel-based harmonic analysis, kernel-based interpolation technique, and
Koopman operator theory. Our framework provides accurate reconstructions and
frequency identification for three real-world case studies.


  We find the minimax rate of convergence in Hausdorff distance for estimating
a manifold M of dimension d embedded in R^D given a noisy sample from the
manifold. We assume that the manifold satisfies a smoothness condition and that
the noise distribution has compact support. We show that the optimal rate of
convergence is n^{-2/(2+d)}. Thus, the minimax rate depends only on the
dimension of the manifold, not on the dimension of the space in which M is
embedded.


  Mass spectrum of charmonium is computed in the framework of potential
non-relativistic quantum chromodynamics. \textit{O}$(1/m)$ and
\textit{O}$(1/m^2)$ relativistic corrections to the Cornell potential and
spin-dependent potential have been added, and is solved numerically. New
experimentally observed and modified positive and negative parity states like
${{\boldsymbol \psi}{(4230)}}$, ${{\boldsymbol \psi}{(4260)}}$, ${{\boldsymbol
\psi}{(4360)}}$, ${{\boldsymbol \psi}{(4390)}}$, ${{\boldsymbol
\psi}{(4660)}}$, ${{\boldsymbol \chi}_{{c1}}{(4140)}}$ and ${{\boldsymbol
\chi}_{{c1}}{(4274)}}$ near open-flavor threshold have also been studied. We
explain them as admixtures of S-D wave states and P-wave states. Apart from
these states, some other states like ${{\mathit X}{(3915)}}$, ${{\boldsymbol
\chi}_{{c1}}{(3872)}}$, ${{\boldsymbol \psi}{(3770)}}$ and ${{\boldsymbol
\psi}{(4160)}}$ have been identified as $2^3P_0$, $2^3P_1$, $1^3D_1$ and
$2^3D_1$ states. Subsequently, the electromagnetic transition widths and
$\gamma\gamma$, $e^+e^-$, light hadron and $\gamma\gamma\gamma$ decay widths of
several states are calculated at various leading orders. All the calculated
results are compared with experimental and results from various theoretical
models.


  Understanding the geographic distribution of species is a key concern in
conservation. By pairing species occurrences with environmental features,
researchers can model the relationship between an environment and the species
which may be found there. To facilitate research in this area, we present the
GeoLifeCLEF 2020 dataset, which consists of 1.9 million species observations
paired with high-resolution remote sensing imagery, land cover data, and
altitude, in addition to traditional low-resolution climate and soil variables.
We also discuss the GeoLifeCLEF 2020 competition, which aims to use this
dataset to advance the state-of-the-art in location-based species
recommendation.


  We introduce CM3, a family of causally masked generative models trained over
a large corpus of structured multi-modal documents that can contain both text
and image tokens. Our new causally masked approach generates tokens left to
right while also masking out a small number of long token spans that are
generated at the end of the string, instead of their original positions. The
casual masking object provides a type of hybrid of the more common causal and
masked language models, by enabling full generative modeling while also
providing bidirectional context when generating the masked spans. We train
causally masked language-image models on large-scale web and Wikipedia
articles, where each document contains all of the text, hypertext markup,
hyperlinks, and image tokens (from a VQVAE-GAN), provided in the order they
appear in the original HTML source (before masking). The resulting CM3 models
can generate rich structured, multi-modal outputs while conditioning on
arbitrary masked document contexts, and thereby implicitly learn a wide range
of text, image, and cross modal tasks. They can be prompted to recover, in a
zero-shot fashion, the functionality of models such as DALL-E, GENRE, and HTLM.
We set the new state-of-the-art in zero-shot summarization, entity linking, and
entity disambiguation while maintaining competitive performance in the
fine-tuning setting. We can generate images unconditionally, conditioned on
text (like DALL-E) and do captioning all in a zero-shot setting with a single
model.


  We provide Schauder estimates for nonlinear Beltrami equations and lower
bounds of the Jacobians for homeomorphic solutions. The results were announced
in arXiv:1412.4046 but here we give detailed proofs.


  Pulsar timing arrays (PTAs) are designed to detect the predicted
gravitational wave (GW) background produced by a cosmological population of
supermassive black hole (SMBH) binaries. In this contribution I review the
physics of such GW background, highlighting its dependence on the overall
binary population, the relation between SMBHs and their hosts, and their
coupling with the stellar and gaseous environment. The latter is particularly
relevant when it drives the binaries to extreme eccentricities (e>0.9), which
might be the case for stellar-driven systems. This causes a substantial
suppression of the low frequency signal, potentially posing a serious threat to
the effectiveness of PTA observations. A future PTA detection will allow to
directly observe for the first time subparsec SMBH binaries on their way to the
GW driven coalescence, providing important answers of the outstanding questions
related to the physics underlying the formation and evolution of these
spectacular sources.


  We propose a new Graph Neural Network that combines recent advancements in
the field. We give theoretical contributions by proving that the model is
strictly more general than the Graph Isomorphism Network and the Gated Graph
Neural Network, as it can approximate the same functions and deal with
arbitrary edge values. Then, we show how a single node information can flow
through the graph unchanged.


  Various novel transport phenomena in chiral systems result from the interplay
of quantum anomalies with magnetic field and vorticity in high-energy heavy-ion
collisions, and could survive the expansion of the fireball and be detected in
experiments. Among them are the chiral magnetic effect, the chiral vortical
effect and the chiral magnetic wave, the experimental searches for which have
aroused extensive interest. The goal of this review is to describe the current
status of experimental studies at Relativistic Heavy Ion Collider at BNL and
the Large Hadron Collider at CERN, and to outline the future work in experiment
needed to eliminate the existing uncertainties in the interpretation of the
data.


  Almost every galaxy has a supermassive black hole (SMBH) residing at its
center, the Milky Way included. Recent studies suggest that these unique places
are expected to host a high abundance of stellar and compact object binaries.
These binaries form hierarchical triple systems with the SMBH and undergo the
eccentric Kozai-Lidov (EKL) mechanism. Here we estimate the detectability of
potential Gravitational-Wave emissions from these compact objects within the
frequency band of the Laser Interferometer Space Antenna (LISA) and Laser
Interferometer Gravitational-Wave Observatory (LIGO) and Virgo detectors. We
generate a post EKL population of stars at the onset of Roche limit crossing
and follow their evolution to compact object binaries. As a proof-of-concept,
we adopt two metallicities, solar metallicity ($Z = 0.02$) and $15\%$ of it ($Z
= 0.003$). We demonstrate that over the observation timescale of LISA, black
hole binaries (BH-BH) and white dwarf binaries provide the most prominent GW
sources via the EKL assisted merger channel. Systems involving neutron stars
are less observable but possibly abundant through different merger channels.
Our population synthesis of BH-BH with $Z = 0.02$ ($Z = 0.003$) translate to
$\sim$ $4$ ($24$) events per year with LIGO within a 1 ${\rm Gpc}^3$ sphere. We
also estimated the number of binaries visible in the LISA band within the inner
parsec of our galactic center (and possibly other galaxies) to be about 14 -
150 WD-WD, 0 - 2 NS-BH, 0.2 - 4 NS-NS, and 0.3 - 20 BH-BH.


  Motivated by the scenario of resonant leptogenesis in which lepton number
creation in the electroweak-scale is relevant, we investigate the spectral
properties and possible collective nature of the standard model neutrinos at
electroweak scale temperature (T). We adopt the R_xi gauge fixing, which
includes the unitary gauge as a limiting case, and allows us to study the
broken as well as the restored phases of the gauge symmetry in a unified way.
We show that the spectral density of the neutrino has a three-peak structure in
the low-momentum region due to the scattering with the thermally excited
particles (i.e., Landau damping) when T becomes comparable to the weak-boson
masses in the plasma. The three peaks are identified with a novel ultrasoft
mode, the usual quasiparticle, and antiplasmino modes. Varying the gauge-fixing
parameter, we show that the three-peak structure appears independently of the
gauge fixing and thus has a physical significance. We discuss possible
implications of the neutrino spectral density obtained in the present work on
particle cosmology, in particular in the context of resonant leptogenesis.


  We study the heat trace for both the drifting Laplacian as well as
Schr\"odinger operators on compact Riemannian manifolds. In the case of a
finite regularity potential or weight function, we prove the existence of a
partial (six term) asymptotic expansion of the heat trace for small times as
well as a suitable remainder estimate. We also demonstrate that the more
precise asymptotic behavior of the remainder is determined by and conversely
distinguishes higher (Sobolev) regularity on the potential or weight function.
In the case of a smooth weight function, we determine the full asymptotic
expansion of the heat trace for the drifting Laplacian for small times. We then
use the heat trace to study the asymptotics of the eigenvalue counting
function. In both cases the Weyl law coincides with the Weyl law for the
Riemannian manifold with the standard Laplace-Beltrami operator. We conclude by
demonstrating isospectrality results for the drifting Laplacian on compact
manifolds.


  In this paper, we provide the mathematical framework to evaluate and quantify
the performance of wireless systems, which employ beamforming, in the presence
of hardware imperfections at both the basestation and the user equipment. In
more detail, by taking a macroscopic view of the joint impact of hardware
imperfections, we introduce a general model that accounts for transceiver
impairments in beamforming transmissions. In order to evaluate their impact, we
present novel closed form expressions for the outage probability and upper
bounds for the characterization of the system's capacity. Our analysis reveals
that the level of imperfection can significantly constraint the ergodic
capacity. Therefore, it is important to take them into account when evaluating
and designing beamforming systems.


  In this paper we formulate and solve an optimal problem for Stochastic
process with a regime absorbing state. The solution for this problem is
obtained through a system of partial differential equations. The method is
applied to obtain an explicit solution for the Merton portfolio problem when an
asset has a default probability in case of a log utility.


  Slow dynamics in disordered materials prohibits direct simulation of their
rich nonequilibrium behavior at large scales. "Patchwork dynamics" is
introduced to mimic relaxation over a very broad range of time scales by
equilibrating or optimizing directly on successive length scales. This dynamics
is used to study coarsening and to replicate memory effects for spin glasses
and random ferromagnets. It is also used to find, with high confidence, exact
ground states in large or toroidal samples.


  The cyclic insertion conjecture of Borwein, Bradley, Broadhurst and
Lison\v{e}k states that by inserting all cyclic permutations of some initial
blocks of 2's into the multiple zeta value $ \zeta(1,3,\ldots,1,3) $ and
summing, one obtains an explicit rational multiple of a power of $ \pi $.
Hoffman gives a conjectural identity of a similar flavour concerning $ 2
\zeta(3,3,\{2\}^m) - \zeta(3,\{2\}^m,(1,2)) $.
  In this paper we introduce the 'generalised cyclic insertion conjecture',
which we describe using a new combinatorial structure on iterated integrals --
the so-called alternating block decomposition. We see that both the original
BBBL cyclic insertion conjecture, and Hoffman's conjectural identity, are
special cases of this 'generalised' cyclic insertion conjecture. By using
Brown's motivic MZV framework, we establish that some symmetrised version of
the generalised cyclic insertion conjecture always holds, up to a rational;
this provides some evidence for the generalised conjecture.


  Distribution of the entangled state of trapped atomic ions to long distance
using quantum repeater protocol is considered. Indeed, the long distance is
divided into short parts, and then using entanglement generation and
entanglement swapping techniques in optomechanical cavities, the entanglement
is distributed. To do the task, we perform interaction between trapped atomic
ions in optomechanical cavities, operate proper measurements on trapped ions
and also make Bell state measurement as a well-known way to swap the
entanglement. Accordingly, the entanglement is distributed between target ions
with satisfactory values of success probability and entanglement degree. The
effects of detuning and amplitude of pump laser on the entanglement and success
probability are evaluated. The uctuations of entanglement and success
probability are decreased by increasing of detuning. Via increasing the
amplitude of pump laser, the maxima of entanglement are repeated more times and
success probability undergoes the collapse-revival phenomenon.


  Extensions beyond the Standard Model allow for a gauge singlet scalar to be
kinetically coupled with the Higgs. We consider kinetic mixing between a Dark
scalar gauge singlet \emph{nearly degenerate} with the Higgs, focusing on the
\emph{dynamical} aspects of the mixing phenomena. The renormalization program
is carried out by obtaining the one-loop effective action which yields an
effective non-hermitian Hamiltonian to study the dynamics of mixing. The scalar
Higgs becomes a coherent superposition of the mass eigenstates, thus kinetic
mixing leads to oscillations and common decay channels in striking similarity
with neutral meson mixing. Near degeneracy yields an \emph{enhancement} of the
kinetic coupling. For small kinetic mixing we find that the mass eigenstates
feature different lifetimes which result in a wide separation of time scales of
evolution along with important coherence aspects from Dark scalar-Higgs
interference. The wide separation of scales is manifest as displaced decay
vertices which could potentially be a telltale experimental signal of kinetic
mixing.


  The XMM Cluster Archive Super Survey (X-CLASS) is a serendipitously-detected
X-ray-selected sample of 845 galaxy clusters based on 2774 XMM archival
observations and covering approximately 90 deg$^2$ spread across the
high-Galactic latitude ($|b|>20$ deg) sky. The primary goal of this survey is
to produce a well-selected sample of galaxy clusters on which cosmological
analyses can be performed. This article presents the photometric redshift
followup of a high signal-to-noise subset of 266 of these clusters with
declination $\delta<+20$ deg with GROND, a seven channel ($grizJHK$)
simultaneous imager on the MPG 2.2m telescope at the ESO La Silla Observatory.
We use a newly developed technique based on the red sequence colour-redshift
relation, enhanced with information coming from the X-ray detection to provide
photometric redshifts for this sample. We determine photometric redshifts for
236 clusters, finding a median redshift of $z=0.39$ with an accuracy of $\Delta
z = 0.02 (1+z)$ when compared to a sample of 76 spectroscopically confirmed
clusters. We also compute X-ray luminosities for the entire sample and find a
median bolometric luminosity of $7.2\times10^{43} \mathrm{erg\ s^{-1}}$ and a
median temperature 2.9 keV. We compare our results to the XMM-XCS and XMM-XXL
surveys, finding good agreement in both samples. The X-CLASS catalogue is
available online at http://xmm-lss.in2p3.fr:8080/l4sdb/.


  After the discovery of the gravitational waves and the observation of
neutrinos of cosmic origin, we have entered a new and exciting era where cosmic
rays, neutrinos, photons and gravitational waves will be used simultaneously to
study the highest energy phenomena in the Universe. Here we present a fully
Bayesian approach to the challenge of combining and comparing the wealth of
measurements from existing and upcoming experimental facilities. We discuss the
procedure from a theoretical point of view and using simulations, we also
demonstrate the feasibility of the method by incorporating the use of
information provided by different theoretical models and different experimental
measurements.


  We study the problem of dynamic regret minimization in online convex
optimization, in which the objective is to minimize the difference between the
cumulative loss of an algorithm and that of an arbitrary sequence of
comparators. While the literature on this topic is very rich, a unifying
framework for the analysis and design of these algorithms is still missing. In
this paper, \emph{we show that dynamic regret minimization is equivalent to
static regret minimization in an extended decision space}. Using this simple
observation, we show that there is a frontier of lower bounds trading off
penalties due to the variance of the losses and penalties due to variability of
the comparator sequence, and provide a framework for achieving any of the
guarantees along this frontier. As a result, we prove for the first time that
adapting to the squared path-length of an arbitrary sequence of comparators to
achieve regret $R_{T}(u_{1},\dots,u_{T})\le O(\sqrt{T\sum_{t}
\|u_{t}-u_{t+1}\|^{2}})$ is impossible. However, we prove that it is possible
to adapt to a new notion of variability based on the locally-smoothed squared
path-length of the comparator sequence, and provide an algorithm guaranteeing
dynamic regret of the form $R_{T}(u_{1},\dots,u_{T})\le \tilde
O(\sqrt{T\sum_{i}\|\bar u_{i}-\bar u_{i+1}\|^{2}})$. Up to polylogarithmic
terms, the new notion of variability is never worse than the classic one
involving the path-length.


  Given the increasing competition in mobile app ecosystems, improving the
experience of users has become a major goal for app vendors. This article
introduces a visionary app store, called APP STORE 2.0, which exploits
crowdsourced information about apps, devices and users to increase the overall
quality of the delivered mobile apps. We sketch a blueprint architecture of the
envisioned app stores and discuss the different kinds of actionable feedbacks
that app stores can generate using crowdsourced information.


  Quantum superposition is normally sustained in a microscopic regime governed
by Heisenberg uncertainty principle applicable to a single particle. Quantum
correlation between paired particles implies the violation of local realism
governed by classical physics. Over the last decades, quantum features have
been implemented in various quantum technologies including quantum computing,
communications, and sensing. Such quantum features are generally known to be
impossible by any classical means. Here, a macroscopic quantum correlation is
presented for coherence manipulations of polarization-path correlations of a
continuous wave laser, satisfying the joint-parameter relation in an
inseparable product-basis form. For the coherence control of the
polarization-path correlation, a pair of electro-optic modulators is used in a
noninterfering Mach-Zehnder interferometer for deterministic switching between
paired polarization bases, resulting in the polarization product-basis
superposition in a selective product-basis choice manner by a followed pair of
acousto-optic modulators. This unprecedented macroscopic quantum feature opens
the door to a new understanding of quantum mechanics beyond the microscopic
regime for future classical optics-compatible quantum information.


  Verification is a task to check whether a given quantum state is close to an
ideal state or not. In this paper, we show that a variety of many-qubit quantum
states can be verified with only sequential single-qubit measurements of Pauli
operators. First, we introduce a protocol for verifying ground states of
Hamiltonians. We next explain how to verify quantum states generated by a
certain class of quantum circuits. We finally propose an adaptive test of
stabilizers that enables the verification of all polynomial-time-generated
hypergraph states, which include output states of the
Bremner-Montanaro-Shepherd-type instantaneous quantum polynomial time (IQP)
circuits. Importantly, we do not make any assumption that the identically and
independently distributed copies of the same states are given: Our protocols
work even if some highly complicated entanglement is created among copies in
any artificial way. As applications, we consider the verification of the
quantum computational supremacy demonstration with IQP models, and verifiable
blind quantum computing.


  We report a precise search for correlation effects in linear chains of 2 and
3 trapped Ca+ ions. Unexplained correlations in photon emission times within a
linear chain of trapped ions have been reported, which, if genuine, cast doubt
on the potential of an ion trap to realize quantum information processing. We
observe quantum jumps from the metastable 3d 2D_{5/2} level for several hours,
searching for correlations between the decay times of the different ions. We
find no evidence for correlations: the number of quantum jumps with separations
of less than 10 ms is consistent with statistics to within errors of 0.05%; the
lifetime of the metastable level derived from the data is consistent with that
derived from independent single-ion data at the level of the experimental
errors 1%; and no rank correlations between the decay times were found with
sensitivity to rank correlation coefficients at the level of |R| = 0.024.


  We consider biorthogonal polynomials that arise in the study of a
generalization of two--matrix Hermitian models with two polynomial potentials
V_1(x), V_2(y) of any degree, with arbitrary complex coefficients. Finite
consecutive subsequences of biorthogonal polynomials (`windows'), of lengths
equal to the degrees of the potentials, satisfy systems of ODE's with
polynomial coefficients as well as PDE's (deformation equations) with respect
to the coefficients of the potentials and recursion relations connecting
consecutive windows. A compatible sequence of fundamental systems of solutions
is constructed for these equations. The (Stokes) sectorial asymptotics of these
fundamental systems are derived through saddle-point integration and the
Riemann-Hilbert problem characterizing the differential equations is deduced.


  Concrete is the most widely used engineered material in the world with more
than 10 billion tons produced annually. Unfortunately, with that scale comes a
significant burden in terms of energy, water, and release of greenhouse gases
and other pollutants. As such, there is interest in creating concrete formulas
that minimize this environmental burden, while satisfying engineering
performance requirements. Recent advances in artificial intelligence have
enabled machines to generate highly plausible artifacts, such as images of
realistic looking faces. Semi-supervised generative models allow generation of
artifacts with specific, desired characteristics. In this work, we use
Conditional Variational Autoencoders (CVAE), a type of semi-supervised
generative model, to discover concrete formulas with desired properties. Our
model is trained using open data from the UCI Machine Learning Repository
joined with environmental impact data computed using a web-based tool. We
demonstrate CVAEs can design concrete formulas with lower emissions and natural
resource usage while meeting design requirements. To ensure fair comparison
between extant and generated formulas, we also train regression models to
predict the environmental impacts and strength of discovered formulas. With
these results, a construction engineer may create a formula that meets
structural needs and best addresses local environmental concerns.


  We investigate the black hole mass function at $z\sim5$ using XQz5, our
recent sample of the most luminous quasars between the redshifts $4.5 < z <
5.3$. We include 72 quasars with black hole masses estimated from
velocity-broadened emission-line measurements and single-epoch virial
prescriptions in the footprint of a highly complete parent survey. The sample
mean Eddington ratio and standard deviation is $\log\lambda \approx
-0.20\pm0.24$. The completeness-corrected mass function is modelled as a double
power-law, and we constrain its evolution across redshift assuming
accretion-dominated mass growth. We estimate the evolution of the mass function
from $z=5-4$, presenting joint constraints on accretion properties through a
measured dimensionless e-folding parameter, $k_{\rm{ef}} \equiv
\langle\lambda\rangle U (1-\epsilon)/\epsilon = 1.79\pm0.06$, where
$\langle\lambda\rangle$ is the mean Eddington ratio, $U$ is the duty cycle, and
$\epsilon$ is the radiative efficiency. If these supermassive black holes were
to form from seeds smaller than $10^8\,M_{\odot}$, the growth rate must have
been considerably faster at $z\gg5$ than observed from $z=5-4$. A growth rate
exceeding $3\times$ the observed rate would reduce the initial heavy seed mass
to $10^{5-6}\,M_{\odot}$, aligning with supermassive star and/or direct
collapse seed masses. Stellar mass ($10^2\,M_{\odot}$) black hole seeds would
require $\gtrsim4.5\times$ the observed growth rate at $z\gg5$ to reproduce the
measured active black hole mass function. A possible pathway to produce the
most extreme quasars is radiatively inefficient accretion flow, suggesting
black holes with low angular momentum or photon trapping in supercritically
accreting thick discs.


  We investigate the CO excitation and interstellar medium (ISM) conditions in
a cold gas mass-selected sample of 22 star-forming galaxies at $z=0.46-3.60$,
observed as part of the ALMA Spectroscopic Survey in the Hubble Ultra Deep
Field (ASPECS). Combined with VLA follow-up observations, we detect a total of
34 CO $J \rightarrow J-1$ transitions with $J=1$ up to $8$ (and an additional
21 upper limits, up to $J=10$) and six [C I] ${^3P}_1 \rightarrow {^3P}_0$ and
${^3P}_2 \rightarrow {^3P}_1$ transitions (and 12 upper limits). The CO(2-1)
and CO(3-2)-selected galaxies, at $z=1.2$ and $2.5$, respectively, exhibit a
range in excitation in their mid-$J=4,5$ and high-$J=7,8$ lines, on average
lower than ($L_{\rm IR}$-brighter) BzK-color- and submillimeter-selected
galaxies at similar redshifts. The former implies that a warm ISM component is
not necessarily prevalent in gas mass-selected galaxies at $z=1.2$. We use
stacking and Large Velocity Gradient models to measure and predict the average
CO ladders at $z<2$ and $z\geq2$, finding $r_{21}=0.75 \pm 0.11$ and
$r_{31}=0.77 \pm 0.14$, respectively. From the models, we infer that the
galaxies at $z\geq2$ have intrinsically higher excitation than those at $z<2$.
This fits a picture in which the global excitation is driven by an increase in
the star formation rate surface density of galaxies with redshift. We derive a
neutral atomic carbon abundance of $(1.9 \pm 0.4) \times 10^{-5}$, comparable
to the Milky Way and main-sequence galaxies at similar redshifts, and fairly
high densities ($\geq 10^4$ cm$^{-3}$), consistent with the low-$J$ CO
excitation. Our results imply a decrease in the cosmic molecular gas mass
density at $z\geq2$ compared to previous ASPECS measurements.


  In this paper basic differential invariants of generic hyperbolic
Monge--Amp\`ere equations with respect to contact transformations are
constructed and the equivalence problem for these equations is solved.


  The ANTARES Collaboration is aiming at the construction and the operation of
a large undersea neutrino telescope for neutrino astronomy, neutrino
oscillation and indirect dark matter searches. Started 3 years ago an intensive
R&D program has shown the feasibility of such a detector in the deep waters of
the Mediterranean sea. We have now started the design and the construction of a
0.1 km(^{2}) detector for which the expected performance will be briefly
described here.


  The general form of the global conservation laws for $N$-body systems in the
first post-Newtonian approximation of general relativity is considered. Our
approach applies to the motion of an isolated system of $N$ arbitrarily
composed and shaped, weakly self-gravitating, rotating, deformable bodies and
uses a framework recently introduced by Damour, Soffel and Xu (DSX). We succeed
in showing that seven of the first integrals of the system (total mass-energy,
total dipole mass moment and total linear momentum) can be broken up into a sum
of contributions which can be entirely expressed in terms of the basic
quantities entering the DSX framework: namely, the relativistic individual
multipole moments of the bodies, the relativistic tidal moments experienced by
each body, and the positions and orientations with respect to the global
coordinate system of the local reference frames attached to each body. On the
other hand, the total angular momentum of the system does not seem to be
expressible in such a form due to the unavoidable presence of irreducible
nonlinear gravitational effects.


  Mass spectrometry proteomics, characterized by spiky, spatially heterogeneous
functional data, can be used to identify potential cancer biomarkers. Existing
mass spectrometry analyses utilize mean regression to detect spectral regions
that are differentially expressed across groups. However, given the
inter-patient heterogeneity that is a key hallmark of cancer, many biomarkers
are only present at aberrant levels for a subset of, not all, cancer samples.
Differences in these biomarkers can easily be missed by mean regression, but
might be more easily detected by quantile-based approaches. Thus, we propose a
unified Bayesian framework to perform quantile regression on functional
responses. Our approach utilizes an asymmetric Laplace working likelihood,
represents the functional coefficients with basis representations which enable
borrowing of strength from nearby locations, and places a global-local
shrinkage prior on the basis coefficients to achieve adaptive regularization.
Different types of basis transform and continuous shrinkage priors can be used
in our framework. A scalable Gibbs sampler is developed to generate posterior
samples that can be used to perform Bayesian estimation and inference while
accounting for multiple testing. Our framework performs quantile regression and
coefficient regularization in a unified manner, allowing them to inform each
other and leading to improvement in performance over competing methods as
demonstrated by simulation studies. We also introduce an adjustment procedure
to the model to improve its frequentist properties of posterior inference. We
apply our model to identify proteomic biomarkers of pancreatic cancer that are
differentially expressed for a subset of cancer patients compared to the normal
controls, which were missed by previous mean-regression based approaches.
Supplementary materials for this article are available online.


  We establish a characterization of supernilpotent Mal'cev algebras which
generalizes the affine structure of abelian Mal'cev algebras and the recent
characterization of 3-supernilpotent Mal'cev algebras. We then show that for
varieties in which the two-generated free algebra is finite: (1) neutrality of
the higher commutators is equivalent to congruence meet-semidistributivity, and
(2) the class of varieties which interpret a Mal'cev term in every
supernilpotent algebra is equivalent to the existence of a weak difference
term. We then establish properties of the higher commutator in the
aforementioned second class of varieties.


  One of the celebrated tools in explaining the Hydrogen atom is
Born-Oppenheimer approximation. The resemblance of $QQ\bar{q}\bar{q}$
tetraquarks to Hydrogen atom within Quantum chromodynamics (QCD) implies usage
of Born-Oppenheimer approximation for these multiquark states. In this work, we
use dynamical diquark model to calculate mass spectra and sizes of doubly
charmed and charged tetraquark states denoted as $T_{cc}^{++}$. Our results for
mass spectra indicate some bound state candidates with respect to corresponding
two-meson thresholds. Calculation of expectation values of $\sqrt{\langle r^2
\rangle}$ reflects that doubly charmed and charged tetraquark states are
compact.


  Principal Component Analysis (PCA) is a fundamental data preprocessing tool
in the world of machine learning. While PCA is often thought of as a
dimensionality reduction method, the purpose of PCA is actually two-fold:
dimension reduction and uncorrelated feature learning. Furthermore, the
enormity of the dimensions and sample size in the modern day datasets have
rendered the centralized PCA solutions unusable. In that vein, this paper
reconsiders the problem of PCA when data samples are distributed across nodes
in an arbitrarily connected network. While a few solutions for distributed PCA
exist, those either overlook the uncorrelated feature learning aspect of the
PCA, tend to have high communication overhead that makes them inefficient
and/or lack `exact' or `global' convergence guarantees. To overcome these
aforementioned issues, this paper proposes a distributed PCA algorithm termed
FAST-PCA (Fast and exAct diSTributed PCA). The proposed algorithm is efficient
in terms of communication and is proven to converge linearly and exactly to the
principal components, leading to dimension reduction as well as uncorrelated
features. The claims are further supported by experimental results.


  People frequently interact with information retrieval (IR) systems, however,
IR models exhibit biases and discrimination towards various demographics. The
in-processing fair ranking methods provide a trade-offs between accuracy and
fairness through adding a fairness-related regularization term in the loss
function. However, there haven't been intuitive objective functions that depend
on the click probability and user engagement to directly optimize towards this.
In this work, we propose the In-Batch Balancing Regularization (IBBR) to
mitigate the ranking disparity among subgroups. In particular, we develop a
differentiable \textit{normed Pairwise Ranking Fairness} (nPRF) and leverage
the T-statistics on top of nPRF over subgroups as a regularization to improve
fairness. Empirical results with the BERT-based neural rankers on the MS MARCO
Passage Retrieval dataset with the human-annotated non-gendered queries
benchmark \citep{rekabsaz2020neural} show that our IBBR method with nPRF
achieves significantly less bias with minimal degradation in ranking
performance compared with the baseline.


  Atomistic deformation simulations in the nominally elastic regime are
performed for a model binary glass with strain rates as low as $10^{4}$/sec
(corresponding to 0.01 shear strain per 1$\mu$sec). A robust elasticity is
revealed that exhibits only minor elastic softening, despite quite different
degrees of structural relaxation occurring over the four orders of magnitude
strain rates considered. A closer inspection of the atomic-scale structure
indicates the material response is distinctly different for two types of local
atomic environments. A system spanning iscosahedrally coordinated substructure
responds purely elastically, whereas the remaining substructure also admits
microplastic evolution. This leads to a heterogeneous internal stress
distribution which, upon unloading, results in negative creep and complete
residual-strain recovery. A detailed structural analysis in terms of local
stress, atomic displacement, and SU(2) local bonding topology shows such
microscopic processes can result in large changes in local stress and are more
likely to occur in geometrically frustrated regions characterized by higher
free volume and softer elastic stiffness. These insights shed atomistic light
onto the structural origins that may govern recent experimental observations of
significant structural evolution in response to elastic loading protocols.


  We investigate the H\"older geometry of curves generated by iterated function
systems (IFS) in a complete metric space. A theorem of Hata from 1985 asserts
that every connected attractor of an IFS is locally connected and
path-connected. We give a quantitative strengthening of Hata's theorem. First
we prove that every connected attractor of an IFS is $(1/s)$-H\"older
path-connected, where $s$ is the similarity dimension of the IFS. Then we show
that every connected attractor of an IFS is parameterized by a
$(1/\alpha)$-H\"older curve for all $\alpha>s$. At the endpoint, $\alpha=s$, a
theorem of Remes from 1998 already established that connected self-similar sets
in Euclidean space that satisfy the open set condition are parameterized by
$(1/s)$-H\"older curves. In a secondary result, we show how to promote Remes'
theorem to self-similar sets in complete metric spaces, but in this setting
require the attractor to have positive $s$-dimensional Hausdorff measure in
lieu of the open set condition. To close the paper, we determine sharp H\"older
exponents of parameterizations in the class of connected self-affine
Bedford-McMullen carpets and build parameterizations of self-affine sponges. An
interesting phenomenon emerges in the self-affine setting. While the optimal
parameter $s$ for a self-similar curve in $\mathbb{R}^n$ is always at most the
ambient dimension $n$, the optimal parameter $s$ for a self-affine curve in
$\mathbb{R}^n$ may be strictly greater than $n$.


  In a previous paper we used T-duality to construct a new type of 1/4-BPS
solution describing a pair of NS5-branes intersecting in 1+3 dimensions and
localised in all other directions except for a single transverse circle. This
led to an explicit solution to a sourced Monge--Ampere equation, of which there
are few known examples. In this paper we refine this formalism and apply it to
two important generalisations: the resolved and deformed conifolds. In doing so
we construct two new solutions describing, respectively, a pair of NS5-branes
separated in a transverse direction and a pair of NS5-branes with smooth
`diamond' profile. We show how the parameter of the resolved conifold (size of
the S^2) maps to a transverse separation of the NS5-branes, while the modulus
of the deformed conifold (size of the S^3) maps to the deformation parameter of
the diamond web.


  We introduce Open3DIS, a novel solution designed to tackle the problem of
Open-Vocabulary Instance Segmentation within 3D scenes. Objects within 3D
environments exhibit diverse shapes, scales, and colors, making precise
instance-level identification a challenging task. Recent advancements in
Open-Vocabulary scene understanding have made significant strides in this area
by employing class-agnostic 3D instance proposal networks for object
localization and learning queryable features for each 3D mask. While these
methods produce high-quality instance proposals, they struggle with identifying
small-scale and geometrically ambiguous objects. The key idea of our method is
a new module that aggregates 2D instance masks across frames and maps them to
geometrically coherent point cloud regions as high-quality object proposals
addressing the above limitations. These are then combined with 3D
class-agnostic instance proposals to include a wide range of objects in the
real world. To validate our approach, we conducted experiments on three
prominent datasets, including ScanNet200, S3DIS, and Replica, demonstrating
significant performance gains in segmenting objects with diverse categories
over the state-of-the-art approaches.


  "Background subtraction" is an old technique for finding moving objects in a
video sequence for example, cars driving on a freeway. The idea is that
subtracting the current image from a timeaveraged background image will leave
only nonstationary objects. It is, however, a crude approximation to the task
of classifying each pixel of the current image; it fails with slow-moving
objects and does not distinguish shadows from moving objects. The basic idea of
this paper is that we can classify each pixel using a model of how that pixel
looks when it is part of different classes. We learn a mixture-of-Gaussians
classification model for each pixel using an unsupervised technique- an
efficient, incremental version of EM. Unlike the standard image-averaging
approach, this automatically updates the mixture component for each class
according to likelihood of membership; hence slow-moving objects are handled
perfectly. Our approach also identifies and eliminates shadows much more
effectively than other techniques such as thresholding. Application of this
method as part of the Roadwatch traffic surveillance project is expected to
result in significant improvements in vehicle identification and tracking.


  We propose a scheme to prepare nanomechanical oscillators in nonclassical
steady states, characterized by a pronounced negative Wigner function. In our
optomechanical approach, the mechanical oscillator couples to multiple laser
driven resonances of an optical cavity. By lowering the resonance frequency of
the oscillator via an inhomogeneous electrostatic field, we significantly
enhance its intrinsic geometric nonlinearity per phonon. This causes the
motional sidebands to split into separate spectral lines for each phonon number
and transitions between individual phonon Fock states can be selectively
addressed. We show that this enables the preparation of the nanomechanical
oscillator in a single phonon Fock state. Our scheme can for example be
implemented with a carbon nanotube dispersively coupled to the evanescent field
of a state of the art whispering gallery mode microcavity.


  Consider a quantum cat map $M$ associated to a matrix
$A\in\mathop{\mathrm{Sp}}(2n,\mathbb Z)$, which is a common toy model in
quantum chaos. We show that the mass of eigenfunctions of $M$ on any nonempty
open set in the position-frequency space satisfies a lower bound which is
uniform in the semiclassical limit, under two assumptions: (1) there is a
unique simple eigenvalue of $A$ of largest absolute value and (2) the
characteristic polynomial of $A$ is irreducible over the rationals. This is
similar to previous work [arXiv:1705.05019], [arXiv:1906.08923] on negatively
curved surfaces and [arXiv:2103.06633] on quantum cat maps with $n=1$, but this
paper gives the first results of this type which apply in any dimension. When
condition (2) fails we provide a weaker version of the result and discuss
relations to existing counterexamples. We also obtain corresponding statements
regarding semiclassical measures and damped quantum cat maps.


  In this paper, we propose a new algorithm of iterative least squared (LS)
channel estimation for 64 antennas Massive Multiple Input, Multiple Output
(MIMO) turbo-receiver. The algorithm employs log-likelihood ratios (LLR) of
low-density parity-check (LDPC) decoder and minimum mean square error (MMSE)
estimator to achieve soft data symbols. These soft data symbols are further
MMSE-weighted again and combined with pilot symbols to achieve a modified LS
channel estimate. The modified LS estimate is employed by the same channel
estimation unit to enhance turbo-receiver performance via channel
re-estimation, as a result, the proposed approach has low complexity and fits
any channel estimation solution, which is quite valuable in practice. We
analyze both hard and soft algorithm versions and present simulation results of
5G turbo-receiver in the 3D-UMa model of the QuaDRiGa 2.0 channel. Simulation
results demonstrate up to 0.3dB performance gain compared to the unweighted
hard data symbols utilization in the LS channel re-calculation.


  There have been intensive studies on Kitaev materials for the sake of the
realization of exotic states such as quantum spin liquid and topological
orders. In realistic materials, the Kitaev interaction may coexist with the
Dzyaloshinskii-Moriya interaction (DMI), and it is a challenge to distinguish
their magnitudes separately. Here, we study the topological magnon excitations
and related thermal Hall conductivity of kagome magnet exhibiting Heisenberg,
Kitaev and DM interactions exposed to a magnetic field. In a strong magnetic
field perpendicular to the plane of the lattice ([111] direction) that bring
the system into the fully polarized paramagnetic phase, we find that the magnon
bands carry nontrivial Chern numbers in the full region of the phase diagram.
Furthermore, there are phase transitions relate two topological phases with
opposite Chern numbers, which lead to the sign changes of the thermal Hall
conductivity. In the phase with negative thermal conductivity, the Kitaev
interaction is relatively large and the width of the phase increases with the
strength of DMI. Hence the study here will contribute to the understanding of
related compounds.


  The phenomenology of neutrino oscillations is extended to the neutron-
antineutron oscillations predicted by the grand unified theories. There are six
parameters in general describing the one-flavor oscillations: two real Majorana
masses (of opposite signs), three Euler's angles, and a phase multiplier "chi".
The sum of the Majorana masses, treated as a small parity- violating parameter
"epsilon", induces the nuclear decays (A,Z) -> (A-2,Z) and determines the
oscillation rate of neutrons in the vacuum. We derive a constraint to a small
parity-conserving parameter "epsilon-prime" representing a combination of two
Euler's angles. This parameter gives no significant contribution to the neutron
oscillation rate in the vacuum, while contributes to the nuclear decay rate.
The nuclear stability implies "epsilon-prime" < 1/year. Absence of the vacuum
neutron oscillations together with existence of the nuclear decays (A,Z) ->
(A-2,Z) would become simplest manifestation of the "epsilon-prime" =/ 0.


  We derive a beta-integral over $\mathbb{Z}\times \mathbb{R}$ , which is a
counterpart of the Dougall $_5H_5$-formula and of the de Branges--Wilson
integral, our integral includes $_{10}H_{10}$-summation. For a derivation we
use a two-dimensional integral transform related to representations of the
Lorentz group, this transform is a counterpart of the Olevskii index transform
(a synonym: Jacobi transform).


  We review methods for determination of "quasi-periods" (or "cycle length") of
signals of low coherence. Such type of variability was called "cyclic" for
semi-regular red variables, or "quasi-periodic oscillations" (QPO) for fast
variability in cataclysmic variables and related objects. Methods are
illustrated by application to AF Cygni.


  Fixed-target experiments permit the study of hadron production in the target
fragmentation region. It is expected that the tagging of specific particles in
the target fragments can be employed to introduce a bias in the hard scattering
process towards a specific flavour content. The case of hadrons containing a
heavy quark is particularly attractive because of the clear experimental
signatures and the applicability of perturbative QCD. The standard approach to
one-particle inclusive processes based on fragmentation functions is valid in
the current fragmentation region and for large transverse momenta $p_T$ in the
target fragmentation region, but it fails for particle production at small
$p_T$ in the target fragmentation region. A collinear singularity, which cannot
be absorbed in the standard way into the phenomenological distribution
functions, prohibits the application of this procedure. This situation is
remedied by the introduction of a new set of distribution functions, the target
fragmentation functions. They describe particle production in the target
fragmentation region, and can be viewed as correlated distribution functions in
the momentum fractions of the observed particle and of the parton initiating
the hard scattering process. It is shown in a next-to-leading-order calculation
for the case of deeply inelastic lepton-nucleon scattering that the additional
singularity can be consistently absorbed into the renormalized target
fragmentation functions on the one-loop level. The formalism is derived in
detail and is applied to the production of heavy quarks. The renormalization
group equation of the target fragmentation functions for the perturbative
contribution is solved numerically, and the results of a case study for deeply
inelastic lepton-nucleon scattering at DESY (H1 and ZEUS at HERA), at CERN
(NA47) and at Fermilab (E665) are discussed. We also comment briefly on the
case of an intrinsic heavy-quark content of the proton.


  Gross domestic product (GDP) is an important economic indicator that
aggregates useful information to assist economic agents and policymakers in
their decision-making process. In this context, GDP forecasting becomes a
powerful decision optimization tool in several areas. In order to contribute in
this direction, we investigated the efficiency of classical time series models,
the state-space models, and the neural network models, applied to Brazilian
gross domestic product. The models used were: a Seasonal Autoregressive
Integrated Moving Average (SARIMA) and a Holt-Winters method, which are
classical time series models; the dynamic linear model, a state-space model;
and neural network autoregression and the multilayer perceptron, artificial
neural network models. Based on statistical metrics of model comparison, the
multilayer perceptron presented the best in-sample and out-sample forecasting
performance for the analyzed period, also incorporating the growth rate
structure significantly.


  The well-known Bragg-Kleeman rule RCSDA = A dot E0p has become a pioneer work
in radiation physics of charged particles and is still a useful tool to
estimate the range RCSDA of approximately monoenergetic protons with initial
energy E0 in a homogeneous medium. The rule is based on the
continuous-slowing-down-approximation (CSDA). It results from a generalized
(nonrelativistic) Langevin equation and a modification of the phenomenological
friction term. The complete integration of this equation provides information
about the residual energy E(z) and dE(z)/dz at each position z (0 <= z <=
RCSDA). A relativistic extension of the generalized Langevin equation yields
the formula RCSDA = A dot (E0 +E02/2M dot c2)p. The initial energy of
therapeutic protons satisfies E0 << 2M dot c2 (M dot c2 = 938.276 MeV), which
enables us to consider the relativistic contributions as correction terms.
Besides this phenomenological starting-point, a complete integration of the
Bethe-Bloch equation (BBE) is developed, which also provides the determination
of RCSDA, E(z) and dE(z)/dz and uses only those parameters given by the BBE
itself (i.e., without further empirical parameters like modification of
friction). The results obtained in the context of the aforementioned methods
are compared with Monte-Carlo calculations (GEANT4); this Monte-Carlo code is
also used with regard to further topics such as lateral scatter, nuclear
interactions, and buildup effects. In the framework of the CSDA, the energy
transfer from protons to environmental atomic electrons does not account for
local fluctuations.


  We explain the entire process by which we conduct the Galactic Arecibo L-Band
Feed Array HI (GALFA-HI) survey. The survey is a high resolution (3.4'), large
area (13000 deg^2), large Galactic velocity range (-750 to +750 km/s), high
spectral resolution (0.18 km/s) survey of the Galaxy in the 21 cm line
hyperfine transition of hydrogen conducted at Arecibo Observatory. We touch on
some of the new Galactic science being conducted using the GALFA-HI survey,
ranging from High-Velocity Clouds to HI narrow-line self-absorption. We explain
the many technical challenges that confront such a survey, including baseline
ripple, gain variation and asymmetrical beam shapes. To correct for these
systematic effects we use various newly developed methods, which we describe in
detail. We also explain the data reduction process step by step, starting with
the raw time-ordered data and ending with fully calibrated maps. The effects of
each step of the data reduction on the final data product is shown
sequentially. We conclude with future directions for the ongoing survey.


  Previous surveys by Baumert and Lopez and Sanchez have resolved the existence
of cyclic (v,k,lambda) difference sets with k <= 150, except for six open
cases. In this paper we show that four of those difference sets do not exist.
We also look at the existence of difference sets with k <= 300 and cyclic
Hadamard difference sets with v <= 10,000. Finally, we extend an earlier search
of the second author to show that no cyclic projective planes exist with
non-prime power orders up to two billion.


  Two popular perspectives on the non-perturbative domain of Yang-Mills
theories are either in terms of the gluons themselves or in terms of collective
gluonic excitations, i.e. topological excitations. If both views are correct,
then they are only two different representations of the same underlying
physics. One possibility to investigate this connection is by the determination
of gluon correlation functions in topological background fields, as created by
the smearing of lattice configurations. This is performed here for the minimal
Landau gauge gluon propagator, ghost propagator, and running coupling, both in
momentum and position space for SU(2) Yang-Mills theory. The results show that
the salient low-momentum features of the propagators are qualitatively retained
under smearing at sufficiently small momenta, in agreement with an equivalence
of both perspectives. However, the mid-momentum behavior is significantly
affected. These results are also relevant for the construction of truncations
in functional methods, as they provide hints on necessary properties to be
retained in truncations.


  We obtain the two-point Green's function for the relativistic
Dirac-Oscillator problem. This is accomplished by setting up the relativistic
problem in such a way that makes comparison with the nonrelativistic problem
highly transparent and results in a map of the latter into the former. The
relativistic bound states energy spectrum is obtained by locating the energy
poles of this Green's function in a simple and straightforward manner.


  A flux-calibrated high resolution spectrum of the airglow emission is a
practical lambda-calibration reference for astronomical spectral observations.
It is also useful for constraining the molecular parameters of the OH molecule
and the physical conditions in the upper mesosphere. methods: We use the data
collected during the first technical commissioning of the GIANO spectrograph at
the Telescopio Nazionale Galileo (TNG). The high resolution (R~50,000) spectrum
simultaneously covers the 0.95-2.4 micron wavelength range. Relative flux
calibration is achieved by the simultaneous observation of spectrophotometric
standard star. results: We derive a list of improved positions and intensities
of OH infrared lines. The list includes Lambda-split doublets many of which are
spectrally resolved. Compared to previous works, the new results correct errors
in the wavelengths of the Q-branch transitions. The relative fluxes of OH lines
from different vibrational bands show remarkable deviations from theoretical
predictions: the Deltav=3,4 lines are a factor of 2 and 4 brighter than
expected. We also find evidence of a significant fraction (1-4%) of OH
molecules with ``non-thermal'' population of high-J levels. Finally we list
wavelengths and fluxes of 153 lines not attributable to OH. Most of these can
be associated to O2, while 37 lines in the H band are not identified. The O2
and unidentified lines in the H band account for ~5% of the total airglow flux
in this band.


  Motivated by CoNb2O6 (belonging to the columbite family of minerals), we
theoretically study the physics of quantum ferromagnetic Ising chains coupled
anti-ferromagnetically on a triangular lattice in the plane perpendicular to
the chain direction. We combine exact solutions of the chain physics with
perturbative approximations for the transverse couplings. When the triangular
lattice has an isosceles distortion (which occurs in the real material), the
T=0 phase diagram is rich with five different states of matter: ferrimagnetic,
N\'eel, anti-ferromagnetic, paramagnetic and incommensurate phases, separated
by quantum phase transitions. Implications of our results to experiments on
CoNb2O6 are discussed.


  This paper introduces a Continuously Variable Series Reactor (CVSR) to the
transmission expansion planning (TEP) problem. The CVSR is a FACTS-like device
which has the capability of controlling the overall impedance of the
transmission line. However, the cost of the CVSR is about one tenth of a
similar rated FACTS device which potentially allows large numbers of devices to
be installed. The multi-stage TEP with the CVSR considering the $N-1$ security
constraints is formulated as a mixed integer linear programming model. The
nonlinear part of the power flow introduced by the variable reactance is
linearized by a reformulation technique. To reduce the computational burden for
a practical large scale system, a decomposition approach is proposed. The
detailed simulation results on the IEEE 24-bus and a more practical Polish
2383-bus system demonstrate the effectiveness of the approach. Moreover, the
appropriately allocated CVSRs add flexibility to the TEP problem and allow
reduced planning costs. Although the proposed decomposition approach cannot
guarantee global optimality, a high level picture of how the network can be
planned reliably and economically considering CVSR is achieved.


  The Perceiver makes few architectural assumptions about the relationship
among its inputs with quadratic scalability on its memory and computation time.
Indeed, the Perceiver model outpaces or is competitive with ResNet-50 and ViT
in terms of accuracy to some degree. However, the Perceiver does not take
predictive uncertainty and calibration into account. The Perceiver also
generalizes its performance on three datasets, three models, one evaluation
metric, and one hyper-parameter setting. Worst of all, the Perceiver's relative
performance improvement against other models is marginal. Furthermore, its
reduction of architectural prior is not substantial; is not equivalent to its
quality. Thereby, I invented five mutations of the Perceiver, the
Uncertainty-Aware Perceivers, that obtain uncertainty estimates and measured
their performance on three metrics. Experimented with CIFAR-10 and CIFAR-100,
the Uncertainty-Aware Perceivers make considerable performance enhancement
compared to the Perceiver.


  The Exponential-family Random Graph Model (ERGM) is a powerful model to fit
networks with complex structures. However, for dynamic valued networks whose
observations are matrices of counts that evolve over time, the development of
the ERGM framework is still in its infancy. To facilitate the modeling of dyad
value increment and decrement, a Partially Separable Temporal ERGM is proposed
for dynamic valued networks. The parameter learning algorithms inherit
state-of-the-art estimation techniques to approximate the maximum likelihood,
by drawing Markov chain Monte Carlo (MCMC) samples conditioning on the valued
network from the previous time step. The ability of the proposed model to
interpret network dynamics and forecast temporal trends is demonstrated with
real data.


  Millimeter wave (mm-wave) communications is considered a promising technology
for 5G networks. Exploiting beamforming gains with large-scale antenna arrays
to combat the increased path loss at mm-wave bands is one of its defining
features. However, previous works on mm-wave network analysis usually adopted
oversimplified antenna patterns for tractability, which can lead to significant
deviation from the performance with actual antenna patterns. In this paper,
using tools from stochastic geometry, we carry out a comprehensive
investigation on the impact of directional antenna arrays in mm-wave networks.
We first present a general and tractable framework for coverage analysis with
arbitrary distributions for interference power and arbitrary antenna patterns.
It is then applied to mm-wave ad hoc and cellular networks, where two
sophisticated antenna patterns with desirable accuracy and analytical
tractability are proposed to approximate the actual antenna pattern. Compared
with previous works, the proposed approximate antenna patterns help to obtain
more insights on the role of directional antenna arrays in mm-wave networks. In
particular, it is shown that the coverage probabilities of both types of
networks increase as a non-decreasing concave function with the antenna array
size. The analytical results are verified to be effective and reliable through
simulations, and numerical results also show that large-scale antenna arrays
are required for satisfactory coverage in mm-wave networks.


  Exascale systems will suffer failures hourly. HPC programmers rely mostly on
application-level checkpoint and a global rollback to recover. In recent years,
techniques reducing the number of rolling back processes have been implemented
via message logging. However, the log-based approaches have weaknesses, such as
being dependent on complex modifications within an MPI implementation, and the
fact that a full restart may be required in the general case. To address the
limitations of all log-based mechanisms, we return to checkpoint-only
mechanisms, but advocate data-flow-driven recovery (DFR), a fundamentally
different approach relying on analysis of the data flow of iterative codes, and
the well-known concept of data-flow graphs. We demonstrate the effectiveness of
DFR for an MPI stencil code to optimise rollback and reduce the overall energy
consumption by 10-12 % on idling nodes during localised rollback. We also
provide large-scale estimates for the energy savings of DFR compared to global
rollback, which for stencil codes increase as n square for a process count n.


  (Abridged) The rest-frame near-IR spectra of intermediate age (1-2 Gyr)
stellar populations are dominated by carbon based absorption features offering
a wealth of information. Yet, spectral libraries that include the near-IR
wavelength range do not sample a sufficiently broad range of ages and
metallicities to allow for accurate calibration of stellar population models
and thus the interpretation of the observations. In this paper we investigate
the integrated J- and H-band spectra of six intermediate age (1-3 Gyr) and old
(>10 Gyr) globular clusters in the Large Magellanic Cloud, using observations
obtained with the SINFONI IFU at the VLT. H-band C2 and K-band 12CO(2-0)
feature strengths are compared to the models of Maraston (2005). C2 is
reasonably well reproduced by the models at all ages, while 12CO(2-0) shows
good agreement for older (age>2 Gyr) populations, but the younger (1.3 Gyr)
globular clusters do not follow the models. We argue that this is due to the
fact that the empirical calibration of the models relies on only a few Milky
Way carbon star spectra, which show different 12CO(2-0) index strengths than
the LMC stars. The C2 absorption feature strength correlates strongly with age.
It is present essentially only in populations that have 1-2 Gyr old stars,
while its value is consistent with zero for older populations. The distinct
spectral energy distribution observed for the intermediate age globular
clusters in the J- and H-bands agrees well with the model predictions of
Maraston for the contribution from the thermally pulsing asymptotic giant
branch phase (TP-AGB). We show that the H-band C2 absorption feature and the
J-, H-band spectral shape can be used as an age indicator for intermediate age
stellar populations in integrated spectra of star clusters and galaxies.


  Given a sample from a multivariate distribution $F$, the uniform random
variates generated independently and rearranged in the order specified by the
componentwise ranks of the original sample look like a sample from the copula
of $F$. This idea can be regarded as a variant on Baker's [J. Multivariate
Anal. 99 (2008) 2312--2327] copula construction and leads to the definition of
the empirical beta copula. The latter turns out to be a particular case of the
empirical Bernstein copula, the degrees of all Bernstein polynomials being
equal to the sample size.
  Necessary and sufficient conditions are given for a Bernstein polynomial to
be a copula. These imply that the empirical beta copula is a genuine copula.
Furthermore, the empirical process based on the empirical Bernstein copula is
shown to be asymptotically the same as the ordinary empirical copula process
under assumptions which are significantly weaker than those given in Janssen,
Swanepoel and Veraverbeke [J. Stat. Plan. Infer. 142 (2012) 1189--1197].
  A Monte Carlo simulation study shows that the empirical beta copula
outperforms the empirical copula and the empirical checkerboard copula in terms
of both bias and variance. Compared with the empirical Bernstein copula with
the smoothing rate suggested by Janssen et al., its finite-sample performance
is still significantly better in several cases, especially in terms of bias.


  A four-band exciton Hamiltonian is constructed starting from the
single-particle Dirac Hamiltonian for charge carriers in monolayer transition
metal dichalcogenides (TMDs). The angular part of the exciton wave function can
be separated from the radial part, in the case of zero center of mass momentum
excitons, by exploiting the eigenstates of the total exciton angular momentum
operator with which the Hamiltonian commutes. We explain why this approach
fails for excitons with finite center of mass momentum or in the presence of a
perpendicular magnetic field and present an approximation to resolve this
issue. We calculate the (binding) energy and average interparticle distance of
different excited exciton states in different TMDs and compare these with
results available in the literature. Remarkably, we find that the intervalley
exciton ground state in the $\mp K$ valley has angular momentum $j=\pm1$, which
is due to the pseudospin of the separate particles. The exciton mass and the
exciton Landau levels are calculated and we find that the degeneracy of exciton
states with opposite relative angular momentum is altered by a magnetic field.


  Orbifold compactifications of 10D heterotic strings do allow different sets
of chiral fermions at different fixed points. Even if the effective 4D theory
is anomaly free by including the bulk fermions, there arise abelian and
nonabelian fixed point anomalies from these chiral fermions. As the underlying
string theory is well defined these localized fixed point anomalies of the
chiral fermions are to be cancelled by a variant of the Green-Schwarz
mechanism.


  It has been recently suggested that the Bose-Einstein condensate formed by
excitons in the dilute limit must be dark, i.e., not coupled to photons. Here,
we show that, under a density increase, the dark exciton condensate must
acquire a bright component due to carrier exchange in which dark excitons turn
bright. This however requires a density larger than a threshold which seems to
fall in the forbidden region of the phase separation between a dilute exciton
gas and a dense electron-hole plasma. The BCS-like condensation which is likely
to take place on the dense side, must then have a dark and a bright component -
which makes it "gray". It should be possible to induce an internal Josephson
effect between these two coherent components, with oscillations of the
photoluminescence as a strong proof of the existence for this "gray" BCS-like
exciton condensate.


  Quantum technologies, including quantum computing, cryptography, and sensing,
among others, are set to revolutionize sectors ranging from materials science
to drug discovery. Despite their significant potential, the implications for
public health have been largely overlooked, highlighting a critical gap in
recognition and preparation. This oversight necessitates immediate action, as
public health remains largely unaware of quantum technologies as a tool for
advancement. The application of quantum principles to epidemiology and health
informatics, termed quantum health epidemiology and quantum health informatics,
has the potential to radically transform disease surveillance, prediction,
modeling, and analysis of health data. However, there is a notable lack of
quantum expertise within the public health workforce and educational pipelines.
This gap underscores the urgent need for the development of quantum literacy
among public health practitioners, leaders, and students to leverage emerging
opportunities while addressing risks and ethical considerations. Innovative
teaching methods, such as interactive simulations, games, visual models, and
other tailored platforms, offer viable solutions for bridging knowledge gaps
without the need for advanced physics or mathematics. However, the opportunity
to adapt is fleeting as the quantum era in healthcare looms near. It is
imperative that public health urgently focuses on updating its educational
approaches, workforce strategies, data governance, and organizational culture
to proactively meet the challenges of quantum disruption thereby becoming
quantum ready.


  I estimate the semi-elasticity of blood donations with respect to a monetary
benefit, namely the waiver of user fees when using the National Health Service,
in Portugal. Using within-county variation over time in the value of the
benefitI estimate both the unconditional elasticity, which captures overall
response of the market, and the conditional elasticity, which holds constant
the number of blood drives. This amounts to fixing a measure of the cost of
donation to the blood donor. I instrument for the number of blood drives, which
is endogenous, using a variable based on the number of weekend days and the
proportion of blood drives on weekends. A one euro increase in the subsidy
leads 1.8% more donations per 10000 inhabitants, conditional on the number of
blood drives. The unconditional effect is smaller. The benefit does not attract
new donors, instead it fosters repeated donation. Furthermore, the
discontinuation of the benefit lead to a predicted decrease in donations of
around 18%, on average. However, I show that blood drives have the potential to
effectively substitute monetary incentives in solving market imbalances.


  Recent deep inelastic results from the H1 collaboration are presented. The
topics covered include inclusive diffractive physics, the determination of
alpha_S using the event shapes, the study of the hadronic final state at low x
with single particles and with jets, the structure function measurements in
particular F_2 at low Q^2 and the high Q^2 physics both in neutral and charged
current.


  Absorbing boundary conditions in the form of a complex absorbing potential
are routinely introduced in the Schr\"odinger equation to limit the
computational domain or to study reactive scattering events using the
multi-configurational time-dependent Hartree method (MCTDH). However, it is
known that a pure wave-function description does not allow the modeling and
propagation of the remnants of a system of which some parts are removed by the
absorbing boundary. It was recently shown [S. Selst{\o} and S. Kvaal, J. Phys.
B: At. Mol. Opt. Phys. {\bfseries 43} (2010), 065004] that a master equation of
Lindblad form was necessary for such a description. We formulate a
multiconfigurational time-dependent Hartree method for this master equation,
usable for any quantum system composed of any mixture of species. The
formulation is a strict generalization of pure-state propagation using standard
MCTDH. We demonstrate the formulation with a numerical experiment.


  We introduce two new estimators of the bivariate Hurst exponent in the
power-law cross-correlations setting -- the cross-periodogram and local
$X$-Whittle estimators -- as generalizations of their univariate counterparts.
As the spectrum-based estimators are dependent on a part of the spectrum taken
into consideration during estimation, a simulation study showing performance of
the estimators under varying bandwidth parameter as well as correlation between
processes and their specification is provided as well. The newly introduced
estimators are less biased than the already existent averaged periodogram
estimator which, however, has slightly lower variance. The spectrum-based
estimators can serve as a good complement to the popular time domain
estimators.


  Let $(X, Y)$ be a suitable couple of quasi-Banach lattices of measurable
functions on $\mathbb T \times \Omega$, and let $(X_A, Y_A)$ be the couple of
the corresponding Hardy-type spaces. It has long been suspected that the
BMO-regularity property of $(X, Y)$ is not only sufficient for the $\mathrm
K$-closedness of $(X_A, Y_A)$ in $(X, Y)$ but also necessary. We establish the
equivalence of these two properties for a general couple of Banach lattices
having the Fatou property when $\Omega$ is a discrete measurable space, and
also for couples $(X, Y)$ where $X$ is allowed to be quasi-Banach but $Y$ is
assumed to be $p$-convex with some $p > 1$ (here $\Omega$ is arbitrary). We
show under certain mild restrictions that the "good interpolation" formula $$
\left(X_A, \mathrm H_q\right)_{\theta, p} = \left[\left(X, \mathrm
L_q\right)_{\theta, p}\right]_A $$ holds true if and only if $X$ is
BMO-regular.


  This paper is the manual of the CompOSE service, see http://compose.obspm.fr,
an equation of state (EoS) database for use in nuclear physics and in
astrophysical applications, e.g. the simulation of core-collapse supernovae and
compact stars. The main aims of the service are the following: to offer a
robust, easily extendable data format to store and read EoS data tables and
related physical quantities; to make these data available to the public --
respecting the original work by the contributors -- in a standard format
designed for easy access and flexibility; and to provide routines to
interpolate these data in the parameter space of density, temperature and
hadronic charge fraction. The manual contains a detailed description of the
service. It is divided into three parts, containing a general introduction as
well as instructions for potential contributors and for users.


  We introduce a new permutation statistic, namely, the number of cycles of
length $q$ consisting of consecutive integers, and consider the distribution of
this statistic among the permutations of $\{1,2,...,n\}$. We determine explicit
formulas, recurrence relations, and ordinary and exponential generating
functions. A generalization to more than one fixed length is also considered.


  A magnetostatic spin wave analog of integer quantum Hall (IQH) state is
proposed in realistic patterned ferromagnetic thin films. Due to magnetic shape
anisotropy, magnetic moments in a thin film lie within the plane, while all
spin-wave excitations are fully gapped. Under an out-of-plane magnetic field,
the film acquires a finite magnetization, where some of the gapped magnons
become significantly softened near a saturation field. It is shown that, owing
to a spin-orbit locking nature of the magnetic dipolar interaction, these soft
spin-wave volume-mode bands become chiral volume-mode bands with finite
topological Chern integers. A bulk-edge correspondence in IQH physics suggests
that such volume-mode bands are accompanied by a chiral magnetostatic spin-wave
edge mode. The existence of the edge mode is justified both by micromagnetic
simulations and by band calculations based on a linearized Landau-Lifshitz
equation. Employing intuitive physical arguments, we introduce proper
tight-binding models for these soft volume-mode bands. Based on the
tight-binding models, we further discuss possible applications to other systems
such as magnetic ultrathin films with perpendicular magnetic anisotropy (PMA).


  We propose a general extended coherent state approach to the qubit (or
fermion) and multi-mode boson coupling systems. The application to the
spin-boson model with the discretization of a bosonic bath with arbitrary
continuous spectral density is described in detail, and very accurate solutions
can be obtained. The quantum phase transition in the nontrivial sub-Ohmic case
can be located by the fidelity and the order-parameter critical exponents for
the bath exponents $s<1/2$ can be correctly given by the fidelity
susceptibility, demonstrating the strength of the approach.


  The period doubling renormalization operator was introduced by M. Feigenbaum
and by P. Coullet and C. Tresser in the nineteen-seventieth to study the
asymptotic small scale geometry of the attractor of one-dimensional systems
which are at the transition from simple to chaotic dynamics. This geometry
turns out to not depend on the choice of the map under rather mild smoothness
conditions. The existence of a unique renormalization fixed point which is also
hyperbolic among generic smooth enough maps plays a crucial role in the
corresponding renormalization theory. The uniqueness and hyperbolicity of the
renormalization fixed point were first shown in the holomorphic context, by
means that generalize to other renormalization operators. It was then proved
that in the space of $C^{2+\alpha}$ unimodal maps, for $\alpha$ close to one,
the period doubling renormalization fixed point is hyperbolic as well. In this
paper we study what happens when one approaches from below the minimal
smoothness thresholds for the uniqueness and for the hyperbolicity of the
period doubling renormalization generic fixed point. Indeed, our main results
states that in the space of $C^2$ unimodal maps the analytic fixed point is not
hyperbolic and that the same remains true when adding enough smoothness to get
a priori bounds. In this smoother class, called $C^{2+|\cdot|}$ the failure of
hyperbolicity is tamer than in $C^2$. Things get much worse with just a bit
less of smoothness than $C^2$ as then even the uniqueness is lost and other
asymptotic behavior become possible. We show that the period doubling
renormalization operator acting on the space of $C^{1+Lip}$ unimodal maps has
infinite topological entropy.


  The emergence and nature of amplitude mediated chimera states,
spatio-temporal patterns of co-existing coherent and incoherent regions, are
investigated for a globally coupled system of active and inactive
Ginzburg-Landau oscillators. The existence domain of such states is found to
shrink and shift in parametric space as the fraction of inactive oscillators is
increased. The role of inactive oscillators is found to be two fold - they get
activated to form a separate region of coherent oscillations and in addition
decrease the common collective frequency of the coherent regions by their
presence. The dynamical origin of these effects is delineated through a
detailed bifurcation analysis of a reduced model equation that is based on a
mean field approximation. Our results may have practical implications for the
robustness of such states in biological or physical systems where age related
deterioration in the functionality of components can occur.


  We review recent progress in modeling credit risk for correlated assets. We
start from the Merton model which default events and losses are derived from
the asset values at maturity. To estimate the time development of the asset
values, the stock prices are used whose correlations have a strong impact on
the loss distribution, particularly on its tails. These correlations are
non-stationary which also influences the tails. We account for the asset
fluctuations by averaging over an ensemble of random matrices that models the
truly existing set of measured correlation matrices. As a most welcome side
effect, this approach drastically reduces the parameter dependence of the loss
distribution, allowing us to obtain very explicit results which show
quantitatively that the heavy tails prevail over diversification benefits even
for small correlations. We calibrate our random matrix model with market data
and show how it is capable of grasping different market situations.
Furthermore, we present numerical simulations for concurrent portfolio risks,
i.e., for the joint probability densities of losses for two portfolios. For the
convenience of the reader, we give an introduction to the Wishart random matrix
model.


  Memory constraint of always-on devices is one of the major concerns when
deploying speech processing models on these devices. While larger models
trained with sufficiently large amount of data generally perform better, making
them fit in the device memory is a demanding challenge. In this paper, we aim
to reduce model size by reparameterizing model weights across Transformer
encoder layers and assuming a special weight composition and structure. More
specifically, inspired by ResNet and the more recent LoRA work, we propose an
approach named ResidualTransformer, where each weight matrix in a Transformer
layer comprises 1) a shared full-rank component with its adjacent layers, and
2) a unique low-rank component to itself. The low-rank matrices only account
for a small amount of model size increase. In addition, we add diagonal weight
matrices to improve modeling capacity of the low-rank matrices. Experiments of
our 10k-hour speech recognition and speech translation tasks show that the
Transformer encoder size can be reduced by ~3X with very slight performance
degradation.


  We report on the measurement of the time required for a wave packet to tunnel
through the potential barriers of an optical lattice. The experiment is carried
out by loading adiabatically a Bose-Einstein condensate into a 1D optical
lattice. A sudden displacement of the lattice by a few tens of nm excites the
micromotion of the dipole mode. We then directly observe in momentum space the
splitting of the wave packet at the turning points and measure the delay
between the reflected and the tunneled packets for various initial
displacements. Using this atomic beam splitter twice, we realize a chain of
coherent micron-size Mach-Zehnder interferometers at the exit of which we get
essentially a wave packet with a negative momentum, a result opposite to the
prediction of classical physics.


  The calculation of mass outflow rates of AGN winds is of great importance in
understanding the role that such winds play in AGN-galaxy feedback processes.
The mass outflow rates are, however, difficult to estimate since the volume
filling factors of the winds are unknown. In this paper, we use constraints
imposed by the observed radio emission to obtain upper limits to the volume
filling factors of wind components in certain nearby AGN. We do this by
predicting the 1.4 GHz radio flux densities emitted by those components,
assuming a uniform wind, and then comparing these with the observed flux
densities for each AGN at this frequency. We find that the upper limits to the
volume filling factors are in the range 10^{-4}-0.5.


  The eccentricity (anti-adjacency) matrix $\varepsilon(G)$ of a graph $G$ is
obtained from the distance matrix by retaining the eccentricities in each row
and each column. This matrix is first defined in 2018 by Wang et al. \cite{1}.
In this paper we have characterized the graphs which have at most one (hence
exactly) positive eigenvalue of $\varepsilon(G)$.


  The effect of aberrations on the aperture efficiency has not been discussed
analytically, though aberrations determine the performance of a wide
field-of-view system. Expansion of a wavefront error and a feed pattern into a
series of the Zernike polynomials enables us to calculate the aperture
efficiency. We explicitly show the aperture efficiency affected by the Seidel
aberrations and derive the conditions for reducing the effects of the spherical
aberration and coma. In particular, the condition for coma can reduce a
pointing error. We performed Physical Optics simulations and found that, if the
Strehl ratio is higher than 0.8, the derived expression provides the aperture
efficiencies with a precision of < 2%.


  An open challenge in physics is to expand the frontiers of the validity of
quantum mechanics by evidencing nonclassicality of the centre of mass state of
a macroscopic object. Yet another equally important task is to evidence the
essential nonclassicality of the interactions which act between macroscopic
objects. Here we introduce a new tool to meet these challenges: massive spatial
qubits. In particular, we show that if two distinct localized states of a mass
are used as the $|0\rangle$ and $|1\rangle$ states of a qubit, then we can
measure this encoded spatial qubit with a high fidelity in the $\sigma_x,
\sigma_y$ and $\sigma_z$ bases simply by measuring its position after different
durations of free evolution. We show how this technique can be used to reveal
an irreducible nonclassicality through a Bell-inequality violation arising from
the entanglement of the centre of mass of a nano-crystal with its spin in a
Stern-Gerlach setup. Secondly, we show how our methodology, in conjuction with
the Casimir interaction, offers a powerful method to create and certify
non-Gaussian entanglement between two neutral nano-objects. Fundamentally, the
generation of such an entanglement provides an empirical means for
demonstrating an inherent quantumness of the Casimir interaction.


  We propose new conjectures about the relationship between the principal
blocks of finite groups for different primes and establish evidence for these
conjectures.


  The origin of the metamagnetic antiferromagnetic-ferromagnetic phase
transition of FeRh is a subject of much debate. Competing explanations invoke
magnetovolume effects and purely ther- modynamic transitions within the spin
system. It is experimentally difficult to observe the changes in the magnetic
system and the lattice simultaneously, leading to differing conclusions over
which mechanism is responsible for the phase transition. A non-collinear
electronic structure study by Mryasov [O.N. Mryasov, Phase Transitions 78, 197
(2005)] showed that non-linear behavior of the Rh moment leads to higher order
exchange terms in FeRh. Using atomistic spin dynamics (ASD) we demonstrate that
the phase transition can occur due to the competition between bilinear and the
higher order four spin exchange terms in an effective spin Hamiltonian. The
phase transition we see is of first order and shows thermal hysteresis in
agreement with experimental observations. Simulating sub-picosecond laser
heating we show an agreement with pump-probe experiments with a ferromagnetic
response on a picosecond timescale.


  Anomaly detection, a critical facet in data analysis, involves identifying
patterns that deviate from expected behavior. This research addresses the
complexities inherent in anomaly detection, exploring challenges and adapting
to sophisticated malicious activities. With applications spanning
cybersecurity, healthcare, finance, and surveillance, anomalies often signify
critical information or potential threats. Inspired by the success of Anomaly
Generative Adversarial Network (AnoGAN) in image domains, our research extends
its principles to tabular data. Our contributions include adapting AnoGAN's
principles to a new domain and promising advancements in detecting previously
undetectable anomalies. This paper delves into the multifaceted nature of
anomaly detection, considering the dynamic evolution of normal behavior,
context-dependent anomaly definitions, and data-related challenges like noise
and imbalances.


  Recently, the solid-state frustrated Lewis pairs (FLPs) on the surface of
CeO2 have been demonstrated to effectively catalyze the selective hydrogenation
of unsaturated substrates, hence, the relationship between their intrinsic
properties and H2 activation at the atomic scale has attracted great attention.
In this work, the effects of Cu doping on the intrinsic FLPs properties for
different facets of CeO2 is investigated by using density functional theory
calculations, including the geometric parameters between Lewis acid-base
centers, and the reactivity of Lewis acid-base towards H2 activation. The study
demonstrates that introducing O vacancies on different crystal facets of CeO2
creates FLPs with the ability to efficiently cleavage hydrogen molecules. After
the substitution of Ce with Cu, the inadequate electron availability of Cu to
bond with O contributes to a reduction in the formation energy of O vacancies.
Importantly, Cu exert an influence not only on the intrinsic properties of FLPs
but also on the formation of new Ce-O and Cu-O FLPs. Considering the H2
activation, the doping of Cu results in an enhancement for the thermodynamics
by decreasing the reaction energies, while a hinderance for the kinetics by
increasing the energy barriers. Overall, with these theoretical investigations,
we propose certain hints for the future experimental studies concerning the
synthesis of Cu doped CeO2 catalysts for the H2 activation and hydrogenation
reactions.


  In recent years, using drone, also known as unmanned aerial vehicle (UAV), in
close-distance visual inspection has became an active area in many disciplines.
However, many challenges still remain before we can achieve autonomous
inspection, especially when inspecting complex structures. The complex civil
structures, such as bridges, dams and wind turbines, are large-scale and
geometrical complicated. It requires sophisticated path planning algorithms to
achieve close-distance inspection and, at the same time, avoid collisions. In
practice, directly deploying the path planning result on such structures is
error prone, costly, and full of hazards. In this paper, rely on micro
quadrotor UAV, the authors present an affordable experimental platform for
testing drone-based path planning result. The platform allows the users to
conduct many path planning experiments at any time without worrying expensive
and time consuming outdoor test flying. This platform is developed based on the
bundle of Crazyflie, which includes Crazyflie 2.0 quadrotor, Crazyradio and
loco positioning system (LPS). Equipped with an onboard micro FPV camera, the
visual data can be lively streamed to the host computer during flight. The
functions of manual configuration and waypoints control are explicitly designed
in this platform to increase its flexibility and performance on path following
and debugging. To evaluate the practicability of the proposed test platform,
two existing drone-based path planning algorithms are tested. The results show
that even though certain level of error existed, the quality of visual data and
accuracy of path following are high enough for simulating most practical
inspection applications.


  Compressive spectral imaging (CSI) has emerged as an alternative spectral
image acquisition technology, which reduces the number of measurements at the
cost of requiring a recovery process. In general, the reconstruction methods
are based on hand-crafted priors used as regularizers in optimization
algorithms or recent deep neural networks employed as an image generator to
learn a non-linear mapping from the low-dimensional compressed measurements to
the image space. However, these data-driven methods need many spectral images
to obtain good performance. In this work, a deep recovery framework for CSI
without training data is presented. The proposed method is based on the fact
that the structure of some deep neural networks and an appropriated
low-dimensional structure are sufficient to impose a structure of the
underlying spectral image from CSI. We analyzed the low-dimension structure via
the Tucker representation, modeled in the first net layer. The proposed scheme
is obtained by minimizing the $\ell_2$-norm distance between the compressive
measurements and the predicted measurements, and the desired recovered spectral
image is formed just before the forward operator. Simulated and experimental
results verify the effectiveness of the proposed method.


  Potentials play an important role in solving boundary value problems for
elliptic equations. In the middle of the last century, a potential theory was
constructed for a two-dimensional elliptic equation with one singular
coefficient. In the study of potentials, the properties of the fundamental
solutions of the given equation are essentially and fruitfully used. At the
present time, fundamental solutions of a three-dimensional elliptic equation
with one degeneration line are already known. In this paper, we investigate the
double- and simple-layer potentials for this kind of elliptic equations.
Results from potential theory allow us to represent the solution of the
boundary value problems in integral equation form. By using some properties of
Gaussian hypergeometric function, we prove limiting theorems and derive
integral equations concerning a densities of the double- and simple-layer
potentials. The obtained results are applied to find an explicit solution of
the Dirichlet and Holmgren problems for the three-dimensional singular elliptic
equation in the half of the ball.


  Interest in the inference of evolutionary networks relating species or
populations has grown with the increasing recognition of the importance of
hybridization, gene flow and admixture, and the availability of large-scale
genomic data. However, what network features may be validly inferred from
various data types under different models remains poorly understood. Previous
work has largely focused on level-1 networks, in which reticulation events are
well separated, and on a general network's tree of blobs, the tree obtained by
contracting every blob to a node. An open question is the identifiability of
the topology of a blob of unknown level. We consider the identifiability of the
circular order in which subnetworks attach to a blob, first proving that this
order is well-defined for outer-labeled planar blobs. For this class of blobs,
we show that the circular order information from 4-taxon subnetworks identifies
the full circular order of the blob. Similarly, the circular order from 3-taxon
rooted subnetworks identifies the full circular order of a rooted blob. We then
show that subnetwork circular information is identifiable from certain data
types and evolutionary models. This provides a general positive result for
high-level networks, on the identifiability of the ordering in which taxon
blocks attach to blobs in outer-labeled planar networks. Finally, we give
examples of blobs with different internal structures which cannot be
distinguished under many models and data types.


  We study deterministic extractors for oblivious bit-fixing sources (a.k.a.
resilient functions) and exposure-resilient functions with small min-entropy:
of the function's n input bits, k << n bits are uniformly random and unknown to
the adversary. We simplify and improve an explicit construction of extractors
for bit-fixing sources with sublogarithmic k due to Kamp and Zuckerman (SICOMP
2006), achieving error exponentially small in k rather than polynomially small
in k. Our main result is that when k is sublogarithmic in n, the short output
length of this construction (O(log k) output bits) is optimal for extractors
computable by a large class of space-bounded streaming algorithms.
  Next, we show that a random function is an extractor for oblivious bit-fixing
sources with high probability if and only if k is superlogarithmic in n,
suggesting that our main result may apply more generally. In contrast, we show
that a random function is a static (resp. adaptive) exposure-resilient function
with high probability even if k is as small as a constant (resp. log log n). No
explicit exposure-resilient functions achieving these parameters are known.