  We study a strongly correlated spin-1 Bose gas in 2D space by using the
projective construction. A spin-disordered superfluid state is constructed and
proposed as a candidate competing with the conventional polar condensate when
interaction is antiferromagnetic. This novel state has a non-trivial
topological order whose low energy excitations carry fractional spin, charge,
and statistics. The spin excitations become gapless only at the edge and are
described by level-1 SU(2) Kac-Moody algebra. The edge state is identical to
the edge state of the chiral spin liquid or the right moving sector of spin-1/2
chain.


  We prove a query complexity lower bound for $\mathsf{QMA}$ protocols that
solve approximate counting: estimating the size of a set given a membership
oracle. This gives rise to an oracle $A$ such that $\mathsf{SBP}^A \not\subset
\mathsf{QMA}^A$, resolving an open problem of Aaronson [2]. Our proof uses the
polynomial method to derive a lower bound for the $\mathsf{SBQP}$ query
complexity of the $\mathsf{AND}$ of two approximate counting instances. We use
Laurent polynomials as a tool in our proof, showing that the "Laurent
polynomial method" can be useful even for problems involving ordinary
polynomials.


  This work presents an effort to bridge the gap between abstract high level
programming and OpenCL by extending an existing high level Java programming
framework (APARAPI), based on OpenCL, so that it can be used to program FPGAs
at a high level of abstraction and increased ease of programmability. We run
several real world algorithms to assess the performance of the framework on
both a low end and a high end system. On the low end and high end systems
respectively we observed up to 78-80 percent power reduction and 4.8X-5.3X
speed increase running NBody simulation, as well as up to 65-80 percent power
reduction and 6.2X-7X speed increase for a KMeans, MapReduce algorithm running
on top of the Hadoop framework and APARAPI.


  This paper is concerned with time reversal in \emph{photoacoustic tomography}
(PAT) of dissipative media that are similar to water. Under an appropriate
condition, it is shown that the time reversal method in \cite{Wa11,AmBrGaWa11}
based on the non-causal thermo-viscous wave equation can be used if the
non-causal data is replaced by a \emph{time shifted} set of causal data. We
investigate a similar imaging functional for time reversal and an operator
equation with the time reversal image as right hand side. If required, an
enhanced image can be obtained by solving this operator equation. Although time
reversal (for noise-free data) does not lead to the exact initial pressure
function, the theoretical and numerical results of this paper show that
regularized time reversal in dissipative media similar to water is a valuable
method. We note that the presented time reversal method can be considered as an
alternative to the causal approach in \cite{KaSc13} and a similar operator
equation may hold for their approach.


  It is well-known that the circular flow number of a bridgeless cubic graph
can be computed in terms of certain partitions of its vertex-set with
prescribed properties. In the present paper, we first study some of these
properties that turn out to be useful in order to design a more efficient
algorithm for the computation of the circular flow number of a bridgeless cubic
graph. Using this algorithm, we determine the circular flow number of all
snarks up to 36 vertices as well as the circular flow number of various famous
snarks. After that, as combination of the use of our algorithm with new
theoretical results, we present an infinite family of snarks of order $8k+2$
whose circular flow numbers meet a general lower bound presented by Lukot'ka
and Skoviera in 2008. In particular, this answers a question proposed in their
paper. Moreover, we improve the best known upper bound for the circular flow
number of Goldberg snarks and we conjecture that this new upper bound is
optimal. Finally, we discuss a possible extension to the computation of the
circular flow number in the non-regular case.


  Analyzed is the effective potential of D-dimensional thermodynamic
Gross-Neveu model (defined by large-N leading order, $2\leq D<4$) under
constant electromagnetic field ($\vec{E}\cdot\vec{B}=0$). The potential is
derived from a thermal analogy of the worldline formalism. In the magnetic
case, the potential is expressed in terms of a discretized momentum sum instead
of a continuum momentum integral, and it reproduces known critical values of
$\mu$ and $T$ in the continuum limit. In the electric case, chiral symmetry is
restored at finite $T$ (with arbitrary $\mu$) against instability of fermion
vacuum. An electromagnetic duality is pointed out as well. Phase diagrams are
obtained in both cases.


  Single crystals of La_1.8Sr_0.2CuO_4-\delta grown by the travelling solvent
floating zone method have been ground to spherical shape for studies of
anisotropic supercondcucting properties by SQUID magnetometry. Here we report
on magnetization measurements parallel and perpendicular to the c-axis on two
of these crystals. At low enough temperatures and fields the spheres are
perfectly shielding (susceptibility -1.5 [SI]) and thus magnetically isotropic.
The field dependence of the critical temperature, the transition width and the
field expulsion well below T_c is qualitatively similar in both samples and is
detailed in the paper. The anisotropy of the first critical field also shows
similar behavior for the two crystals. Magnetization vs field experiments
reveal a large difference in the hysteresis behavior along the two directions
and an enhancement of the critical current density through the CuO_2-planes
compared to the in-plane current density at higher fields.


  Hybrid materials, containing a 2D filler embedded in a polymeric matrix, are
an interesting platform for several applications, because of the variety of
properties that the filler can impart to the polymer matrix when dispersed at
the nanoscale. Moreover, novel properties could arise from the interaction
between the two. Mostly the bulk properties of these materials have been
studied so far, especially focusing on how the filler changes the polymeric
matrix properties. Here we propose a complete change of perspective by using
the hybrid nanocomposite material as a platform suitable to engineer the
properties of the filler and to exploit its potential in the fabrication of
devices. As a proof of concept of the versatility and potentiality of the new
method, we applied this approach to prepare black phosphorus nanocomposites
through its dispersion in poly (methyl methacrylate). Black phosphorus is a
very interesting 2D material, whose application have so far been limited by its
very high reactivity to oxygen and water. In this respect, we show that
electronic-grade black phosphorus flakes, already embedded in a protecting
matrix since their exfoliation from the bulk material, are endowed with
significant increased stability, and can be further processed into devices
without degrading their properties.


  Radio frequency (RF) wireless power transfer (WPT) is a promising technology
for 6G use cases. It enables a massive, yet sustainable deployment of
batteryless energy neutral (EN) devices at unprecedented scale. Recent research
on 6G is exploring high operating frequencies up to the THz spectrum, where
antenna arrays with large apertures are capable of forming narrow, "laser-like"
beams. At sub-10 GHz frequencies, physically large antenna arrays are
considered that are operating in the array near field. Transmitting spherical
wavefronts, power can be focused in a focal point rather than a beam, which
allows for efficient and radiation-safe WPT. We formulate a multipath channel
model comprising specular components and diffuse scattering to find the WPT
power budget in a realistic indoor scenario. Specular components can be
predicted by means of a geometric model. This is used to transmit power via
multiple beams simultaneously, increasing the available power budget and
expanding the initial access distance. We show that exploiting this "beam
diversity" reduces the required fading margin for the initial access to EN
devices.


  In this paper, we studied the semileptonic $B/B_s \to (D^{(*)},D_s^{(*)})
l\nu_l$ decays in the framework of the standard model (SM) , by employing the
perturbative QCD (PQCD) factorization formalism combining with the lattice QCD
inputs of the relevant transition form factors. We calculated the branching
ratios ${\cal B}(B_{(s)} \to D_{(s)}^{(*)} l \nu_l )$ with $l=(e,\mu.\tau)$ ,
the ratios of the branching ratios $R(D^{(*)})$ and $R(D_s^{(*)} )$ and other
physical observables $P_\tau(D_{(s)}^{(*)})$, $F_L(D^*_{(s)})$ and
$A_{FB}(\tau)$. The "PQCD+Lattice" predictions for ${\cal B}(B \to D^{(*)}
l\nu_l)$ and $R(D^{(*)})$ do agree well with those currently available
experimental measurements within the errors. For the ratios $R(D_s)$ and
$R(D_s^*)$, the "PQCD+Lattice" predictions agree well with other known
predictions. For both $P_\tau(D^*)$ and $F_L(D^*)$, our theoretical predictions
agree well with the measured values within errors. Our theoretical predictions
about the considered semileptonic $B/B_s$ decays could be tested in the near
future LHCb and the Belle II experiments.


  Results from a groundbased high contrast imaging survey of thirteen nearby
white dwarfs for substellar objects is presented. We place strict upper limits
on the type of substellar objects present, ruling out the presence of anything
larger than $\sim$14 M$_{Jup}$ for eight of the white dwarfs at separations
$>$19 AU and corresponding to primordial separations of $\sim$3-6~AU assuming
adiabatic mass loss without tidal interactions.
  With these results we place the first upper limit on the number of
intermediate mass stars with brown dwarfs at separations $>$ 13 AU. We combine
these results with previous work to place upper limits on the number of massive
Jovian ($>$ 10 M$_{Jup}$) planets in orbit around white dwarfs whose
progenitors spanned a mass range of 1-7 M$_{\odot}$.


  In this paper, we study the structure of the singular set for a $C^{1}$
smooth surface in the $3$-dimensional Heisenberg group $\boldsymbol{H}_{1}$. We
discover a Codazzi-like equation for the $p$-area element along the
characteristic curves on the surface. Information obtained from this ordinary
differential equation helps us to analyze the local configuration of the
singular set and the characteristic curves. In particular, we can estimate the
size and obtain the regularity of the singular set. We understand the global
structure of the singular set through a Hopf-type index theorem. We also
justify that Codazzi-like equation by proving a fundamental theorem for local
surfaces in $\boldsymbol{H}_{1}$.


  The Distributed Messaging Systems (DMSs) used in IoT systems require timely
and reliable data dissemination, which can be achieved through configurable
parameters. However, the high-dimensional configuration space makes it
difficult for users to find the best options that maximize application
throughput while meeting specific latency constraints. Existing approaches to
automatic software profiling have limitations, such as only optimizing
throughput, not guaranteeing explicit latency limitations, and resulting in
local optima due to discretizing parameter ranges. To overcome these
challenges, a novel configuration tuning system called DMSConfig is proposed
that uses machine learning and deep reinforcement learning. DMSConfig interacts
with a data-driven environment prediction model, avoiding the cost of online
interactions with the production environment. DMSConfig employs the deep
deterministic policy gradient (DDPG) method and a custom reward mechanism to
make configuration decisions based on predicted DMS states and performance.
Experiments show that DMSConfig performs significantly better than the default
configuration, is highly adaptive to serve tuning requests with different
latency boundaries, and has similar throughput to prevalent parameter tuning
tools with fewer latency violations.


  Research in Mobile Location-Based Crowdsourcing is hindered by a marked lack
of real-world data. The development of a standardized, lightweight, easily
deployable, modular, composable, and most of all, scalable experimentation
framework would go a long way in facilitating such research. Conveniently,
these are all salient characteristics of systems developed using a
microservices approach. We propose QRowdsource - a MLBC experimentation
framework built using a distributed services architecture. In this paper, we
discuss the design and development of QRowdsource, from the decomposition of
functional components to the orchestration of services within the framework. We
also take a look at how the advantages and disadvantages of using a
microservices approach translate to our specific use case and deliberate over a
number of lessons learned while developing the experimentation framework.


  [abridged]
  Aims. The aim of the present paper is to provide new and more detailed
relations at the kpc scale between the gas surface density and the face-on
optical depth directly calibrated on galaxies, in order to compute the
attenuation not only for semi-analytic models but also observationally as new
and upcoming radio observatories are able to trace gas ever farther in the
Universe.
  Methods. We have selected a sample of 4 nearby resolved galaxies and a sample
of 27 unresolved galaxies from the Herschel Reference Survey and the Very
Nearby Galaxies Survey, for which we have a large set of multi-wavelength data
from the FUV to the FIR including metallicity gradients for resolved galaxies,
along with radio HI and CO observations. For each pixel in resolved galaxies
and for each galaxy in the unresolved sample, we compute the face-on optical
depth from the attenuation determined with the CIGALE SED fitting code and an
assumed geometry. We determine the gas surface density from HI and CO
observations with a metallicity-dependent XCO factor.
  Results. We provide new, simple to use, relations to determine the face-on
optical depth from the gas surface density, taking the metallicity into
account, which proves to be crucial for a proper estimate. The method used to
determine the gas surface density or the face-on optical depth has little
impact on the relations except for galaxies that have an inclination over 50d.
Finally, we provide detailed instructions on how to compute the attenuation
practically from the gas surface density taking into account possible
information on the metallicity.
  Conclusions. Examination of the influence of these new relations on simulated
FUV and IR luminosity functions shows a clear impact compared to older oft-used
relations, which in turn could affect the conclusions drawn from studies based
on large scale cosmological simulations.


  We give a new interpretation for the super loop space that has been used to
formulate supersymmetry. The fermionic coordinates in the super loop space are
identified as the odd generators of the Weil algebra. Their bosonic
superpartners are the auxiliary fields. The general N=1 supermultiplet is
interpreted in terms of Weil algebras. As specific examples we consider
supersymmetric quantum mechanics, Wess-Zumino model and supersymmetric
Yang-Mills theory in four dimensions. Some comments on the formulation of
constrained systems and integrable models and non-Abelian localization are
given.


  Time series forecasting is essential for many practical applications, with
the adoption of transformer-based models on the rise due to their impressive
performance in NLP and CV. Transformers' key feature, the attention mechanism,
dynamically fusing embeddings to enhance data representation, often relegating
attention weights to a byproduct role. Yet, time series data, characterized by
noise and non-stationarity, poses significant forecasting challenges. Our
approach elevates attention weights as the primary representation for time
series, capitalizing on the temporal relationships among data points to improve
forecasting accuracy. Our study shows that an attention map, structured using
global landmarks and local windows, acts as a robust kernel representation for
data points, withstanding noise and shifts in distribution. Our method
outperforms state-of-the-art models, reducing mean squared error (MSE) in
multivariate time series forecasting by a notable 3.6% without altering the
core neural network architecture. It serves as a versatile component that can
readily replace recent patching based embedding schemes in transformer-based
models, boosting their performance.


  We defined generalized \delta-derivations of algebra A as linear mapping \chi
associated with usual \delta-derivation \phi by the rule
\chi(xy)=\delta(\chi(x)y+x\phi(y))=\delta(\phi(x)y+x\chi(y)) for any x,y \in A.
We described generalized \delta-derivations of prime alternative algebras,
prime Lie algebras and superalgebras, unital algebras, and semisimple
finite-dimensional Jordan superalgebras. In this cases we proved that
generalized \delta-derivation is a generalized derivation or \delta-derivation.
After that we described \delta-superderivations of superalgebras <<KKM
Double>>, arising from prime alternative algebras, prime Lie algebras and
superalgebras, unital algebras, and semisimple finite-dimensional Jordan
superalgebras. In the end, we constructed new examples of non-trivial
\delta-derivations of Lie algebras.


  As a dedicated solar radioheliograph, the MingantU SpEctral RadioHeliograph
(MUSER) has a maximum baseline of more than 3000 meters and a frequency range
of 400 MHz -- 15 GHz. According to the classical radio interferometry theory,
the non-coplanar baseline effect (i.e., w-term effect) would be considered and
calibrated for such a radio instrument. However, little previous literature
made the qualitative or quantitative analyses on w-term effects of solar
radioheliograph in-depth. This study proposes a complete quantitative analysis
of w-term effects for the MUSER. After a brief introduction of the MUSER, we
systematically investigate the baseline variations over a year and analyze the
corresponding variations of w-term. We further studied the effects of the
w-term in the imaging for the specified extended source, i.e., the Sun. We
discussed the possible effects of the w-term, such as image distortion and so
on. The simulated results show that the w-term is an essential and unavoidable
issue for solar radio imaging with high spatial resolution.


  With the increasing practicality of deep learning applications, practitioners
are inevitably faced with datasets corrupted by noise from various sources such
as measurement errors, mislabeling, and estimated surrogate inputs/outputs that
can adversely impact the optimization results. It is a common practice to
improve the optimization algorithm's robustness to noise, since this algorithm
is ultimately in charge of updating the network parameters. Previous studies
revealed that the first-order moment used in Adam-like stochastic gradient
descent optimizers can be modified based on the Student's t-distribution. While
this modification led to noise-resistant updates, the other associated
statistics remained unchanged, resulting in inconsistencies in the assumed
models. In this paper, we propose AdaTerm, a novel approach that incorporates
the Student's t-distribution to derive not only the first-order moment but also
all the associated statistics. This provides a unified treatment of the
optimization process, offering a comprehensive framework under the statistical
model of the t-distribution for the first time. The proposed approach offers
several advantages over previously proposed approaches, including reduced
hyperparameters and improved robustness and adaptability. This noise-adaptive
behavior contributes to AdaTerm's exceptional learning performance, as
demonstrated through various optimization problems with different and/or
unknown noise ratios. Furthermore, we introduce a new technique for deriving a
theoretical regret bound without relying on AMSGrad, providing a valuable
contribution to the field


  We revisited barium abundance in a sample of giant stars in the dwarf
spheroidal Fornax galaxy. Non-local thermodynamic equilibrium (NLTE) synthesis
was used to derive the barium abundance from two Ba II lines. Our new NLTE
result for barium shows that in the range of metallicities from -1 to -0.5 the
abundance of this element is almost the same as in the stars of the Milky Way.
We conclude that the evolution of barium abundance in the dSph Fornax galaxy
resembles that of the Milky Way at the epoch of the corresponding metallicity
level.


  I review constraints on solar system-bound dark matter, and discuss the
possibility that dark matter could be gravitationally bound to the earth and
other planets. I briefly survey various empirical constraints on such
planet-bound dark matter, and discuss effects it could produce if present,
including anomalous planetary heating and flyby velocity changes.


  Van de Waals heterostructures (VDWH) is an emerging strategy to engineer the
electronic properties of two-dimensional (2D) material systems. Motivated by
the recent discovery of MoSi$_2$N$_4$ - a synthetic septuple-layered 2D
semiconductor with exceptional mechanical and electronic properties, we
investigate the synergy of \ce{MoSi2N4} with wide band gap (WBG) 2D monolayers
of GaN and ZnO using first-principle calculations. We find that
MoSi$_2$N$_4$/GaN is a direct band gap Type-I VDWH while MoSi$_2$N$_4$/ZnO is
an indirect band gap Type-II VDWH. Intriguingly, by applying an electric field
or mechanical strain along the out-of-plane direction, the band structures of
MoSi$_2$N$_4$/GaN and MoSi$_2$N$_4$/ZnO can be substantially modified,
exhibiting rich transitional behaviors, such as the Type-I-to-Type-II band
alignment and the direct-to-indirect band gap transitions. These findings
reveal the potentials of MoSi$_2$N$_4$-based WBG VDWH as a tunable hybrid
materials with enormous design flexibility in ultracompact optoelectronic
applications.


  We present the multi-band dual triply irreducible local expansion (D-TRILEX)
approach to interacting electronic systems and discuss its numerical
implementation. This method is designed for a self-consistent description of
multi-orbital systems that can also have several atoms in the unit cell. The
current implementation of the D-TRILEX approach is able to account for the
frequency- and channel-dependent long-ranged electronic interactions. We show
that our method is accurate when applied to small multi-band systems such as
the Hubbard-Kanamori dimer. Calculations for the extended Hubbard, the
two-orbital Hubbard-Kanamori, and the bilayer Hubbard models are also
discussed.


  Regular spatially-Coupled LDPC (SC-LDPC) ensembles have gained significant
interest since they were shown to universally achieve the capacity of binary
memoryless channels under low-complexity belief-propagation decoding. In this
work, we focus primarily on the performance of these ensembles over binary
channels affected by bursts of erasures. We first develop an analysis of the
finite length performance for a single burst per codeword and no errors
otherwise. We first assume that the burst erases a complete spatial position,
modeling for instance node failures in distributed storage. We provide new
tight lower bounds for the block erasure probability ($P_{\mathrm{B}}$) at
finite block length and bounds on the coupling parameter for being
asymptotically able to recover the burst. We further show that expurgating the
ensemble can improve the block erasure probability by several orders of
magnitude. Later we extend our methodology to more general channel models. In a
first extension, we consider bursts that can start at a random position in the
codeword and span across multiple spatial positions. Besides the finite length
analysis, we determine by means of density evolution the maximnum correctable
burst length. In a second extension, we consider the case where in addition to
a single burst, random bit erasures may occur. Finally, we consider a block
erasure channel model which erases each spatial position independently with
some probability $p$, potentially introducing multiple bursts simultaneously.
All results are verified using Monte-Carlo simulations.


  We consider nonparametric classification with smooth regression functions,
where it is well known that notions of margin in $E[Y|X]$ determine fast or
slow rates in both active and passive learning. Here we elucidate a striking
distinction between the two settings. Namely, we show that some seemingly
benign nuances in notions of margin -- involving the uniqueness of the Bayes
classifier, and which have no apparent effect on rates in passive learning --
determine whether or not any active learner can outperform passive learning
rates. In particular, for Audibert-Tsybakov's margin condition (allowing
general situations with non-unique Bayes classifiers), no active learner can
gain over passive learning in commonly studied settings where the marginal on
$X$ is near uniform. Our results thus negate the usual intuition from past
literature that active rates should improve over passive rates in nonparametric
settings.


  Statistical testing is classically used as an exploratory tool to search for
association between a phenotype and many possible explanatory variables. This
approach often leads to multiple testing under dependence. We assume a
hierarchical structure between tests via an Ornstein-Uhlenbeck process on a
tree. The process correlation structure is used for smoothing the p-values. We
design a penalized estimation of the mean of the Ornstein-Uhlenbeck process for
p-value computation. The performances of the algorithm are assessed via
simulations. Its ability to discover new associations is demonstrated on a
metagenomic dataset. The corresponding R package is available from
https://github.com/abichat/zazou.


  In this paper we describe two approaches that allow to calculate some thermal
features as perceived by different observers in curved spacetimes: the
tunnelling method and the Unruh-DeWitt detector. The tunnelling phenomenon is a
semi-classical approach to the issue of Hawking radiation and allows a
straightforward calculation of the horizon temperature in a plethora of
scenarios; the Unruh-DeWitt model relies instead on a quantum field-theoretical
approach and (whenever possible) gives a more exact answer in terms of
transition rates between energy levels of an idealized detector.


  Let G be an even orthogonal or unitary group over a number field. Based on
the same observation used in arXiv:1705.10106, we prove the Arthur's
multiplicity formula for the generic part of the automorphic discrete spectrum
of G by using the theta lift. We also consider a class of non-generic
A-parameters and obtain a multiplicity formula in this case. In particular, we
obtain a description of the full automorphic discrete spectrum of even
orthogonal or unitary groups with Witt index less or equal to one.


  We consider difference operators in $L^2$ on $\R$ of the form $$ L
f(s)=p(s)f(s+i)+q(s) f(s)+r(s) f(s-i) ,$$ where $i$ is the imaginary unit. The
domain of definiteness are functions holomorphic in a strip with some
conditions of decreasing at infinity. Problems of such type with discrete
spectra are well known (Meixner--Pollaszek, continuous Hahn, continuous dual
Hahn, and Wilson hypergeometric orthogonal polynomials).
  We write explicit spectral decompositions for several operators $L$ with
continuous spectra. We also discuss analogs of 'boundary conditions' for such
operators.


  Critical dynamics of the Nambu-Jona-Lasinio model, coupled to a constant
electromagnetic field in D=2, 3, and 4, is reconsidered from a viewpoint of
infrared behavior and vacuum instability. The latter is associated with
constant electric fields and cannot be avoidable in the nonperturbative
framework obtained through the proper time method. As for magnetic fields, an
infrared cut-off is essential to investigate the critical phenomena. The result
reconfirms the fact that the critical coupling in D=3 and 4 goes to zero even
under an infinitesimal magnetic field. There also shows that a non-vanishing
$F_{\mu\nu}\widetilde F^{\mu\nu}$ causes instability. A perturbation with
respect to external fields is adopted to investigate critical quantities, but
the resultant asymptotic expansion excellently matches with the exact value.


  $BF$ theories defined over non trivial line bundles are studied. It is shown
that such theories describe a realization of a non trivial higher order bundle.
The partition function differs from the usual one -in terms of the Ray Singer
Torsion- by a factor that arises from the non triviality of the line bundles.


  A wide variation in the charge transport properties of
poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT-PSS) films is
attributed to the degree of phase-segregation of the excess insulating
polyanion. The results indicate that the charge transport in PEDOT-PSS can vary
from hopping to critical regime of the metal-insulator transition, depending on
the subtle details of morphology. The extent of electrical-connectivity in
films, directly obtained from a temperature dependent high-frequency transport
study, indicates various limiting factors to the transport, which are
correlated with the phase separation process. The low temperature
magnetotransport further supports this morphology-dependent transport scenario.


  Learning rich and compact representations is an open topic in many fields
such as object recognition or image retrieval. Deep neural networks have made a
major breakthrough during the last few years for these tasks but their
representations are not necessary as rich as needed nor as compact as expected.
To build richer representations, high order statistics have been exploited and
have shown excellent performances, but they produce higher dimensional
features. While this drawback has been partially addressed with factorization
schemes, the original compactness of first order models has never been
retrieved, or at the cost of a strong performance decrease. Our method, by
jointly integrating codebook strategy to factorization scheme, is able to
produce compact representations while keeping the second order performances
with few additional parameters. This formulation leads to state-of-the-art
results on three image retrieval datasets.


  We present moderate resolution (R > 1,800) infrared K-band spectra of twelve
long-period (Porb > 6 hr) cataclysmic variables. We detect absorption lines
from the photospheres of the secondary stars in every system, even though two
of the m were undergoing outubrsts. We have attempted to assign spectral types
to each of the secondary stars, and these classifications are generally
consistent with previous determinations/estimates. We find evidence for
abundance anomalies that include enhancements and/or deficits for all of the
species commonly found in the K-band spectra of G- and K-type dwarfs. There is,
however, only one common abundance anomaly: extremely weak CO features. Only
two of the twelve objects appeared to have normal levels of CO absorption. We
interpret this as evidence for low carbon abundances. In addition, we detect
13CO absorption in four of the twelve objects. Depleted levels of 12C and
enhanced levels of 13C indicate that material that has been processed in the
CNO cycle is finding its way into the photospheres of CV secondary stars. In
systems with luminous accretion disks, we find that the spectrum of the
secondary star is contaminated by a source that flattens (reddens) the
continuum. While free-free or classical accretion disk spectra are flatter than
the blackbody-like spectra of G and K dwarfs, removal of such contamination
from the K-band data results in spectra in which the absorption features become
too strong to be consistent with those of G and K dwarfs.


  After defining non-Gaussian L\'evy processes for two-sided time, stochastic
differential equations with such L\'evy processes are considered. Solution
paths for these stochastic differential equations have countable jump
discontinuities in time. Topological equivalence (or conjugacy) for such an
It\^o stochastic differential equation and its transformed random differential
equation is established. Consequently, a stochastic Hartman-Grobman theorem is
proved for the linearization of the It\^o stochastic differential equation.
Furthermore, for Marcus stochastic differential equations,this topological
equivalence is used to prove existence of global random attractors.


  Trajectory forecasting is crucial for video surveillance analytics, as it
enables the anticipation of future movements for a set of agents, e.g.
basketball players engaged in intricate interactions with long-term intentions.
Deep generative models offer a natural learning approach for trajectory
forecasting, yet they encounter difficulties in achieving an optimal balance
between sampling fidelity and diversity. We address this challenge by
leveraging Vector Quantized Variational Autoencoders (VQ-VAEs), which utilize a
discrete latent space to tackle the issue of posterior collapse. Specifically,
we introduce an instance-based codebook that allows tailored latent
representations for each example. In a nutshell, the rows of the codebook are
dynamically adjusted to reflect contextual information (i.e., past motion
patterns extracted from the observed trajectories). In this way, the
discretization process gains flexibility, leading to improved reconstructions.
Notably, instance-level dynamics are injected into the codebook through
low-rank updates, which restrict the customization of the codebook to a lower
dimension space. The resulting discrete space serves as the basis of the
subsequent step, which regards the training of a diffusion-based predictive
model. We show that such a two-fold framework, augmented with instance-level
discretization, leads to accurate and diverse forecasts, yielding
state-of-the-art performance on three established benchmarks.


  Electronic transmission in monolayer ReS$_{2}$ and ReS$_{2}$ based van der
Waals (vdW) heterointerfaces are studied here. Since ReS$_{2}$/WSe$_{2}$ and
ReS$_{2}$/MoSe$_{2}$ type-II vdW heterostructures are suitable for near
infrared (NIR)/short-wave infrared (SWIR) photodetection, the role of
interlayer coupling at the heterointerfaces is examined in this work. Besides,
a detailed theoretical study is presented employing density functional theory
(DFT) and nonequilibrium Green's function (NEGF) combination to analyse the
transmission spectra of the two-port devices with ReS$_{2}$/WSe$_{2}$ and
ReS$_{2}$/MoSe$_{2}$ channels and compare the near-equilibrium conductance
values.Single layer distorted1T ReS$_{2}$ exhibits formation of parallel chains
of 'Re' - 'Re' bonds, leading to in-plane anisotropy. Owing to this structural
anisotropy, the charge carrier transport is very much orientation dependent in
ReS$_{2}$. Therefore, this work is further extended to investigate the role of
clusterized 'Re' atoms in electronic transmission.


  This paper considers the problem of helping humans exercise scalable
oversight over deep neural networks (DNNs). Adversarial examples can be useful
by helping to reveal weaknesses in DNNs, but they can be difficult to interpret
or draw actionable conclusions from. Some previous works have proposed using
human-interpretable adversarial attacks including copy/paste attacks in which
one natural image pasted into another causes an unexpected misclassification.
We build on these with two contributions. First, we introduce Search for
Natural Adversarial Features Using Embeddings (SNAFUE) which offers a fully
automated method for finding copy/paste attacks. Second, we use SNAFUE to red
team an ImageNet classifier. We reproduce copy/paste attacks from previous
works and find hundreds of other easily-describable vulnerabilities, all
without a human in the loop. Code is available at
https://github.com/thestephencasper/snafue


  We present two ways (instantaneous and cumulative) to transform bibliographic
networks, using the works' publication year, into corresponding temporal
networks based on temporal quantities. We also show how to use the addition of
temporal quantities to define interesting temporal properties of nodes, links
and their groups thus providing an insight into evolution of bibliographic
networks. Using the multiplication of temporal networks we obtain different
derived temporal networks providing us with new views on studied networks. The
proposed approach is illustrated with examples from the collection of
bibliographic networks on peer review.


  We report the discovery of seven new millisecond pulsars during 20 cm
searches of 19 globular clusters using the recently upgraded Arecibo Telescope
and the new Green Bank Telescope (GBT). Five of the pulsars are in compact
binaries, three of which are eclipsing. One of the systems is in an eccentric
orbit which is almost certainly highly relativistic. Additional searches and
timing observations are underway.


  Venus currently rotates slowly, with its spin controlled by solid-body and
atmospheric thermal tides. However, conditions may have been far different 4
billion years ago, when the Sun was fainter and most of the carbon within Venus
could have been in solid form, implying a low-mass atmosphere. We investigate
how the obliquity would have varied for a hypothetical rapidly rotating Early
Venus. The obliquity variation structure of an ensemble of hypothetical Early
Venuses is simpler than that Earth would have if it lacked its large Moon
(Lissauer et al., 2012), having just one primary chaotic regime at high
prograde obliquities. We note an unexpected long-term variability of up to
$\pm7^\circ$ for retrograde Venuses. Low-obliquity Venuses show very low total
obliquity variability over billion-year timescales -- comparable to that of the
real Moon-influenced Earth.


  The relationship between the geometrical properties of stellar disks (a
flatness and truncation radius) and the disk kinematics are considered for
edge-on galaxies. It is shown that the observed thickness of the disks and the
approximate constancy of their thickness along the radius well agrees with the
condition of their marginal local gravitational stability. As a consequence,
those galaxies whose disks are thinner should harbor more massive dark haloes.
The correlation between the de-projeced central brightness of the disks and
their flatness is found (the low surface brightness disks tend to be the
thinniest ones). We also show that positions of observed photometrically
determined truncation radii $R_{cut}$ for the stellar disks support the idea of
marginal local gravitational stability of gaseous protodisks at $R =R_{cut}$,
and hence the steepening of photometric profiles may be a result of too
inefficient star formation beyond $R_{cut}$.


  We introduce the ring of partial differential operators with constant
coefficients and commensurate time lags (we use the terminology D$\Delta$
operators from now) initially defined by H. Gl\"using-L\"ur\ss en for ordinary
$D\Delta$ operators and investigate its cohomological properties. Combining
this ring theoretic observation with the integral representation technique
developed by M. Andersson, we solve a certain type of division with bounds. In
the last chapter, we prove the injectivity property of various function modules
over this ring as well as spectral synthesis type theorems for $D\Delta$
equations.


  The convex hull $\psi_{n,n}$ of certain $(n!)^2$ tensors was considered
recently in connection with graph isomorphism. We consider the convex hull
$\psi_n$ of the $n!$ diagonals among these tensors. We show: 1. The polytope
$\psi_n$ is a face of $\psi_{n,n}$. 2. Deciding if a graph $G$ has a subgraph
isomorphic to $H$ reduces to optimization over $\psi_n$. 3. Optimization over
$\psi_n$ reduces to optimization over $\psi_{n,n}$. In particular, this implies
that the subgraph isomorphism problem reduces to optimization over
$\psi_{n,n}$.


  In this paper, we discuss the asymptotic stability of singular steady states
of the nonlinear heat equation in the weighted Lebesgue norms.


  Determining ground state energies of quantum systems by hybrid
classical/quantum methods has emerged as a promising candidate application for
near-term quantum computational resources. Short of large-scale fault-tolerant
quantum computers, small-scale devices can be leveraged with current
computational techniques to identify important subspaces of relatively large
Hamiltonians. Inspired by the work that described the merging of dynamical
mean-field theory (DMFT) with a small-scale quantum computational resource as
an impurity solver [Bauer et al., arXiv:1510.03859v2], we describe an
alternative embedding scheme, density matrix embedding theory (DMET), that
naturally fits with the output from the variational quantum eigensolver and
other hybrid approaches. This approach is validated using a quantum abstract
machine simulator [Smith et al., arXiv:1608.03355] that reproduces the ground
state energy of the Hubbard model converged to the infinite limit.


  We present the first submillimetre observations of the z=2.36 broad
absorption line system Hawaii 167. Our observations confirm the hypothesis that
Hawaii 167 contains a massive quantity of dust, the optical depth of which is
sufficient to completely extinguish our ultraviolet view of a central, buried
quasar. Hawaii~167's submillimetre luminosity and associated dust mass are
similar to the ultraluminous class of infrared galaxies, supporting the
existence of an evolutionary link between these and the active galaxy
population. Hawaii 167 appears to be a young quasar which is emerging from its
dusty cocoon.


  We continue our study of the exact solutions for steady-state cracks in
ideally brittle viscoelastic lattice models by focusing on mode I in a
triangular system. The issues we address include the crack velocity versus
driving curve as well as the onset of additional bond-breaking, signaling the
emergence of complex spatio-temporal behavior. Somewhat surprisingly, the
critical velocity for this transition becomes a decreasing function of the
dissipation for sufficiently large values thereof. At the end, we briefly
discuss the possible relevance of our findings for experiments on mode I crack
instabilities.


  Software is a field of rapid changes: the best technology today becomes
obsolete in the near future. If we review the graduate attributes of any of the
software engineering programs across the world, life-long learning is one of
them. The social and psychological aspects of professional development is
linked with rewards. In organizations, where people are provided with learning
opportunities and there is a culture that rewards learning, people embrace
changes easily. However, the software industry tends to be short-sighted and
its primary focus is more on current project success; it usually ignores the
capacity building of the individual or team. It is hoped that our software
engineering colleagues will be motivated to conduct more research into the area
of software psychology so as to understand more completely the possibilities
for increased effectiveness and personal fulfillment among software engineers
working alone and in teams.


  Spinning horizonless compact objects may be unstable against an 'ergoregion
instability'. We investigate this mechanism for electromagnetic perturbations
of ultracompact Kerr-like objects with a reflecting surface, extending previous
(numerical and analytical) work limited to the scalar case. We derive an
analytical result for the frequency and the instability time scale of unstable
modes which is valid at small frequencies. We argue that our analysis can be
directly extended to gravitational perturbations of exotic compact objects in
the black-hole limit. The instability for electromagnetic and gravitational
perturbations is generically stronger than in the scalar case and it requires
larger absorption to be quenched. We argue that exotic compact objects with
spin $\chi\lesssim 0.7$ ($\chi\lesssim 0.9$) should have an absorption
coefficient of at least $0.3\%$ ($6\%$) to remain linearly stable, and that an
absorption coefficient of at least $\approx60\%$ would quench the instability
for any spin. We also show that - in the static limit - the scalar,
electromagnetic, and gravitatonal perturbations of the Kerr metric are related
to one another through Darboux transformations.


  We investigate the fabrication of electrical contacts using ion- and
electron-beam induced deposition of platinum at the sub-\mu m scale. Halos
associated with the metal surface decoration are characterized electrically in
the 0.05-2 \mu m range using transport measurements, conducting atomic force
microscopy and Kelvin probe microscopy. In contrast with IBID, EBID electrodes
exhibit weakly conductive halos at the sub-\mu m scale, and can thus be used to
achieve resist-free electrical contacts for transport measurements at the
sub-\mu m scale. Four-point transport measurements using \mu m-spaced EBID
contacts are provided in the case of a multiwalled carbon nanotube.


  We evaluate quantum corrections to conductivity in an electrically gated thin
film of a three-dimensional (3D) topological insulator (TI). We derive
approximate analytical expressions for the low-field magnetoresistance as a
function of bulk doping and bulk-surface tunneling rate. Our results reveal
parameter regimes for both weak localization and weak antilocalization, and
include diffusive Weyl semimetals as a special case.


  Following a methodology similar to \cite{Alishahiha:2015rta}, we derive a
holographic complexity for two dimensional holographic superconductors
(gauge/string superconductors) with backreactions. Applying a perturbation
method proposed by Kanno in Ref. \cite{kanno}, we study behaviors of the
complexity for a dual quantum system near critical points. We show that when a
system moves from the normal phase ($T>T_c$) to the superconductor phase
($T<T_c$), the holographic complexity will be divergent.


  We study the linearized maximal operator associated with dilates of the
hyperbolic cross multiplier in dimension two. Assuming a Lipschitz condition
and a lower bound on the linearizing function, we obtain $L^{p}(\mathbb{R}^{2})
\to L^{p}(\mathbb{R}^{2})$ bounds for all $1<p <\infty$. We discuss various
related results.


  Forman introduced discrete Morse theory as a tool for studying CW complexes
by essentially collapsing them onto smaller, simpler-to-understand complexes of
critical cells in [Fo]. Chari reformulated discrete Morse theory for regular
cell complexes in terms of acyclic matchings on face posets in [Ch]. This paper
addresses two questions: (1) under what conditions may several gradient paths
in a discrete Morse function simultaneously be reversed to cancel several pairs
of critical cells, to further collapse the complex, and (2) how to use
lexicographically first reduced expressions for permutations (in the sense of
[Ed]) to make (1) practical for poset order complexes.
  Applications include Cohen-Macaulayness of a new partial order, recently
introduced by Remmel, on the symmetric group (by refinement on the underlying
partitions into cycles) as well as a simple new proof of the homotopy type for
intervals in the weak order for the symmetric group. Additional applications
appear in [HW].


  We address a core partition regularity problem in Ramsey theory by proving
that every finite coloring of the positive integers contains monochromatic
Pythagorean pairs, i.e., $x,y\in \mathbb{N}$ such that $x^2\pm y^2=z^2$ for
some $z\in \mathbb{N}$. We also show that partitions generated by level sets of
multiplicative functions taking finitely many values always contain Pythagorean
triples. Our proofs combine known Gowers uniformity properties of aperiodic
multiplicative functions with a novel and rather flexible approach based on
concentration estimates of multiplicative functions.


  We show that it is possible to determine the weak phase \gamma \equiv \arg (-
V^*_{ub} V_{ud} / V^*_{cb} V_{cd}) of the Cabibbo-Kobayashi-Maskawa flavor
mixing matrix only from the measurement of the color-allowed B^{\pm}_u \to D
K^{\pm} decay rates. The uncertainty of this method, arising mainly from the
factorization approximation for two tree-level spectator quark transitions, may
be well controlled.


  We present two new examples of reflexive Banach spaces $X$ for which
$\mathscr{B}(X)$ is not a Grothendieck space, namely $X = T$ (the Tsirelson
space) and $X = B_p$ (the $p^{\text{th}}$ Baernstein space) for
$p\in(1,\infty)$.


  We derive threshold resummations for single-particle and single-jet inclusive
cross sections, thus generalizing previous results at fixed invariant mass to a
wider class of cross sections with phenomenological interest. We confirm the
structure of our resummed expressions by comparison with explicit one-loop
calculations for direct photons and heavy quarks.


  Spin correlation functions (up to the 3-site one) of disordered Ising model
with the nearest neighbour interaction are calculated and investigated within a
two-site cluster approximation for both quenched and annealed cases. The
approach yields the exact results for the one-dimensional system. The
long-range interaction is taken into account in the mean field approximation.


  Recently, multimodal recommendations have gained increasing attention for
effectively addressing the data sparsity problem by incorporating
modality-based representations. Although multimodal recommendations excel in
accuracy, the introduction of different modalities (e.g., images, text, and
audio) may expose more users' sensitive information (e.g., gender and age) to
recommender systems, resulting in potentially more serious unfairness issues.
Despite many efforts on fairness, existing fairness-aware methods are either
incompatible with multimodal scenarios, or lead to suboptimal fairness
performance due to neglecting sensitive information of multimodal content. To
achieve counterfactual fairness in multimodal recommendations, we propose a
novel fairness-aware multimodal recommendation approach (dubbed as FMMRec) to
disentangle the sensitive and non-sensitive information from modal
representations and leverage the disentangled modal representations to guide
fairer representation learning. Specifically, we first disentangle biased and
filtered modal representations by maximizing and minimizing their sensitive
attribute prediction ability respectively. With the disentangled modal
representations, we mine the modality-based unfair and fair (corresponding to
biased and filtered) user-user structures for enhancing explicit user
representation with the biased and filtered neighbors from the corresponding
structures, followed by adversarially filtering out sensitive information.
Experiments on two real-world public datasets demonstrate the superiority of
our FMMRec relative to the state-of-the-art baselines. Our source code is
available at https://anonymous.4open.science/r/FMMRec.


  An important quality aspect of official statistics produced by national
statistical institutes is comparability over time. To maintain uninterrupted
time series, surveys conducted by national statistical institutes are often
kept unchanged as long as possible. To improve the quality or efficiency of a
survey process, however, it remains inevitable to adjust methods or redesign
this process from time to time. Adjustments in the survey process generally
affect survey characteristics such as response bias and therefore have a
systematic effect on the parameter estimates of a sample survey. Therefore, it
is important that the effects of a survey redesign on the estimated series are
explained and quantified. In this paper a structural time series model is
applied to estimate discontinuities in series of the Dutch survey on social
participation and environmental consciousness due to a redesign of the
underlying survey process.


  For any $k>1$, we find the asymptotics of the counting function of $k$-th
power-free elements in an additive arithmetic semigroup with exponential growth
of the abstract prime counting function. This paper continues the authors'
earlier research dealing with the case of infinite $k$.


  We consider certain universal functors on symmetric quotient stacks of
Abelian varieties. In dimension two, we discover a family of
$\mathbb{P}$-functors which induce new derived autoequivalences of Hilbert
schemes of points on Abelian surfaces; a set of braid relations on a
holomorphic symplectic sixfold; and a pair of spherical functors on the Hilbert
square of an Abelian surface, whose twists are related to the well-known Horja
twist. In dimension one, our universal functors are fully faithful, giving rise
to a semiorthogonal decomposition for the symmetric quotient stack of an
elliptic curve (which we compare to the one discovered by Polishchuk--Van den
Bergh), and they lift to spherical functors on the canonical cover, inducing
twists which descend to give new derived autoequivalences here as well.


  In this paper, we propose a generative multi-column network for image
inpainting. This network synthesizes different image components in a parallel
manner within one stage. To better characterize global structures, we design a
confidence-driven reconstruction loss while an implicit diversified MRF
regularization is adopted to enhance local details. The multi-column network
combined with the reconstruction and MRF loss propagates local and global
information derived from context to the target inpainting regions. Extensive
experiments on challenging street view, face, natural objects and scenes
manifest that our method produces visual compelling results even without
previously common post-processing.


  We consider the one-loop quantum corrections to the Nielsen-Olesen flux tube
of finite length $L$, by imposing periodic boundary conditions. The
calculations are based on a recent evaluation of these quantum corrections to
the string tension of an infinite vortex. The finite length corrections are
finite from the outset. If the computation is restricted to the zero modes we
obtain the standard L\"uscher term $\pi/3L$ for a closed string. The inclusion
of the other fluctuation modes of Higgs and gauge fields, using the numerically
computed trace of the Euclidian Green's function, leads to corrections that
decrease exponentially with $L$. We present numerical results for these
corrections, discuss their possible relevance, and the limitations of the
approach.


  Large pre-trained language models have repeatedly shown their ability to
produce fluent text. Yet even when starting from a prompt, generation can
continue in many plausible directions. Current decoding methods with the goal
of controlling generation, e.g., to ensure specific words are included, either
require additional models or fine-tuning, or work poorly when the task at hand
is semantically unconstrained, e.g., story generation. In this work, we present
a plug-and-play decoding method for controlled language generation that is so
simple and intuitive, it can be described in a single sentence: given a topic
or keyword, we add a shift to the probability distribution over our vocabulary
towards semantically similar words. We show how annealing this distribution can
be used to impose hard constraints on language generation, something no other
plug-and-play method is currently able to do with SOTA language generators.
Despite the simplicity of this approach, we see it works incredibly well in
practice: decoding from GPT-2 leads to diverse and fluent sentences while
guaranteeing the appearance of given guide words. We perform two user studies,
revealing that (1) our method outperforms competing methods in human
evaluations; and (2) forcing the guide words to appear in the generated text
has no impact on the fluency of the generated text.


  The double-helical structure of DNA results from canonical base pairing and
stacking interactions. However, variations from steady-state conformations
result from mechanical perturbations in cells. These different topologies have
physiological relevance but their dependence on sequence remains unclear. Here,
we use molecular dynamics simulations to show that sequence differences result
in markedly different structural motifs upon physiological twisting and
stretching. We simulated overextension on four different sequences of DNA
((AA)12, (AT)12, (GG)12 and (GC)12) with supercoiling densities within the
physiological range. We found that DNA denatures in the majority of stretching
simulations, surprisingly including those with overtwisted DNA. GC-rich
sequences were observed to be more stable than AT-rich, with the specific
response dependent on base pair ordering. Furthermore, we found that (AT)12
forms stable periodic structures with non-canonical hydrogen bonds in some
regions and non-canonical stacking in others, whereas (GC)12 forms a stacking
motif of four base pairs independent of supercoiling density. Our results
demonstrate that 20-30% DNA extension is sufficient for breaking B-DNA around
and significantly above cellular supercoiling, and that the DNA sequence is
crucial for understanding structural changes under mechanical stress. Our
findings have important implications for the activities of protein machinery
interacting with DNA in all cells.


  We investigate the relation between the eigenvalues of the Laplacian with
Kirchhoff vertex conditions on a finite metric graph and a corresponding
Titchmarsh-Weyl function (a parameter-dependent Neumann-to-Dirichlet map). We
give a complete description of all real resonances, including multiplicities,
in terms of the edge lengths and the connectivity of the graph, and apply it to
characterize all eigenvalues which are visible for the Titchmarsh-Weyl
function.


  Several studies have shown that a number of stars pulsating in p modes lie
between the $\beta$ Cep and $\delta$ Sct instability strips in the
Hertzsprung-Russell (HR) Diagram. At present, there is no certain understanding
of how p~modes can be excited in this $T_{\rm eff}$ range. The goal of this
work is to disprove the conjecture that all stars pulsating in p modes and
lying in this $T_{\rm eff}$ range are the result of incorrect measurements of
$T_{\rm eff}$, contamination, or the presence of unseen cooler companions lying
in the $\delta$ Sct instability strip (given the high binary fraction of stars
in this region of the HR Diagram). Using TESS data, we show that the A0Vnne
star HD 42477 has a single p mode coupled to several r modes and/or g modes. We
rule out a contaminating background star with a pixel-by-pixel examination, and
we essentially rule out the possibility of a companion $\delta$ Sct star in a
binary. We model the pulsations in HD 42477 and suggest that the g modes are
excited by overstable convective core modes. We also conjecture that the single
p mode is driven by coupling with the g modes, or that the oblateness of this
rapidly-rotating star permits driving by He II ionization in the equatorial
region.


  Il is argued that the generalisation of the mechanical principles to other
variables than localisation, velocity and momentum leads to the laws of
generalized dynamics under the condition of continuous and derivable space
time. However, when the fractality arises, the mechanics principles may no more
be extended especially because the time and space singularity appears on the
boundary and creates curvature. There is no more equilibrium state, but only a
horizon which might play a same role as equilibrium but does not close the
problem - especially the problem of the invariance of the energy - which
requires two complementary factors: a first one related to the closure in the
dimensional space, and the second to scan dissymmetry stemming from the default
of tilling the space time. A new discreet time arises from fractality. It leads
irreversible thermodynamic properties. Space and time singularities lead to the
relation between the above mentioned problematic and the Riemann zeta functions
as well as its zeros.


  Given a string on an integer alphabet, we present an algorithm that computes
the set of all distinct squares belonging to this string in time linear to the
string length. As an application, we show how to compute the tree topology of
the minimal augmented suffix tree in linear time. Asides from that, we
elaborate an algorithm computing the longest previous table in a succinct
representation using compressed working space.


  This article presents a general approximation-theoretic framework to analyze
measure transport algorithms for probabilistic modeling. A primary motivating
application for such algorithms is sampling -- a central task in statistical
inference and generative modeling. We provide a priori error estimates in the
continuum limit, i.e., when the measures (or their densities) are given, but
when the transport map is discretized or approximated using a
finite-dimensional function space. Our analysis relies on the regularity theory
of transport maps and on classical approximation theory for high-dimensional
functions. A third element of our analysis, which is of independent interest,
is the development of new stability estimates that relate the distance between
two maps to the distance~(or divergence) between the pushforward measures they
define. We present a series of applications of our framework, where
quantitative convergence rates are obtained for practical problems using
Wasserstein metrics, maximum mean discrepancy, and Kullback--Leibler
divergence. Specialized rates for approximations of the popular triangular
Kn{\"o}the-Rosenblatt maps are obtained, followed by numerical experiments that
demonstrate and extend our theory.


  The extension of the so-called "empty" (with gravity and antigravity that
compensate each other in full or do not exist at all) universe and cosmological
redshift in it are considered in this paper. Its flat space-time can be
submitted not only as manifold with Friedman-Robertson-Walker metrics (FRW) of
the general theory of relativity (GR) but also as space-time with usual
Minkowski metrics (M-metrics) of the special theory of relativity (SR); the
transfer of metrics can be done by suitable transformation of reference frame.
Both below-mentioned statements are equally fair for such the universe. First:
the distant galaxies can have superluminity recession velocities in FRW-space
of GR; we have no right to use here the formula of relativistic Doppler effect.
Secondly: the SR theory is fair in the M-space and, accordingly, recession
velocities of the same galaxies here can aspire to the speed of light only.
  In this article it is shown that, despite opposite pictures in FRW-and M-
spaces, in the careful account of all details both approaches yield results
agreed among them. Thus, actually there are no contradictions between the
interpretations of cosmological redshift, based on SR and GR.


  We demonstrate how the rotor position of a PWM-controlled PMSM can be
recovered from the measured currents, by suitably using the excitation provided
by the PWM itself. This provides the benefits of signal injection, in
particular the ability to operate even at low velocity, without the drawbacks
of an external probing signal. We illustrate the relevance of the approach by
simulations and experimental results.


  We study the kinetics of infiltration in which contaminant particles, which
are suspended in a flowing carrier fluid, penetrate a porous medium. The
progress of the ``invader'' particles is impeded by their trapping on active
``defender'' sites which are on the surfaces of the medium. As the defenders
are used up, the invader penetrates further and ultimately breaks through. We
study this process in the regime where the particles are much smaller than the
pores so that the permeability change due to trapping is negligible. We develop
a family of microscopic models of increasing realism to determine the
propagation velocity of the invasion front, as well as the shapes of the
invader and defender profiles. The predictions of our model agree qualitatively
with experimental results on breakthrough times and the time dependence of the
invader concentration at the output. Our results also provide practical
guidelines for improving the design of deep bed filters in which infiltration
is the primary separation mechanism.


  We study the phase diagram of two different Hamiltonians with competiting
local, nearest-neighbour, and mean-field couplings. The first example
corresponds to the HMF Hamiltonian with an additional short-range interaction.
The second example is a reduced Hamiltonian for dipolar layered spin
structures, with a new feature with respect to the first example, the presence
of anisotropies. The two examples are solved in both the canonical and the
microcanonical ensemble using a combination of the min-max method with the
transfer operator method. The phase diagrams present typical features of
systems with long-range interactions: ensemble inequivalence, negative specific
heat and temperature jumps. Moreover, in a given range of parameters, we report
the signature of phase reentrance. This can also be interpreted as the presence
of azeotropy with the creation of two first order phase transitions with
ensemble inequivalence, as one parameter is varied continuously.


  It has been shown recently that intermittency of the Gledzer Ohkitani Yamada
(GOY) shell model of turbulence has to be related to singular structures whose
dynamics in the inertial range includes interactions with a background of
fluctuations. In this paper we propose a statistical theory of these objects by
modelling the incoherent background as a Gaussian white-noise forcing of small
strength $\Gamma $. A general scheme is developed for constructing instantons
in spatially discrete dynamical systems and the Cram\'er function governing the
probability distribution of effective singularities of exponent $z$ is computed
up to first order in a semiclassical expansion in powers of $\Gamma $. The
resulting predictions are compared with the statistics of coherent structures
deduced from full simulations of the GOY model at very high Reynolds numbers.


  We study the inter-particle potentials for few-particle systems in a scalar
theory with a non-linear mediating field of the Higgs type. We use the
variational method, in a reformulated Hamiltonian formalism of QFT, to derive
relativistic three and four particle wave equations for stationary states of
these systems. We show that the cubic and quartic non-linear terms modify the
attractive Yukawa potentials but do not change the attractive nature of the
interaction if the mediating fields are massive.


  The phenomenon of inverse magnetic catalysis of chiral symmetry in QCD
predicted by lattice simulations can be reproduced within the
Nambu--Jona-Lasinio model if the coupling~$G$ of the model decreases with the
strength $B$ of the magnetic field and temperature~$T$. The thermo-magnetic
dependence of $G(B,T)$ is obtained by fitting recent lattice QCD predictions
for the chiral transition order parameter. Different thermodynamic quantities
of magnetized quark matter evaluated with $G(B, T)$ are compared with the ones
obtained at constant coupling, $G$. The model with $G(B,T)$ predicts a more
dramatic chiral transition as the field intensity increases. In addition, the
pressure and magnetization always increase with $B$ for a given temperature.
Being parametrized by four magnetic field dependent coefficients and having a
rather simple exponential thermal dependence our accurate ansatz for the
coupling constant can be easily implemented to improve typical model
applications to magnetized quark matter.


  We discuss the recent paper on "excursion effect" by T. Qian et al. (2020).
We show that the methods presented have close relationships to others in the
literature, in particular to a series of papers by Robins, Hern\'{a}n and
collaborators on analyzing observational studies as a series of randomized
trials. There is also a close relationship to the history-restricted and the
history-adjusted marginal structural models (MSM). Important differences and
their methodological implications are clarified. We also demonstrate that the
excursion effect can depend on the design and discuss its suitability for
modifying the treatment protocol.


  Learning dynamical systems from sparse observations is critical in numerous
fields, including biology, finance, and physics. Even if tackling such problems
is standard in general information fusion, it remains challenging for
contemporary machine learning models, such as diffusion models. We introduce a
method that integrates conditional particle filtering with ancestral sampling
and diffusion models, enabling the generation of realistic trajectories that
align with observed data. Our approach uses a smoother based on iterating a
conditional particle filter with ancestral sampling to first generate plausible
trajectories matching observed marginals, and learns the corresponding
diffusion model. This approach provides both a generative method for
high-quality, smoothed trajectories under complex constraints, and an efficient
approximation of the particle smoothing distribution for classical tracking
problems. We demonstrate the approach in time-series generation and
interpolation tasks, including vehicle tracking and single-cell RNA sequencing
data.


  Among many lightweight materials used in marine applications, sandwich
structures with syntactic foam core are promising because of lower water uptake
in foam core amid face-sheets damage. HDPE (high-density polyethylene) filament
is used to 3D print sandwich skin, and glass microballoon (GMB) reinforced HDPE
syntactic foam filaments are used for the core. The optimized parameters are
used to prepare blends of 20, 40, and 60 volume % of GMB in HDPE. These foamed
blends are extruded in filament form to be subsequently used in commercially
available fused filament fabrication (FFF) based 3D printers. The defect-free
syntactic foam core sandwich composites are 3D printed concurrently for
characterizing their flexural behavior. The printed HDPE, foam cores, and
sandwiches are tested under three-point bending mode. The addition of GMB
increases both specific modulus and strength in sandwich composites and is
highest for the sandwich having a core with 60 volume % of GMB. The flexural
strength, fracture strength, and strain of foam core sandwiches registered
superior response than their respective cores. The experimental results are
found in good agreement compared with theoretical predictions. Finally, the
failure mode of the printed sandwich is also discussed.


  We develop a new statistical machine learning paradigm, named infinite-label
learning, to annotate a data point with more than one relevant labels from a
candidate set, which pools both the finite labels observed at training and a
potentially infinite number of previously unseen labels. The infinite-label
learning fundamentally expands the scope of conventional multi-label learning,
and better models the practical requirements in various real-world
applications, such as image tagging, ads-query association, and article
categorization. However, how can we learn a labeling function that is capable
of assigning to a data point the labels omitted from the training set? To
answer the question, we seek some clues from the recent work on zero-shot
learning, where the key is to represent a class/label by a vector of semantic
codes, as opposed to treating them as atomic labels. We validate the
infinite-label learning by a PAC bound in theory and some empirical studies on
both synthetic and real data.


  Cosmic magnetic fields may be generated during early cosmic phase transition,
such as the QCD- or electroweak- transitions. The magnitude of the remainder of
such fields at the present epoch crucially depends on the exponent $n$ of their
(initially super-Hubble) large-scale tail, i.e. B(lambda) ~ lambda^(-n). It has
been claimed that causality requires n=5/2, contrary to much earlier claims of
n=3/2. Here we analyze this question in detail. First, we note that contrary to
current belief, the large-scale magnetic field tail is not established at the
phase transition itself, but rather continuoulsy evolves up to the present
epoch. Neglecting turbulent flows we find n=7/2, i.e. very strongly suppressed
large-scale fields. However, in the inevitable presence of turbulent flows we
find that the large-scale magnetic field tail has sufficient time to evolve to
that of the fluid turbulence. For white noise fluid turbulence this yields
n=3/2 up to a certain scale and n=5/2 beyond for the magnetic field spectrum.
This picture is also not changed when primordial viscosity and fluid flow
dissipation is taken into account. Appreciable primordial magnetic fields
originating from cosmic phase transitions seem thus possible.


  We show that the orbits of exoplanets of the "hot Jupiter" type, as a rule,
are located close to the Alf\'{v}en point of the stellar wind of the parent
star. At this, many hot Jupiters can be located in the sub-Alf\'{v}en zone in
which the magnetic pressure of the stellar wind exceeds its dynamic pressure.
Therefore, magnetic field of the wind must play an extremely important role for
the flow of the stellar wind around the atmospheres of the hot Jupiters. This
factor must be considered both in theoretical models and in the interpretation
of observational data. The analysis shows that many typical hot Jupiters should
have shock-less intrinsic magnetospheres, which, apparently, do not have
counterparts in the Solar System. Such magnetospheres are characterized,
primarily, by the absence of the bow shock, while the magnetic barrier
(ionopause) is formed by the induced currents in the upper layers of the
ionosphere. We confirmed this inference by the three-dimensional numerical
simulation of the flow of the parent star stellar wind around the hot Jupiter
HD 209458b in which we took into account both proper magnetic field of the
planet and magnetic field of the wind.


  In the paper the distribution of prime numbers and digits of $\pi$ were
presented as chaotic.


  Ng constructed an invariant of knots in ${\mathbb{R}}^3$, a combinatorial
knot contact homology. Extending his study, we construct an invariant of
surface-knots in ${\mathbb{R}}^4$ using diagrams in ${\mathbb{R}}^3$.


  We benchmark different strategies of adding new languages (German and Korean)
into the BigScience's pretrained multilingual language model with 1.3 billion
parameters that currently supports 13 languages. We investigate the factors
that affect the language adaptability of the model and the trade-offs between
computational costs and expected performance.


  In this paper, we consider Universe filled with two-component fluid. We study
two different models. In the first model we assume barotropic fluid with the
linear equation of state as the first component of total fluid. In the second
model we assume Van der Waals gas as the first component of total fluid. In
both models, the second component assumed generalized ghost dark energy. We
consider also interaction between component and discuss, numerically,
cosmological quantities for two different parametrization of EoS which varies
with time. We consider this as a toy model of our Universe. We fix parameters
of the model by using generalized second law of thermodynamics. Comparing our
results with some observational data suggests interacting barotropic fluid with
EoS parameter $\omega(t)=\omega_{0}\cos(tH)+\omega_{1}t\frac{\dot{H}}{H}$ and
generalized ghost dark energy as an appropriate model to describe our Universe.


  Cost-effectiveness analyses (CEAs) are at the center of health economic
decision making. While these analyses help policy analysts and economists
determine coverage, inform policy, and guide resource allocation, they are
statistically challenging for several reasons. Cost and effectiveness are
correlated and follow complex joint distributions which are difficult to
capture parametrically. Effectiveness (often measured as increased survival
time) and accumulated cost tends to be right-censored in many applications.
Moreover, CEAs are often conducted using observational data with non-random
treatment assignment. Policy-relevant causal estimation therefore requires
robust confounding control. Finally, current CEA methods do not address
cost-effectiveness heterogeneity in a principled way - often presenting
population-averaged estimates even though significant effect heterogeneity may
exist. Motivated by these challenges, we develop a nonparametric Bayesian model
for joint cost-survival distributions in the presence of censoring. Our
approach utilizes a joint Enriched Dirichlet Process prior on the covariate
effects of cost and survival time, while using a Gamma Process prior on the
baseline survival time hazard. Causal CEA estimands, with policy-relevant
interpretations, are identified and estimated via a Bayesian nonparametric
g-computation procedure. Finally, we outline how the induced clustering of the
Enriched Dirichlet Process can be used to adaptively detect presence of
subgroups with different cost-effectiveness profiles. We outline an MCMC
procedure for full posterior inference and evaluate frequentist properties via
simulations. We use our model to assess the cost-efficacy of chemotherapy
versus radiation adjuvant therapy for treating endometrial cancer in the
SEER-Medicare database.


  We calculate the ratio of shear viscosity to entropy density for a black
brane of $5$-dimensional Einstein-Yang-Mills Gravity by Kubo and membrane
paradigm methods. The former gives $\frac{1}{4\pi}$ exactly which is an
expected result in the context of the Einstein-Hilbert gravity. In contrast,
the membrane paradigm reaches $\frac{1}{4\pi}$ only in large horizon radius
limit. We comment on this discrepancy.


  We formulate a version of Beck's monadicity theorem for abelian categories,
which is applied to the equivariantization of abelian categories with respect
to a finite group action. We prove that the equivariantization is compatible
with the construction of quotient abelian categories by Serre subcategories. We
prove that the equivariantization of the graded module category over a graded
ring is equivalent to the graded module category over the same ring but with a
different grading. We deduce from these results two equivalences between the
category of (equivariant) coherent sheaves on a weighted projective line of
tubular type and that on an elliptic curve, where the acting groups are cyclic
and the two equivalences are somehow adjoint to each other.


  The use of meta-rules in logic, i.e., rules whose content includes other
rules, has recently gained attention in the setting of non-monotonic reasoning:
a first logical formalisation and efficient algorithms to compute the
(meta)-extensions of such theories were proposed in Olivieri et al (2021) This
work extends such a logical framework by considering the deontic aspect. The
resulting logic will not just be able to model policies but also tackle
well-known aspects that occur in numerous legal systems. The use of Defeasible
Logic (DL) to model meta-rules in the application area we just alluded to has
been investigated. Within this line of research, the study mentioned above was
not focusing on the general computational properties of meta-rules.
  This study fills this gap with two major contributions. First, we introduce
and formalise two variants of Defeasible Deontic Logic with Meta-Rules to
represent (1) defeasible meta-theories with deontic modalities, and (2) two
different types of conflicts among rules: Simple Conflict Defeasible Deontic
Logic, and Cautious Conflict Defeasible Deontic Logic. Second, we advance
efficient algorithms to compute the extensions for both variants.


  Human neurodevelopment is a highly regulated biological process. In this
article, we study the dynamic changes of neurodevelopment through the analysis
of human brain microarray data, sampled from 16 brain regions in 15 time
periods of neurodevelopment. We develop a two-step inferential procedure to
identify expressed and unexpressed genes and to detect differentially expressed
genes between adjacent time periods. Markov Random Field (MRF) models are used
to efficiently utilize the information embedded in brain region similarity and
temporal dependency in our approach. We develop and implement a Monte Carlo
expectation-maximization (MCEM) algorithm to estimate the model parameters.
Simulation studies suggest that our approach achieves lower misclassification
error and potential gain in power compared with models not incorporating
spatial similarity and temporal dependency.


  High-throughput biological assays such as microarrays let us ask very
detailed questions about how diseases operate, and promise to let us
personalize therapy. Data processing, however, is often not described well
enough to allow for exact reproduction of the results, leading to exercises in
"forensic bioinformatics" where aspects of raw data and reported results are
used to infer what methods must have been employed. Unfortunately, poor
documentation can shift from an inconvenience to an active danger when it
obscures not just methods but errors. In this report we examine several related
papers purporting to use microarray-based signatures of drug sensitivity
derived from cell lines to predict patient response. Patients in clinical
trials are currently being allocated to treatment arms on the basis of these
results. However, we show in five case studies that the results incorporate
several simple errors that may be putting patients at risk. One theme that
emerges is that the most common errors are simple (e.g., row or column
offsets); conversely, it is our experience that the most simple errors are
common. We then discuss steps we are taking to avoid such errors in our own
investigations.


  We present a carrier-envelope offset (CEO) stable ytterbium-doped fiber
chirped-pulse amplification system employing the technology of coherent beam
combining and delivering more than 1 kW of average power at a pulse repetition
rate of 80 MHz. The CEO stability of the system is 220 mrad rms, characterized
out-of-loop with an f-to-2f interferometer in a frequency offset range of 10 Hz
to 20 MHz. The high-power amplification system boosts the average power of the
CEO stable oscillator by five orders of magnitude while increasing the phase
noise by only 100 mrad. No evidence of CEO noise deterioration due to coherent
beam combining is found. Low-frequency CEO fluctuations at the chirped-pulse
amplifier are suppressed by a slow loop feedback. To the best of our knowledge,
this is the first demonstration of a coherently combined laser system
delivering an outstanding average power and high CEO stability at the same
time.


  We observe a dependence of the damping of a confined mode of precessing
ferromagnetic magnetization on the size of the mode. The micron-scale mode is
created within an extended, unpatterned YIG film by means of the intense local
dipolar field of a micromagnetic tip. We find that damping of the confined mode
scales like the surface-to-volume ratio of the mode, indicating an interfacial
damping effect (similar to spin pumping) due to the transfer of angular
momentum from the confined mode to the spin sink of ferromagnetic material in
the surrounding film. Though unexpected for insulating systems, the measured
intralayer spin-mixing conductance $g_{\uparrow \downarrow} = 5.3 \times
10^{19} {\rm m}^{-2}$ demonstrates efficient intralayer angular momentum
transfer.


  We develop a supersymmetric field theoretical description of the Gaussian
ensemble of the almost diagonal Hermitian Random Matrices. The matrices have
independent random entries H_{ij} with parametrically small off-diagonal
elements H_{ij}/H_{ii} ~ B << 1. We derive a regular virial expansion of
correlation functions in the number of ``interacting'' supermatrices associated
with different sites in the real space and demonstrate that the perturbation
theory constructed in this way is controlled by a small parameter B. General
form of the integral expression for the m-th virial coefficient governed by the
``interaction'' of m supermatrices is presented and calculated explicitly in
the cases of 2- and 3-matrix ``interaction''. The suggested technique allows us
to calculate both the spectral correlations and the correlations of the
eigenfunctions taken at different energies and in different space points.


  The one-shot classical capacity of a quantum channel quantifies the amount of
classical information that can be transmitted through a single use of the
channel such that the error probability is below a certain threshold. In this
work, we show that this capacity is well approximated by a
relative-entropy-type measure defined via hypothesis testing. Combined with a
quantum version of Stein's lemma, our results give a conceptually simple proof
of the well-known Holevo-Schumacher-Westmoreland theorem for the capacity of
memoryless channels. More generally, we obtain tight capacity formulas for
arbitrary (not necessarily memoryless) channels.


  We report an experimental and numerical study of the propagation of
free-electron laser pulses (wavelength 24.3 nm) through helium gas. Ionisation
and excitation populates the He$^{+}$ 4$p$ state. Strong, directional emission
was observed at wavelengths of 469 nm, 164 nm, 30.4 nm, and 24.5 nm. We
interpret the emissions at 469 nm and 164 nm as 4$p$-3$s$-2$p$ cascade
superfluorescence, that at 30.4 nm as yoked superfluorescence on the 2$p$-1$s$
transition, and that at 25.6 nm as free-induction decay of the 3$p$ state.


  Multipotent stem or progenitor cells undergo a sequential series of binary
fate decisions, which ultimately generate the diversity of differentiated
cells. Efforts to understand cell fate control have focused on simple gene
regulatory circuits that predict the presence of multiple stable states,
bifurcations and switch-like transitions. However, existing gene network models
do not explain more complex properties of cell fate dynamics such as the
hierarchical branching of developmental paths. Here, we construct a generic
minimal model of the genetic regulatory network controlling cell fate
determination, which exhibits five elementary characteristics of cell
differentiation: stability, directionality, branching, exclusivity, and
promiscuous expression. We argue that a modular architecture comprising
repeated network elements reproduces these features of differentiation by
sequentially repressing selected modules and hence restricting the dynamics to
lower dimensional subspaces of the high-dimensional state space. We implement
our model both with ordinary differential equations (ODEs), to explore the role
of bifurcations in producing the one-way character of differentiation, and with
stochastic differential equations (SDEs), to demonstrate the effect of noise on
the system. We further argue that binary cell fate decisions are prevalent in
cell differentiation due to general features of the underlying dynamical
system. This minimal model makes testable predictions about the structural
basis for directional, discrete and diversifying cell phenotype development and
thus can guide the evaluation of real gene regulatory networks that govern
differentiation.


  We present the first results on galaxy metallicity evolution at z>3 from two
projects, LSD (Lyman-break galaxies Stellar populations and Dynamics) and AMAZE
(Assessing the Mass Abundance redshift Evolution). These projects use deep
near-infrared spectroscopic observations of a sample of ~40 LBGs to estimate
the gas-phase metallicity from the emission lines. We derive the
mass-metallicity relation at z$>$3 and compare it with the same relation at
lower redshift. Strong evolution from z=0 and z=2 to z=3 is observed, and this
finding puts strong constrains on the models of galaxy evolution. These
preliminary results show that the effective oxygen yields does not increase
with stellar mass, implying that the simple outflow model does not apply at
z>3.


  There is a serious disconnect between quantum theory and gravity. It occurs
at the level of the very foundations of quantum theory, and is far deeper than
just the matter of trying to quantize a non-linear theory. We shall examine
some of the physical reasons for this disconnect and show how it manifests
itself at the beginning, at the level of the equivalence principle.


  We show by explicit computations that there is a superficial inconsistency
between the conventional first law of black hole thermodynamics and
Bekenstein-Hawking area law for three types of regular black holes. The
corrected form of the first law for these regular black holes is given. The
derivation relies on the general structure of the energy-momentum tensor of the
matter fields. When the black hole mass parameter $M$ is included in the
energy-momentum tensor, the conventional form of the first law should be
modified with an extra factor. In this case, the black hole mass $M$ can no
longer be considered as the internal energy of the regular black holes.


  Efficient usage of in-device storage and computation capabilities are key
solutions to support data-intensive applications such as immersive digital
experiences. This paper proposes a location-dependent multi-antenna coded
caching -based content delivery scheme tailored specifically for wireless
immersive viewing applications. First, a novel memory allocation process
incentivizes the content relevant to the identified wireless bottleneck areas.
This enables a trade-off between local and global caching gains and results in
unequal fractions of location-dependent multimedia content cached by each user.
Then, a novel packet generation process is carried out during the subsequent
delivery phase, given the asymmetric cache placement. During this phase, the
number of packets transmitted to each user is the same, while the sizes of the
packets are proportional to the corresponding location-dependent cache ratios.
In this regard, each user is served with location-specific content using joint
multicast beamforming and a multi-rate modulation scheme that simultaneously
benefits from global caching and spatial multiplexing gains. Numerical
experiments and mathematical analysis demonstrate significant performance gains
compared to the state-of-the-art.


  Two dimensional conformal field theories with large central charge and a
sparse low-lying spectrum are expected to admit a classical string holographic
dual. We construct a large class of such theories employing permutation
orbifold technology. In particular, we describe the group theoretic constraints
on permutation groups to ensure a (stringy) holographic CFT. The primary result
we uncover is that in order for the degeneracy of states to be finite in the
large central charge limit, the groups of interest are the so-called
oligomorphic permutation groups. Further requiring that the low-lying spectrum
be sparse enough puts a bound on the number of orbits of these groups (on
finite element subsets). Along the way we also study familiar cyclic and
symmetric orbifolds to build intuition. We also demonstrate how holographic
spectral properties are tied to the geometry of covering spaces for permutation
orbifolds.


  Recent data from high statistics experiments that have measured the modulus
of the pion electromagnetic form factor from threshold to relatively high
energies are used as input in a suitable mathematical framework of analytic
continuation to find stringent constraints on the shape parameters of the form
factor at $t=0$. The method uses also as input a precise description of the
phase of the form factor in the elastic region based on Fermi-Watson theorem
and the analysis of the $\pi\pi$ scattering amplitude with dispersive Roy
equations, and some information on the spacelike region coming from recent high
precision experiments. Our analysis confirms the inconsistencies of several
data on the modulus, especially from low energies, with analyticity and the
input phase, noted in our earlier work. Using the data on the modulus from
energies above $0.65 \,{\rm GeV}$, we obtain, with no specific parametrization,
the prediction $<r_\pi^2 \r angle \in\, (0.42,\,0.44)\,\fmsq $ for the charge
radius. The same formalism leads also to very narrow allowed ranges for the
higher-order shape parameters at $t=0$, with a strong correlation among them.


  In outside the body HIFU treatment that focused ultrasound beams hit severely
with cancer tissue layer especially the soft one, at the time of passage of the
body different layers as long as they want to reach tumor, put their own way
components under mechanical and even thermal influence and they can cause skin
lesions. To reduce this effect a specific mechanical model can be used that
means body tissue is considered as a mechanical model, it is affected when
passing sound mechanical waves through it and each layer has an average heat.
Gradually sound intensity decreases through every layer passage, finally in one
direction a decreased intensity sound reach tumor tissue. If sound propagated
directions increase, countless waves with decreased intensity are gathered upon
the tumor tissue that causes a lot of heat focus on tumor tissue. Depending on
the kind and mechanical properties of the tissue, intensity of each sound wave
when it passes through tissue can be controlled to reduce damages outside the
tumor tissue.


  A methane line list for the HITEMP spectroscopic database, covering 0-13,400
cm$^{-1}$ ($>$746 nm), is presented. To create this compilation, ab initio line
lists of $^{12}$CH$_{4}$ from Rey et al. (2017) ApJ, 847, 105 (provided at
separate temperatures in the TheoReTS information system), are now combined
with HITRAN2016 methane data to produce a single line list suitable for
high-temperature line-by-line calculations up to 2000 K. An
effective-temperature interpolation model was created in order to represent
continuum-like features at any temperature of interest. This model is
advantageous to previously-used approaches that employ so-called
``super-lines'', which are suitable only at a given temperature and require
separate line lists for different temperatures. The resultant HITEMP line list
contains $\sim$32 million lines and is significantly more flexible than
alternative line lists of methane, while accuracy required for astrophysical or
combustion applications is retained. Comparisons against experimental
observations of methane absorption at high temperatures have been used to
demonstrate the accuracy of the new work. The line list includes both strong
lines and quasi-continuum features and is provided in the common user-friendly
HITRAN/HITEMP format, making it the most practical methane line list for
radiative transfer modeling at high-temperature conditions.


  The cosmic microwave background (CMB) anisotropies are a powerful probe of
the early universe, and have largely contributed to establishing the current
standard cosmological model. To extract the information encoded in those tiny
variations, one must first compress the raw, time-domain data collected by a
telescope into maps of the sky at the observed frequencies, in a procedure
known as map-making. I provide a general introduction to this problem, and
highlight a few specificities of the MAPPRAISER implementation.


  Motivated by spectral analysis of replicated brain signal time series, we
propose a functional mixed effects approach to model replicate-specific
spectral densities as random curves varying about a deterministic
population-mean spectrum. In contrast to existing work, we do not assume the
replicate-specific spectral curves to be independent, i.e. there may exist
explicit correlation between different replicates in the population. By
projecting the replicate-specific curves onto an orthonormal wavelet basis,
estimation and prediction is carried out under an equivalent linear mixed
effects model in the wavelet coefficient domain. To cope with potentially very
localized features of the spectral curves, we develop estimators and predictors
based on a combination of generalized least squares estimation and nonlinear
wavelet thresholding, including asymptotic confidence sets for the
population-mean curve. We derive risk bounds for the nonlinear wavelet
estimator of the population-mean curve, a result that reflects the influence of
correlation between different curves in the replicate-population, and we derive
consistency of the estimators of the inter- and intra-curve correlation
structure in an appropriate sparseness class of functions. To illustrate the
proposed functional mixed effects model and our estimation and prediction
procedures, we present several simulated time series data examples and we
analyze a motivating brain signal dataset recorded during an associative
learning experiment.


  Biological cells can be distinguished by their phenotype or at the molecular
level, based on their genome, epigenome, and transcriptome. This paper focuses
on the transcriptome, which encompasses all the RNA transcripts in a given cell
population, indicating the genes being expressed at a given time. We consider
single-cell RNA sequencing data and develop a novel model-based clustering
method to group cells based on their transcriptome profiles. Our clustering
approach takes into account the presence of zero inflation in the data, which
can occur due to genuine biological zeros or technological noise. The proposed
model for clustering involves a mixture of zero-inflated Poisson or
zero-inflated negative binomial distributions, and parameter estimation is
carried out using the EM algorithm. We evaluate the performance of our proposed
methodology through simulation studies and analyses of publicly available
datasets.