  Cross-correlating the Planck High Frequency Instrument (HFI) maps against
quasars from the Sloan Digital Sky Survey (SDSS) DR7, we estimate the intensity
distribution of the Cosmic Infrared Background (CIB) over the redshift range 0
< z < 5.We detect redshift-dependent spatial cross-correlations between the two
datasets using the 857, 545 and 353 GHz channels and we obtain upper limits at
217 GHz consistent with expectations. At all frequencies with detectable signal
we infer a redshift distribution peaking around z ~ 1.2 and find the recovered
spectrum to be consistent with emission arising from star forming galaxies. By
assuming simple modified blackbody and Kennicutt relations, we estimate dust
and star formation rate density as a function of redshift, finding results
consistent with earlier multiwavelength measurements over a large portion of
cosmic history. However, we note that, lacking mid-infrared coverage, we are
not able to make an accurate determination of the mean temperature for the dust
responsible for the CIB. Our results demonstrate that clustering-based redshift
inference is a valuable tool for measuring the entire evolution history of the
cosmic star formation rate from a single and homogeneous dataset.


  We investigate the possibility for cosmic ray experiments to discover
non-thermal small black holes with masses in the TeV range. Such black holes
would result due to the impact between ultra high energy cosmic rays or
neutrinos with nuclei from the upper atmosphere and decay instantaneously. They
could be produced copiously if the Planck scale is in the few TeV region. As
their masses are close to the Planck scale, these holes would typically decay
into two particles emitted back-to-back. Depending on the angles between the
emitted particles with respect to the center of mass direction of motion, it is
possible for the simultaneous showers to be measured by the detectors.


  In this paper, for finite discrete field $F$, nonempty set $\Gamma$, weight
vector $\mathfrak{w}=({\mathfrak w}_\alpha)_{\alpha\in\Gamma}\in F^\Gamma$ and
weighted generalized shift $\sigma_{\varphi,{\mathfrak w}}:F^\Gamma\to
F^\Gamma$, we find necessary and sufficient conditions for uniform dynamical
system $(F^\Gamma,\sigma_{\varphi,{\mathfrak w}})$ to be Li--Yorke chaotic.
Next we find necessary and sufficient conditions for
$(F^\Gamma,\sigma_{\varphi,{\mathfrak w}})$ to be Devaney chaotic.


  We present resolved thermodynamic profiles out to 500 kpc, about $r_{500}$,
of the $z=1.75$ galaxy cluster IDCS J1426.5+3508 with 40 kpc resolution. Thanks
to the combination of Sunyaev-Zel'dovich and X-ray datasets, IDCS J1426.5+3508
becomes the most distant cluster with resolved thermodynamic profiles. These
are derived assuming a non-parametric pressure profile and a very flexible
model for the electron density profile. The shape of the pressure profile is
flatter than the universal pressure profile. The IDCS J1426.5+3508 temperature
profile is increasing radially out to 500 kpc. To identify the possible future
evolution of IDCS J1426.5+3508 , we compared it with its local descendants that
numerical simulations show to be $0.65\pm0.12$ dex more massive. We found no
evolution at 30 kpc, indicating a fine tuning between cooling and heating at
small radii. At $30<r<300$ kpc, our observations show that entropy and heat
must be deposited with little net gas transfer, while at 500 kpc the gas need
to be replaced by a large amount of cold, lower entropy gas, consistent with
theoretical expectation of a filamentary gas stream, which brings low entropy
gas to 500 kpc and energy at even smaller radii. At $r \gtrsim 400$ kpc the
polytropic index takes a low value, which indicates the presence of a large
amount of non-thermal pressure. Our work also introduces a new definition of
the evolutionary rate, which uses unscaled radii, unscaled thermodynamic
quantities, and different masses at different redshifts to compare ancestors
and descendants. It has the advantage of separating cluster evolution,
dependence on mass, pseudo-evolution and returns a number with unique
interpretation, unlike other definitions used in literature.


  Optical whispering gallery mode (WGM) resonators are a powerful and versatile
tool used in many branches of science. Fine tuning of the central frequency and
line width of individual resonances is however desirable in a number of
applications including frequency conversion, optical communications and
efficient light-matter coupling. To this end we present a detailed theoretical
analysis of dielectric tuning of WGMs supported in axisymmetric resonators.
Using the Bethe-Schwinger equation and adopting an angular spectrum field
representation we study the resonance shift and mode broadening of high $Q$
WGMs when a planar dielectric substrate is brought close to the resonator.
Particular focus is given to use of a uniaxial substrate with an arbitrarily
aligned optic axis. Competing red and blue resonance shifts ($\sim 30$ MHz),
deriving from generation of a near field material polarisation and back action
from the radiation continuum respectively, are found. Anomalous resonance
shifts can hence be observed depending on the substrate material, whereas mode
broadening on the order of $\sim 50$ MHz can also be simply realised.
Furthermore, polarisation selective coupling with extinction ratios of $> 10^4$
can be achieved when the resonator and substrate are of the same composition
and their optic axes are chosen correctly. Double refraction and properties of
out-coupled beams are also discussed.


  As part of the DESY summer student program 2021, transverse momentum
dependent (TMD) parton distributions obtained from the Parton Branching (PB)
method were combined with next-to-leading-order (NLO) using the POWHEG method.
Computations of the resulting Drell-Yan (DY) transverse momentum spectrum were
performed. A good agreement of the theoretical predictions with the measurement
performed by the CMS experiment at the center-of-mass energy of 13 TeV is
found, at low and intermediate DY $p_{\rm T}$. The new scale choice option for
the matching has been included in the CASCADE event generator.


  The paper is devoted to the Hamiltonian treatment of classical and quantum
properties of Liouville field theory on a timelike strip in 2d Minkowski space.
We give a complete description of classical solutions regular in the interior
of the strip and obeying constant conformally invariant conditions on both
boundaries. Depending on the values of the two boundary parameters these
solutions may have different monodromy properties and are related to bound or
scattering states. By Bohr-Sommerfeld quantization we find the quasiclassical
discrete energy spectrum for the bound states in agreement with the
corresponding limit of spectral data obtained previously by conformal bootstrap
methods in Euclidean space. The full quantum version of the special vertex
operator $e^{-\phi}$ in terms of free field exponentials is constructed in the
hyperbolic sector.


  We investigate a poset structure that extends the weak order on a finite
Coxeter group $W$ to the set of all faces of the permutahedron of $W$. We call
this order the facial weak order. We first provide two alternative
characterizations of this poset: a first one, geometric, that generalizes the
notion of inversion sets of roots, and a second one, combinatorial, that uses
comparisons of the minimal and maximal length representatives of the cosets.
These characterizations are then used to show that the facial weak order is in
fact a lattice, generalizing a well-known result of A. Bj\"orner for the
classical weak order. Finally, we show that any lattice congruence of the
classical weak order induces a lattice congruence of the facial weak order, and
we give a geometric interpretation of their classes. As application, we
describe the facial boolean lattice on the faces of the cube and the facial
Cambrian lattice on the faces of the corresponding generalized associahedron.


  In an earlier work (Shankar kumar Jha, A Vyas, O S K S Sastri, Rajkumar Jain
& K S Umesh, 'Determination of wavelength of laser light using Modified
Newton's rings setup', Physics Education, vol. 22, no.3, 195-202(2005))
reported by our group, a version of Newton's rings experiment called Modified
Newton's rings was proposed. The present work is an extension of this work.
Here, a general formula for wavelength has been derived, applicable for a plane
of observation at any distance. A relation between the focal length and the
radius curvature is also derived for a plano-convex lens which is essentially
used as a concave mirror. Tracker, a video analysis software, freely
downloadable from the net, is employed to analyze the fringes captured using a
CCD camera. Two beams which give rise to interference fringes in conventional
Newton's rings and in the present setup are clearly distinguished.


  We apply macroscopic fluctuation theory to study the diffusion of a tracer in
a one-dimensional interacting particle system with excluded mutual passage,
known as single-file diffusion. In the case of Brownian point particles with
hard-core repulsion, we derive the cumulant generating function of the tracer
position and its large deviation function. In the general case of arbitrary
inter-particle interactions, we express the variance of the tracer position in
terms of the collective transport properties, viz. the diffusion coefficient
and the mobility. Our analysis applies both for fluctuating (annealed) and
fixed (quenched) initial configurations.


  We characterize statistical properties of the flow field in developed
turbulence using concepts from stochastic thermodynamics. On the basis of data
from a free air-jet experiment, we demonstrate how the dynamic fluctuations
induced by small-scale intermittency generate analogs of entropy-consuming
trajectories with sufficient weight to make fluctuation theorems observable at
the macroscopic scale. We propose an integral fluctuation theorem for the
entropy production associated with the stochastic evolution of velocity
increments along the eddy-hierarchy and demonstrate its extreme sensitivity to
the accurate description of the tails of the velocity distributions.


  An energy efficient distributed Change Detection scheme based on Page's CUSUM
algorithm was presented in \cite{icassp}. In this paper we consider a
nonparametric version of this algorithm. In the algorithm in \cite{icassp},
each sensor runs CUSUM and transmits only when the CUSUM is above some
threshold. The transmissions from the sensors are fused at the physical layer.
The channel is modeled as a Multiple Access Channel (MAC) corrupted with noise.
The fusion center performs another CUSUM to detect the change. In this paper,
we generalize the algorithm to also include nonparametric CUSUM and provide a
unified analysis.


  Certifying that an n-qubit state synthesized in the lab is close to the
target state is a fundamental task in quantum information science. However,
existing rigorous protocols either require deep quantum circuits or
exponentially many single-qubit measurements. In this work, we prove that
almost all n-qubit target states, including those with exponential circuit
complexity, can be certified from only O(n^2) single-qubit measurements. This
result is established by a new technique that relates certification to the
mixing time of a random walk. Our protocol has applications for benchmarking
quantum systems, for optimizing quantum circuits to generate a desired target
state, and for learning and verifying neural networks, tensor networks, and
various other representations of quantum states using only single-qubit
measurements. We show that such verified representations can be used to
efficiently predict highly non-local properties that would otherwise require an
exponential number of measurements. We demonstrate these applications in
numerical experiments with up to 120 qubits, and observe advantage over
existing methods such as cross-entropy benchmarking (XEB).


  In this letter, we show that the Semiclassical Einstein's Field Equation can
be recovered using the generalized entropy $S_{gen}$. This approach is
reminiscent of non-equilibrium thermodynamics. Furthermore, contrary to the
entanglement equilibrium approach of deriving the semiclassical Einstein's
equation, this approach does not require any such assumptions and still
recovers its correct form. Therefore, in a sense, we also show the validity of
the semiclassical approximation, a crucial approach for establishing a number
of important ideas such as the Hawking effect.


  The Sun is a source of high energy neutrinos (E > 10 GeV) produced by cosmic
ray interactions in the solar atmosphere. We study the impact of three-flavor
oscillations (in vacuum and in matter) on solar atmosphere neutrinos, and
calculate their observable fluxes at Earth, as well as their event rates in a
kilometer-scale detector in water or ice. We find that peculiar three-flavor
oscillation effects in matter, which can occur in the energy range probed by
solar atmosphere neutrinos, are significantly suppressed by averaging over the
production region and over the neutrino and antineutrino components. In
particular, we find that the relation between the neutrino fluxes at the Sun
and at the Earth can be approximately expressed in terms of phase-averaged
``vacuum'' oscillations, dominated by a single mixing parameter (the angle
theta_23).


  We present a general theoretical model for the spatio-temporal dynamics of
animal contests. Inspired by interactions between physical particles, the model
is formulated in terms of effective interaction potentials, which map typical
elements of contest behaviour into empirically verifiable rules of contestant
motion. This allows us to simulate the observable dynamics of contests in
various realistic scenarios, notably in dyadic contests over a localized
resource. Assessment strategies previously formulated in game-theoretic models,
as well as the effects of fighting costs, can be described as variations in our
model's parameters. Furthermore, the trends of contest duration associated with
these assessment strategies can be derived and understood within the model.
Detailed description of the contestants' motion enables the exploration of
spatio-temporal properties of asymmetric contests, such as the emergence of
chase dynamics. Overall, our framework aims to bridge the growing gap between
empirical capabilities and theory in this widespread aspect of animal
behaviour.


  We report the discovery of a spectacular ``post-starburst quasar'' UN
J1025-0040 (B=19; z=0.634). The optical spectrum is a chimera, displaying the
broad Mg II emission line and strong blue continuum characteristic of quasars,
but is dominated in the red by a large Balmer jump and prominent high-order
Balmer absorption lines indicative of a substantial young stellar population at
similar redshift. Stellar synthesis population models show that the stellar
component is consistent with a 400 Myr old instantaneous starburst with a mass
of less than or about 10^{11} solar masses. A deep, K_s-band image taken in 0.5
arcsec seeing shows a point source surrounded by asymmetric extended fuzz.
Approximately 70% of the light is unresolved, the majority of which is expected
to be emitted by the starburst. While starbursts and galaxy interactions have
been previously associated with quasars, no quasar ever before has been seen
with such an extremely luminous young stellar population.


  In this paper, we present a novel deep learning architecture for infrared and
visible images fusion problem. In contrast to conventional convolutional
networks, our encoding network is combined by convolutional layers, fusion
layer and dense block in which the output of each layer is connected to every
other layer. We attempt to use this architecture to get more useful features
from source images in encoding process. And two fusion layers(fusion
strategies) are designed to fuse these features. Finally, the fused image is
reconstructed by decoder. Compared with existing fusion methods, the proposed
fusion method achieves state-of-the-art performance in objective and subjective
assessment. Code and pre-trained models are available at
https://github.com/hli1221/imagefusion_densefuse


  We write the known invariant definition of the Szekeres-Szafron family of
solutions in an intrinsic, deductive, explicit and algorithmic form. We also
intrinsically characterize the two commonly considered subfamilies, and analyze
other subclasses, also defined by first-order differential conditions.
Furthermore, we present a Rainich-like approach to these metrics.


  We prove that, under low noise assumptions, the support vector machine with
$N\ll m$ random features (RFSVM) can achieve the learning rate faster than
$O(1/\sqrt{m})$ on a training set with $m$ samples when an optimized feature
map is used. Our work extends the previous fast rate analysis of random
features method from least square loss to 0-1 loss. We also show that the
reweighted feature selection method, which approximates the optimized feature
map, helps improve the performance of RFSVM in experiments on a synthetic data
set.


  Transformer based pre-trained models such as BERT and its variants, which are
trained on large corpora, have demonstrated tremendous success for natural
language processing (NLP) tasks. Most of academic works are based on the
English language; however, the number of multilingual and language specific
studies increase steadily. Furthermore, several studies claimed that language
specific models outperform multilingual models in various tasks. Therefore, the
community tends to train or fine-tune the models for the language of their case
study, specifically. In this paper, we focus on Turkish maps data and
thoroughly evaluate both multilingual and Turkish based BERT, DistilBERT,
ELECTRA and RoBERTa. Besides, we also propose a MultiLayer Perceptron (MLP) for
fine-tuning BERT in addition to the standard approach of one-layer fine-tuning.
For the dataset, a mid-sized Address Parsing corpus taken with a relatively
high quality is constructed. Conducted experiments on this dataset indicate
that Turkish language specific models with MLP fine-tuning yields slightly
better results when compared to the multilingual fine-tuned models. Moreover,
visualization of address tokens' representations further indicates the
effectiveness of BERT variants for classifying a variety of addresses.


  We compute the thermalization of a hidden sector consisting of minicharged
fermions (MCPs) and massless hidden photons in the early Universe. The precise
measurement of the anisotropies of the cosmic microwave background (CMB) by
Planck and the relic abundance of light nuclei produced during big bang
nucleosynthesis (BBN) constrain the amount of dark radiation of this hidden
sector through the effective number of neutrino species, Neff. This study
presents novel and accurate predictions of dark radiation in the strongly and
weakly coupled regime for a wide range of model parameters. We give the value
of Neff for MCP masses between 100 keV and 10 GeV and minicharges in the range
10^(-11)-1. Our results can be used to constrain MCPs with the current data and
they are also a valuable indicator for future experimental searches, should the
hint for dark radiation manifest itself in the next release of Planck's data.


  In the generalized topological quantum field theory constructed by Andersen
and Kashaev, invariants of 3-manifolds are defined given the combinatorial
structure of a tetrahedral decomposition. Furthermore, a variant of the volume
conjecture has been proposed in which the hyperbolic volume can be extracted
from this invariant of the complementary space of the hyperbolic knot in an
oriented $3$-dimensional closed manifold. We prove that the reformulated volume
conjecture holds for the complementary space of the hyperbolic knot $7_3$ in
$S^3$, given a specific tetrahedral decomposition.


  Logit dynamics are dynamical systems describing transitions and equilibria of
actions of interacting players under uncertainty. An uncertainty is embodied in
logit dynamic as a softmax type function often called a logit function
originating from a maximization problem subjected to an entropic penalization.
This study provides another explanation for the generalized logit dynamic,
particularly its logit function and player's heterogeneity, based on a
discounted mean field game subjected to the costly decision making of a
representative player. A large discount limit of the mean field game is argued
to yield a logit dynamic. Further, mean field games that lead to classical and
generalized logit dynamics are clarified and their well posedness is discussed.
Additionally, numerical methods based on a finite difference discretization for
computing generalized logit dynamics and corresponding mean field games are
presented. Numerical methods are applied to two problems arising in the
management of resources and environment; one involves an inland fisheries
management problem with legal and illegal anglers, while the other is a
sustainable tourism problem. Particularly, cases that possibly lack the
regularity condition to be satisfied for the unique existence of stationary
solutions are computationally discussed.


  High-speed data busses constructed from copper components are both difficult
to model and important to accurately simulate. Using analytic signal theory and
an extension of the skin effect for non-uniform conductivity, experimental data
taken from IEEE 1394-1995 cables and connectors is used to predict the transfer
function of a 4.5 meter cable with two connectors. With these techniques any
length of cable between two connectors can be simulated with high accuracy,
including all the cable and connector losses and the infinitely summed standing
waves that occur between the connectors.


  We present and analyze a novel space-time hybridizable discontinuous Galerkin
(HDG) method for the linear free-surface problem on prismatic space-time
meshes. We consider a mixed formulation which immediately allows us to compute
the velocity of the fluid. In order to show well-posedness, our space-time HDG
formulation makes use of weighted inner products. We perform an a priori error
analysis in which the dependence on the time step and spatial mesh size is
explicit. We provide two numerical examples: one that verifies our analysis and
a wave maker simulation.


  For a polynomial $P$ of degree $n$ and an $m$-tuple
$\Lambda=(\lambda_1,\dots,\lambda_m)$ of distinct complex numbers, the dope
matrix of $P$ with respect to $\Lambda$ is $D_P(\Lambda)=(\delta_{ij})_{i\in
[1,m],j\in[0,n]}$, where $\delta_{ij}=1$ if $P^{(j)}(\lambda_i)=0$, and
$\delta_{ij}=0$ otherwise. Our first result is a combinatorial characterization
of the $2$-row dope matrices (for all pairs $\Lambda$); using this
characterization, we solve the associated enumeration problem. We also give
upper bounds on the number of $m\times(n+1)$ dope matrices, and we show that
the number of $m \times (n+1)$ dope matrices for a fixed $m$-tuple $\Lambda$ is
maximized when $\Lambda$ is generic. Finally, we resolve an ``extension''
problem of Nathanson and present several open problems.


  We explore the evolution of various properties of multiple-population
globular clusters (GCs) for a broad range of initial conditions. We simulated
over 200 GC models using the MOCCA Monte Carlo code and find that present-day
properties (core and half-light radii, ratio of the number of second-generation
(SG) stars to the total number of stars, NSG/NTOT) of these models cover the
observed values of these quantities for Milky Way GCs. Starting with a
relatively small value of the SG fraction (NSG/NTOT ~ 0.25) and a SG system
concentrated in the inner regions of the cluster, we find, in agreement with
previous studies, that systems in which the first-generation (FG) is initially
tidally filling or slightly tidally underfilling best reproduce the observed
ratios of NSG/NTOT and have values of the core and half-light radii typical of
those of many Galactic globular clusters. Models in which the FG is initially
tidally underfilling retain values of NSG/NTOT close to their initial values.
These simulations expand previous investigations and serve to further constrain
the viable range of initial parameters and better understand their influence on
present-day GC properties. The results of this investigation also provide the
basis for our future survey aimed at building specific models to reproduce the
observed trends (or lack thereof) between the properties of multiple stellar
populations and other clusters properties.


  We investigate an application in the automatic tuning of computer codes, an
area of research that has come to prominence alongside the recent rise of
distributed scientific processing and heterogeneity in high-performance
computing environments. Here, the response function is nonlinear and noisy and
may not be smooth or stationary. Clearly needed are variable selection,
decomposition of influence, and analysis of main and secondary effects for both
real-valued and binary inputs and outputs. Our contribution is a novel set of
tools for variable selection and sensitivity analysis based on the recently
proposed dynamic tree model. We argue that this approach is uniquely well
suited to the demands of our motivating example. In illustrations on benchmark
data sets, we show that the new techniques are faster and offer richer feature
sets than do similar approaches in the static tree and computer experiment
literature. We apply the methods in code-tuning optimization, examination of a
cold-cache effect, and detection of transformation errors.


  We investigate the optical property of monolayer and layered BiI$_3$ and
reveal the presence of exciton only in the monolayer crystal. We evaluate the
energy spectrum of a dielectric function by using time-dependent density
functional theory. Bulk crystal of BiI$_3$ is an atomic layered semiconductor
with the band gap corresponding to the frequency of visible light. The
numerical result for the bulk crystal is confirmed to be consistent with the
previous experimental results and it does not depend on the number of layers
except the monolayer. We reveal the excitons appearing below the resonant peak
associated with the inter-band excitation in the monolayer crystal. The unique
optical property can be directly observed in the optical absorption or
differential reflectance spectrum and distinguish the monolayer crystal from
the stacked BiI$_3$.


  Providing connectivity to aerial users such as cellular connected unmanned
aerial vehicles is a key challenge for future cellular systems. In this paper,
the use of conjugate beamforming for simultaneous content delivery to an AU
coexisting with multiple ground users is investigated. In particular, a content
delivery network of uniformly distributed massive MIMO enabled ground base
stations serving both aerial and ground users through spatial multiplexing is
considered. For this model, the successful content delivery probability is
derived as a function of the system parameters. The effects of various system
parameters such as antenna down-tilt angle, AU altitude, number of scheduled
users, and number of antennas on the achievable performance are then
investigated. Results reveal that whenever the AU altitude is below the BS
height, the antennas down-tilt angles yield an inherent tradeoff between the
performance of the AU and the GUs. However, if the AU altitude exceeds the BS
height, down-tilting the BS antennas with a considerably large angle improves
the performance of both the AU and the GUs.


  We consider a quantum system weakly coupled to a large heat bath of harmonic
oscillators. It is well known that such a boson bath initially at thermal
equilibrium thermalises the system. We show that assuming a priori an
equilibrium state is not necessary to obtain the thermalisation of the system.
We determine the complete Schr\"odinger time evolution of the subsystem of
interest for an initial pure product state of the composite system consisting
of the considered system and the bath. We find that the system relaxes into
canonical equilibrium for almost all initial pure bath states of
macroscopically well-defined energy. The temperature of the system asymptotic
thermal state is determined by the energy of the initial bath state as the
corresponding microcanonical temperature. Moreover, the time evolution of the
system is identical to the one obtained assuming that the boson bath is
initially at thermal equilibrium with this temperature. A significant part of
our approach is applicable to other baths and we identify the bath features
which are requisite for the thermalisation studied.


  We present a study of the effect of crowding on stellar photometry. We
develop an analytical model through which we are able to predict the error in
magnitude and color for a given star for any combination of telescope
resolution, stellar luminosity function, background surface brightness, and
distance. We test our predictions with Monte Carlo simulations of the LMC
globular cluster NGC 1835, for resolutions corresponding to a seeing-limited
telescope, the $HST$, and an AO-corrected 30-m (near diffraction limited)
telescope. Our analytically predicted magnitude errors agree with the
simulation results to within $\sim$20%. The analytical model also predicts that
errors in color are strongly affected by the correlation of crowding--induced
photometric errors between bands as is seen in the simulations. Using
additional Monte Carlo simulations and our analytical crowding model, we
investigate the photometric accuracy which 30-m and 100-m Extremely Large
Telescopes (ELTs) will be able to achieve at distances extending to the Virgo
cluster. We argue that for stellar populations work, ELTs quickly become
crowding-limited, suggesting that low--Strehl AO systems may be sufficient for
this type of science.


  Molecular dynamics simulations are an important tool for describing the
evolution of a chemical system with time. However, these simulations are
inherently held back either by the prohibitive cost of accurate electronic
structure theory computations or the limited accuracy of classical empirical
force fields. Machine learning techniques can help to overcome these
limitations by providing access to potential energies, forces and other
molecular properties modeled directly after an electronic structure reference
at only a fraction of the original computational cost. The present text
discusses several practical aspects of conducting machine learning driven
molecular dynamics simulations. First, we study the efficient selection of
reference data points on the basis of an active learning inspired adaptive
sampling scheme. This is followed by the analysis of a machine-learning based
model for simulating molecular dipole moments in the framework of predicting
infrared spectra via molecular dynamics simulations. Finally, we show that
machine learning models can offer valuable aid in understanding chemical
systems beyond a simple prediction of quantities.


  In advanced paradigms of autonomous driving, learning Bird's Eye View (BEV)
representation from surrounding views is crucial for multi-task framework.
However, existing methods based on depth estimation or camera-driven attention
are not stable to obtain transformation under noisy camera parameters, mainly
with two challenges, accurate depth prediction and calibration. In this work,
we present a completely Multi-Camera Calibration Free Transformer (CFT) for
robust BEV representation, which focuses on exploring implicit mapping, not
relied on camera intrinsics and extrinsics. To guide better feature learning
from image views to BEV, CFT mines potential 3D information in BEV via our
designed position-aware enhancement (PA). Instead of camera-driven point-wise
or global transformation, for interaction within more effective region and
lower computation cost, we propose a view-aware attention which also reduces
redundant computation and promotes converge. CFT achieves 49.7% NDS on the
nuScenes detection task leaderboard, which is the first work removing camera
parameters, comparable to other geometry-guided methods. Without temporal input
and other modal information, CFT achieves second highest performance with a
smaller image input 1600 * 640. Thanks to view-attention variant, CFT reduces
memory and transformer FLOPs for vanilla attention by about 12% and 60%,
respectively, with improved NDS by 1.0%. Moreover, its natural robustness to
noisy camera parameters makes CFT more competitive.


  Public policy decision making has become more complex and complicated in
recent times. Some authors have attributed this to the fact that public policy
decision makers now have more variables to consider in every decision more than
ever before. Others have argued that the rate of civilization, globalization
and information technology has made the public to be more enlightened and
abreast with the activities of government and so can oppose government
decisions if they are unfavourable. This tends to increase government need for
more and better information in order to satisfy the public. Consequently, this
paper examined the issue of fuel subsidy removal in Nigeria, the impact of the
policy on the public as well as the country and the role marketing principles
would have played if the Nigerian government had taken some time to investigate
what should be done, how it should be done and when it should be done. It also
proposed a roadmap for future policies that have direct implications for the
general public.


  For any countable torsion subgroup $H$ of an unbounded Abelian group $G$
there is a complete Hausdorff group topology $\tau$ such that $H$ is the von
Neumann radical of $(G,\tau)$. In particular, any unbounded torsion countable
Abelian group admits a complete Hausdorff minimally almost periodic (MinAP)
group topology. If $G$ is a bounded torsion countably infinite Abelian group,
then it admits a MinAP group topology if and only if all its leading
Ulm-Kaplansky invariants are infinite. In such a case, a MinAP group topology
can be chosen to be complete.


  The energy levels of the first few low-lying states of carbon in intense
magnetic fields upwards of $\approx 10^7$ T are calculated in this study. We
extend our previously employed pseudospectral approach for calculating the
eigenstates of the carbon atom. We report data for the ground state and a
low-lying state that are in good agreement with findings elsewhere, as well as
new data for ten other states of the carbon atom that have not been
investigated until now. It is seen that these hitherto uninvestigated states
also become strongly bound with increasing magnetic field strengths. The data
presented in this study are relevant for astrophysical applications, such as
magnetized white dwarf and neutron star spectral analysis as well as opacity
calculations and absorption features, including in the context of material
accreting onto the surfaces of these compact objects.


  We give a version in characteristic $p>0$ of Mumford's theorem characterizing
a smooth complex germ of surface $(X,x)$ by the triviality of the topological
fundamental group of $U=X\setminus \{x\}$.
  This note relies on discussions the authors had during the Christmas break
2009/10 in Ivry. They have been written down by H\'el\`ene in the night when
Eckart died, as a despaired sign of love.


  Mainstream parameter-efficient fine-tuning (PEFT) methods, such as LoRA or
Adapter, project a model's hidden states to a lower dimension, allowing
pre-trained models to adapt to new data through this low-rank bottleneck.
However, PEFT tasks involving multiple modalities, like vision-language (VL)
tasks, require not only adaptation to new data but also learning the
relationship between different modalities. Targeting at VL PEFT tasks, we
propose a family of operations, called routing functions, to enhance VL
alignment in the low-rank bottlenecks. These feature routing functions adopt
linear operations and do not introduce new trainable parameters. In-depth
analyses are conducted to study their behavior. In various VL PEFT settings,
the routing functions significantly improve performance of the original PEFT
methods, achieving over 20\% improvement on VQAv2
($\text{RoBERTa}_{\text{large}}$+ViT-L/16) and 30\% on COCO Captioning
(GPT2-medium+ViT-L/16). Also when fine-tuning a pre-trained multimodal model
such as CLIP-BART, we observe smaller but consistent improvements across a
range of VL PEFT tasks. Our code is available at
https://github.com/tingyu215/Routing_VLPEFT.


  We study Einstein's equation in $(m+n)D$ and $(1+n)D$ warped spaces
$(\bar{M},\bar{g})$ and classify all such spaces satisfying Einstein equations
$\bar{G}=-\bar{\Lambda}\bar{g}$. We show that the warping function not only can
determine the cosmological constant $\bar{\Lambda}$ but also it can determine
the cosmological constant ${\Lambda}$ appearing in the induced Einstein
equations ${G}=-{\Lambda}{h}$ on $(M_2, h)$. Moreover, we discuss on the origin
of the $4D$ cosmological constant as an emergent effect of higher dimensional
warped spaces.


  We propose a physics-aware machine learning method to time-accurately predict
extreme events in a turbulent flow. The method combines two radically different
approaches: empirical modelling based on reservoir computing, which learns the
chaotic dynamics from data only, and physical modelling based on conservation
laws. We show that the combination of the two approaches is able to predict the
occurrence and amplitude of extreme events in the self-sustaining process in
turbulence-the abrupt transitions from turbulent to quasi-laminar states-which
cannot be achieved by using either approach separately. This opens up new
possibilities for enhancing synergistically data-driven methods with physical
knowledge for the accurate prediction of extreme events in chaotic dynamical
systems.


  The emission spectrum from a simple accretion disk model around a compact
object is compared for the cases of a black hole (BH) and a boson star (BS)
playing the role of the central object. It was found in the past that such a
spectrum presents a hardening at high frequencies; however, here it is shown
that the self-interaction and compactness of the BS have the effect of
softening the spectrum, the less compact the star is, the softer the emission
spectrum at high frequencies. Because the mass of the boson fixes the mass of
the star and the self-interaction the compactness of the star, we find that,
for certain values of the BS parameters, it is possible to produce similar
spectra to those generated when the central object is a BH. This result
presents two important implications: (i) using this simple accretion model, a
BS can supplant a BH in the role of compact object accreting matter, and (ii)
within the assumptions of the present accretion disk model we do not find a
prediction that could help distinguish a BH from a BS with appropriate
parameters of mass and self-interaction.


  The gas and dust are spatially segregated in protoplanetary disks due to the
vertical settling and radial drift of large grains. A fuller accounting of the
mass content and distribution in disks therefore requires spectral line
observations. We extend the modeling approach presented in Williams & Best
(2014) to show that gas surface density profiles can be measured from high
fidelity 13CO integrated intensity images. We demonstrate the methodology by
fitting ALMA observations of the HD 163296 disk to determine a gas mass, Mgas =
0.048 solar masse, and accretion disk characteristic size Rc = 213au and
gradient gamma = 0.39. The same parameters match the C18O 2--1 image and
indicates an abundance ratio [13CO]/[C18O] of 700 independent of radius. To
test how well this methodology can be applied to future line surveys of
smaller, lower mass T Tauri disks, we create a large 13CO 2--1 image library
and fit simulated data. For disks with gas masses 3-10 Jupiter masses at 150pc,
ALMA observations with a resolution of 0.2-0.3 arcseconds and integration times
of about 20 minutes allow reliable estimates of Rc to within about 10au and
gamma to within about 0.2. Economic gas imaging surveys are therefore feasible
and offer the opportunity to open up a new dimension for studying disk
structure and its evolution toward planet formation.


  While previous works on privacy-preserving serial data publishing consider
the scenario where sensitive values may persist over multiple data releases, we
find that no previous work has sufficient protection provided for sensitive
values that can change over time, which should be the more common case. In this
work we propose to study the privacy guarantee for such transient sensitive
values, which we call the global guarantee. We formally define the problem for
achieving this guarantee and derive some theoretical properties for this
problem. We show that the anonymized group sizes used in the data anonymization
is a key factor in protecting individual privacy in serial publication. We
propose two strategies for anonymization targeting at minimizing the average
group size and the maximum group size. Finally, we conduct experiments on a
medical dataset to show that our method is highly efficient and also produces
published data of very high utility.


  We present the results of a molecular line survey of the extreme carbon star
CRL 3068. The observations were carried out with the Arizona Radio Observatory
(ARO) 12m telescope and the Heinrich Hertz Submillimeter Telescope (SMT) at the
2mm and 1.3mm atmospheric windows. The observations cover the frequency bands
from 130--162 GHz and 219.5--267.5 GHz. The typical sensitivities achieved are
T_R<15 mK and T_R<7 mK for the ARO 12m and SMT, respectively. Seventy two
individual emission features belonging to 23 molecular species and
isotopologues were detected. Only three faint lines remain unidentified. The
species c-C3H, CH3CN, SiC2, and the isotopologues, C17O and C18O, HC15N, HN13C,
C33S, C34S, 13CS, 29SiS, and 30SiS are detected in this object for the first
time. Rotational diagram analysis is carried out to determine the column
densities and excitation temperatures. The isotopic ratios of the elements C,
N, O, S, and Si have also been estimated. The results are consistent with
stellar CNO processing and suggest that CRL 3068 is more carbon rich than
IRC+10216 and CIT 6. It is also shown that the chemical composition in CRL 3068
is somewhat different from that in IRC+10216 with a more extensive synthesis of
cyclic and long-chain molecules in CRL 3068. The results will provide valuable
clues for better understanding circumstellar chemistry.


  We analyze intermediate degree p-mode eigenfrequencies measured by GONG and
MDI/SOHO over a solar cycle to study the source of their variability. We carry
out a correlation analysis between the change in frequencies and several
measures of the Sun's magnetic activity that are sensitive to changes at
different levels in the solar atmosphere. The observations span a period of
about 12 years starting from mid-1996 (the minimum of cycle 23) to early-2008
(near minimum of cycle 24), corresponding to a nearly complete solar activity
cycle. We demonstrate that the frequencies do vary in phase with the solar
activity indices, however the degree of correlation differs from phase to phase
of the cycle. During the rising and declining phases, the mode frequency shifts
are strongly correlated with the activity proxies whereas during the
high-activity period, the shifts have significantly lower correlation with all
activity proxies, except for the 10.7-cm radio flux. In particular, the proxies
that are only influenced by the variation of the strong component of the
magnetic field in the photosphere have a much lower correlation at the
high-activity period. On the other hand, the shifts are better correlated with
the proxies sensitive to changes in the weak component of the magnetic field.
Our correlation analysis suggests that more than 90% of the variation in the
oscillation frequencies in all activity phases can be explained by changes in
both components of the magnetic field. Further, the slopes obtained from the
linear regression analysis also differ from phase to phase and show a strong
correlation with the correlation coefficients between frequency shifts and
solar activity.


  Intelligent terminals support a large number of multimedia, such as picture,
audio, video, and so on. The coexistence of various multimedia makes it
necessary to provide service for different requests. In this work, we consider
interference-aware coordinated multi-point (CoMP) to mitigate inter-cell
interference and improve total throughput in the fifth-generation (5G) mobile
networks. To select the scheduled edge users, cluster the cooperative base
stations (BSs), and determine the transmitting power, a novel dynamic
bargaining approach is proposed. Based on affinity propagation, we first select
the users to be scheduled and the cooperative BSs serving them respectively.
Then, based on the Nash bargaining solution (NBS), we develop a power control
scheme considering the transmission delay, which guarantees a generalized
proportional fairness among users. Simulation results demonstrate the
superiority of the user-centric scheduling and power control methods in 5G CoMP
systems.


  We investigate the effect of thermal fluctuations on the mechanical
properties of nanotubes by employing tools from statistical physics. For 2D
sheets it was previously shown that thermal fluctuations effectively
renormalize elastic moduli beyond a characteristic temperature-dependent
thermal length scale (a few nanometers for graphene at room temperature), where
the bending rigidity increases, while the in-plane elastic moduli reduce in a
scale-dependent fashion with universal power law exponents. However, the
curvature of nanotubes produces new phenomena. In nanotubes, competition
between stretching and bending costs associated with radial fluctuations
introduces a characteristic elastic length scale, which is proportional to the
geometric mean of the radius and effective thickness. Beyond elastic length
scale, we find that the in-plane elastic moduli stop renormalizing in the axial
direction, while they continue to renormalize in the circumferential direction
beyond the elastic length scale albeit with different universal exponents. The
bending rigidity, however, stops renormalizing in the circumferential direction
at the elastic length scale. These results were verified using molecular
dynamics simulations.


  Star-planet interactions must be taken into account in stellar models to
understand the dynamical evolution of close-in planets. The dependence of the
tidal interactions on the structural and rotational evolution of the star is of
peculiar importance and should be correctly treated. We quantify how tidal
dissipation in the convective envelope of rotating low-mass stars evolves from
the pre-main sequence up to the red-giant branch depending on the initial
stellar mass. We investigate the consequences of this evolution on planetary
orbital evolution. We couple the tidal dissipation formalism described in
Mathis (2015) to the stellar evolution code STAREVOL and apply it to rotating
stars with masses between 0.3 and 1.4 M$_\odot$. In addition, we generalize the
work of Bolmont & Mathis (2016) by following the orbital evolution of close-in
planets using the new tidal dissipation predictions for advanced phases of
stellar evolution. On the PMS the evolution of tidal dissipation is controlled
by the evolution of the internal structure of the contracting star. On the MS
it is strongly driven by the variation of surface rotation that is impacted by
magnetized stellar winds braking. The main effect of taking into account the
rotational evolution of the stars is to lower the tidal dissipation strength by
about four orders of magnitude on the main-sequence, compared to a normalized
dissipation rate that only takes into account structural changes. The evolution
of the dissipation strongly depends on the evolution of the internal structure
and rotation of the star. From the pre-main sequence up to the tip of the
red-giant branch, it varies by several orders of magnitude, with strong
consequences for the orbital evolution of close-in massive planets. These
effects are the strongest during the pre-main sequence, implying that the
planets are mainly sensitive to the star's early history.


  We compute the abundance gradients along the disk of the Milky Way by means
of the two-infall model: in particular, the gradients of oxygen and iron and
their temporal evolution. First, we explore the effects of several physical
processes which influence the formation and evolution of abundance gradients.
They are: i) the inside-out formation of the disk, ii) a threshold in the gas
density for star formation, iii) a variable star formation efficiency along the
disk, iv) radial flows and their speed, and v) different total surface mass
density (gas plus stars) distributions for the halo. We are able to reproduce
at best the present day gradients of oxygen and iron if we assume an inside-out
formation, no threshold gas density, a constant efficiency of star formation
along the disk and radial gas flows. It is particularly important the choice of
the velocity pattern for radial flows and the combination of this velocity
pattern with the surface mass density distribution in the halo. Having selected
the best model, we then explore the evolution of abundance gradients in time
and find that the gradients in general steepen in time and that at redshift z~3
there is a gradient inversion in the inner regions of the disk, in the sense
that at early epochs the oxygen abundance decreases toward the Galactic center.
This effect, which has been observed, is naturally produced by our models if an
inside-out formation of the disk and and a constant star formation efficiency
are assumed. The inversion is due to the fact that in the inside-out formation
a strong infall of primordial gas, contrasting chemical enrichment, is present
in the innermost disk regions at early times. The gradient inversion remains
also in the presence of radial flows, either with constant or variable speed in
time, and this is a new result.


  Photonic and optoelectronic devices may offer the opportunity to realize
efficient signal processing at speeds higher than in conventional electronic
devices. Switches form the building blocks for circuits and fast photonic
switches have been realized [1,2,3,4,5,6]. Recently, proof of principle of
exciton optoelectronic devices was demonstrated [7,8]. Potential advantages of
excitonic devices include high operation and interconnection speed, small
dimensions, and the opportunity to combine many elements into integrated
circuits. Here, we demonstrate experimental proof of principle for the
operation of excitonic switching devices at temperatures around 100 K. The
devices are based on an AlAs/GaAs coupled quantum well structure and include
the exciton optoelectronic transistor (EXOT), the excitonic bridge modulator
(EXBM), and the excitonic pinch-off modulator (EXPOM). This is a two orders of
magnitude increase in the operation temperature compared to the earlier
devices, where operation was demonstrated at 1.5 K [7,8].


  Interferometers from the ground and space will be able to resolve the two
images in a microlensing event. This will at least partially lift the inherent
degeneracy between physical parameters in microlensing events. To increase the
signal-to-noise ratio, intrinsically bright events with large magnifications
will be preferentially selected as targets. These events may be influenced by
finite source size effects both photometrically and astrometrically. Using
observed finite source size events as examples, we show that the fringe
visibility can be affected by 5% - 10%, and the closure phase by a few degrees:
readily detectable by ground and space interferometers. Such detections will
offer unique information about the lens-source trajectory relative to the
baseline of the interferometers. Combined with photometric finite source size
effects, interferometry offers a way to measure the angular sizes of the source
and the Einstein radius accurately.
  Limb-darkening changes the visibility by a small amount compared with a
source with uniform surface brightness, marginally detectable with ground-based
instruments.
  We discuss the implications of our results for the plans to make
interferometric observations of future microlensing events.


  In the present paper we review in a fibre bundle context the covariant and
massless canonical representations of the Poincare' group as well as certain
unitary representations of the conformal group (in 4 dimensions). We give a
simplified proof of the well-known fact that massless canonical representations
with discrete helicity extend to unitary and irreducible representations of the
conformal group mentioned before. Further we give a simple new proof that
massless free nets for any helicity value are covariant under the conformal
group. Free nets are the result of a direct (i.e. independent of any explicit
use of quantum fields) and natural way of constructing nets of abstract
C*-algebras indexed by open and bounded regions in Minkowski space that satisfy
standard axioms of local quantum physics. We also give a group theoretical
interpretation of the embedding ${\got I}$ that completely characterizes the
free net: it reduces the (algebraically) reducible covariant representation in
terms of the unitary canonical ones. Finally, as a consequence of the conformal
covariance we also mention for these models some of the expected algebraic
properties that are a direct consequence of the conformal covariance (essential
duality, PCT--symmetry etc.).


  Electronic transport has been investigated for strong spin-orbit coupled
perovskite SrIrO3 thin films grown at various substrate temperatures. The
electronic transport of the SrIrO3 films is found to be very sensitive to the
growth parameters; in particular, the film can either be a metal or an
insulator depending upon the substrate growth temperature. While all the
metallic films show unusual sublinear temperature dependent non-Fermi liquid
behaviors in resistivity, the insulating film grown at a higher temperature
stands out for its inhomogeneous Ir distribution, as analyzed by secondary ion
mass spectrometry. This observation demonstrates that the inhomogeneous
distribution of cations can be one of the fundamental factors in affecting the
electronic transport in heavy element based oxide films and heterostructures.


  We study strongly convex distributed optimization problems where a set of
agents are interested in solving a separable optimization problem
collaboratively. In this paper, we propose and study a two time-scale
decentralized gradient descent algorithm for a broad class of lossy sharing of
information over time-varying graphs. One time-scale fades out the (lossy)
incoming information from neighboring agents, and one time-scale regulates the
local loss functions' gradients. For strongly convex loss functions, with a
proper choice of step-sizes, we show that the agents' estimates converge to the
global optimal state at a rate of $O(T^{-1/2})$. Another important contribution
of this work is to provide novel tools to deal with diminishing average weights
over time-varying graphs.


  We give a new characterization of elementary and deterministic polynomial
time computation in linear logic through the proofs-as-programs correspondence.
Girard's seminal results, concerning elementary and light linear logic, achieve
this characterization by enforcing a stratification principle on proofs, using
the notion of depth in proof nets. Here, we propose a more general form of
stratification, based on inducing levels in proof nets by means of indexes,
which allows us to extend Girard's systems while keeping the same complexity
properties. In particular, it turns out that Girard's systems can be recovered
by forcing depth and level to coincide. A consequence of the higher flexibility
of levels with respect to depth is the absence of boxes for handling the
paragraph modality. We use this fact to propose a variant of our polytime
system in which the paragraph modality is only allowed on atoms, and which may
thus serve as a basis for developing lambda-calculus type assignment systems
with more efficient typing algorithms than existing ones.


  This paper studies iteration convergence of Kronecker graphical lasso
(KGLasso) algorithms for estimating the covariance of an i.i.d. Gaussian random
sample under a sparse Kronecker-product covariance model and MSE convergence
rates. The KGlasso model, originally called the transposable regularized
covariance model by Allen ["Transposable regularized covariance models with an
application to missing data imputation," Ann. Appl. Statist., vol. 4, no. 2,
pp. 764-790, 2010], implements a pair of $\ell_1$ penalties on each Kronecker
factor to enforce sparsity in the covariance estimator. The KGlasso algorithm
generalizes Glasso, introduced by Yuan and Lin ["Model selection and estimation
in the Gaussian graphical model," Biometrika, vol. 94, pp. 19-35, 2007] and
Banerjee ["Model selection through sparse maximum likelihood estimation for
multivariate Gaussian or binary data," J. Mach. Learn. Res., vol. 9, pp.
485-516, Mar. 2008], to estimate covariances having Kronecker product form. It
also generalizes the unpenalized ML flip-flop (FF) algorithm of Dutilleul ["The
MLE algorithm for the matrix normal distribution," J. Statist. Comput. Simul.,
vol. 64, pp. 105-123, 1999] and Werner ["On estimation of covariance matrices
with Kronecker product structure," IEEE Trans. Signal Process., vol. 56, no. 2,
pp. 478-491, Feb. 2008] to estimation of sparse Kronecker factors. We establish
that the KGlasso iterates converge pointwise to a local maximum of the
penalized likelihood function. We derive high dimensional rates of convergence
to the true covariance as both the number of samples and the number of
variables go to infinity. Our results establish that KGlasso has significantly
faster asymptotic convergence than Glasso and FF. Simulations are presented
that validate the results of our analysis.


  We study the effects of spontaneous emission on the entanglement dynamics of
two qubits interacting with a common Lorentzian structured reservoir. We assume
that the qubits are initially prepared in a Bell-like state. We focus on the
strong coupling regime and study the entanglement dynamics for different
regions of the spontaneous emission decay parameter. This investigation allows
us to explore the cross-over between common and independent reservoirs in
entanglement dynamics.


  This paper deals with the stabilization problem for nonlinear control-affine
systems with the use of oscillating feedback controls. We assume that the local
controllability around the origin is guaranteed by the rank condition with Lie
brackets of length up to 3. This class of systems includes, in particular,
mathematical models of rotating rigid bodies. We propose an explicit control
design scheme with time-varying trigonometric polynomials whose coefficients
depend on the state of the system. The above coefficients are computed in terms
of the inversion of the matrix appearing in the controllability condition. It
is shown that the proposed controllers can be used to solve the stabilization
problem by exploiting the Chen-Fliess expansion of solutions of the closed-loop
system. We also present results of numerical simulations for controlled Euler's
equations and a mathematical model of underwater vehicle to illustrate the
efficiency of the obtained controllers.


  We use the Graph Minor Theorem to characterize infinite sequences of finite
subsets of factorial and commutative semigroups (here semigroups have a unity
element), e.g. the multiplicative semigroup of a unique factorization domain.


  In this work, we investigate the fewest number of colors needed to guarantee
a rainbow solution to the equation $x_1 + x_2 = k x_3$ in $\mathbb{Z}_n$. This
value is called the Rainbow number and is denoted by $rb(\mathbb{Z}_n, k)$ for
positive integer values of $n$ and $k$. We find that $rb(\mathbb{Z}_p, 1) = 4$
for all primes greater than $3$ and that $rb(\mathbb{Z}_n, 1)$ can be
deterimined from the prime factorization of $n$. Furthermore, when $k$ is
prime, $rb(\mathbb{Z}_n, k)$ can be determined from the prime factorization of
$n$.


  Metal-organic frameworks (MOFs) are a specific class of hybrid, crystalline,
nano-porous materials made of metal-ion-based nodes and organic linkers. Most
of the studies on MOFs largely focused on porosity, chemical and structural
diversity, gas sorption, sensing, drug delivery, catalysis, and separation
applications. In contrast, much less reports paid attention to understanding
and tuning the electrical properties of MOFs. Poor electrical conductivity of
MOFs reported in earlier studies, impeded their applications in electronics,
optoelectronics, and renewable energy storage. To overcome this drawback, the
MOF community has adopted several intriguing strategies for electronic
applications. The present review focuses on creatively designed bulk MOFs and
surface-anchored MOFs (SURMOFs) with different metal nodes (from transition
metals to lanthanides), ligand functionalities, and doping entities, allowing
tuning and enhancement of electrical conductivity. Diverse platforms for
MOFs-based electronic device fabrications, conductivity measurements, and
underlying charge transport mechanisms are also addressed. Overall, the review
highlights the pros and cons of MOFs-based electronics, followed by an analysis
of the future directions of research, including optimization of the MOF
compositions, heterostructures, electrical contacts, device stacking, and
further relevant options which can be of interest for MOF researchers and
result in improved devices performance.


  As a basis for epistemological study of ``time,'' we analyze three suspect
phenomena introduced by modern physics: non-locality, asymmetric aging and
advanced interaction. It is shown that all three arise in connection with what
has to be taken as arbitrary ideosyncrasies in formulation. It is shown that
minor changes result in internally consistent variations of both Quantum
Mechanics and Special Relativity devoid of these phenomena. The
reinterpretation of some experiments though to confirm the existence of
non-locality and asymmetric aging is briefly considered and a possible test is
proposed.


  The two CCD photometries of the intermediate polar TV Columbae are made for
obtaining the two updated eclipse timings with high precision. There is an
interval time \sim 17yr since the last mid-eclipse time observed in 1991. Thus,
the new mid-eclipse times can offer an opportunity to check the previous
orbital ephemerides. A calculation indicates that the orbital ephemeris derived
by Augusteijn et al. (1994) should be corrected. Based on the proper linear
ephemeris (Hellier, 1993), the new orbital period analysis suggests a cyclical
period variation in the O-C diagram of TV Columbae. Using Applegate's mechanism
to explain the periodic oscillation in O-C diagram, the required energy is
larger than that a M0-type star can afford over a complete variation period
\sim 31.0(\pm 3.0)yr. Thus, the light travel-time effect indicates that the
tertiary component in TV Columbae may be a dwarf with a low mass, which is near
the mass lower limit \sim 0.08Msun as long as the inclination of the third body
high enough.


  Automotive scene understanding under adverse weather conditions raises a
realistic and challenging problem attributable to poor outdoor scene visibility
(e.g. foggy weather). However, because most contemporary scene understanding
approaches are applied under ideal-weather conditions, such approaches may not
provide genuinely optimal performance when compared to established a priori
insights on extreme-weather understanding. In this paper, we propose a complex
but competitive multi-task learning approach capable of performing in real-time
semantic scene understanding and monocular depth estimation under foggy weather
conditions by leveraging both recent advances in adversarial training and
domain adaptation. As an end-to-end pipeline, our model provides a novel
solution to surpass degraded visibility in foggy weather conditions by
transferring scenes from foggy to normal using a GAN-based model. For optimal
performance in semantic segmentation, our model generates depth to be used as
complementary source information with RGB in the segmentation network. We
provide a robust method for foggy scene understanding by training two models
(normal and foggy) simultaneously with shared weights (each model is trained on
each weather condition independently). Our model incorporates RGB colour,
depth, and luminance images via distinct encoders with dense connectivity and
features fusing, and leverages skip connections to produce consistent depth and
segmentation predictions. Using this architectural formulation with light
computational complexity at inference time, we are able to achieve comparable
performance to contemporary approaches at a fraction of the overall model
complexity.


  Forecasting future stock trends remains challenging for academia and industry
due to stochastic inter-stock dynamics and hierarchical intra-stock dynamics
influencing stock prices. In recent years, graph neural networks have achieved
remarkable performance in this problem by formulating multiple stocks as
graph-structured data. However, most of these approaches rely on artificially
defined factors to construct static stock graphs, which fail to capture the
intrinsic interdependencies between stocks that rapidly evolve. In addition,
these methods often ignore the hierarchical features of the stocks and lose
distinctive information within. In this work, we propose a novel graph learning
approach implemented without expert knowledge to address these issues. First,
our approach automatically constructs dynamic stock graphs by entropy-driven
edge generation from a signal processing perspective. Then, we further learn
task-optimal dependencies between stocks via a generalized graph diffusion
process on constructed stock graphs. Last, a decoupled representation learning
scheme is adopted to capture distinctive hierarchical intra-stock features.
Experimental results demonstrate substantial improvements over state-of-the-art
baselines on real-world datasets. Moreover, the ablation study and sensitivity
study further illustrate the effectiveness of the proposed method in modeling
the time-evolving inter-stock and intra-stock dynamics.


  We investigate a way to suppress high-frequency coupling between a gate and
low-dimensional electron systems in the gigahertz range by measuring the
velocity of edge magnetoplasmons (EMPs) in InAs quantum Hall systems.We compare
the EMPvelocity in three samples with different electromagnetic
environments-one has a highly resistive zinc oxide (ZnO) top gate, another has
a normal metal (Ti/Au) top gate, and the other does not have a gate. The
measured EMP velocity in the ZnO gate sample is one order of magnitude larger
than that in the Ti/Au gate sample and almost the same as that in the ungated
sample. As is well known, the smaller velocity in the Ti/Au gate sample is due
to the screening of the electric field in EMPs. The suppression of the gate
screening effect in the ZnO gate sample allows us to measure the velocity of
unscreened EMPs while changing the electron density. It also offers a way to
avoid unwanted high-frequency coupling between quantum Hall edge channels and
gate electrodes.


  Synesthesia, conceived as a neuropsychological condition, may prove valuable
in studying the interaction between humans and machines by analyzing the
co-occurrence of sensory or cognitive responses triggered by a stimulus. In our
approach, synesthesia is elevated beyond a mere perceptual-cognitive anomaly,
offering insights into the reciprocal interaction between humans and the
digital system, steering novel experimental design and enriching results
interpretations.This review broadens the traditional scope, conventionally
rooted in neuroscience and psychology, by considering how computer science can
approach this condition. The interdisciplinary examination revolves around two
primary viewpoints: one associating this condition with specific cognitive,
perceptual, and behavioral anomalies, and the other acknowledging it as a
prevalent human experience. Synesthesia, in this review, emerges as a
significant model for Human Computer Interaction (HCI). The exploration of this
specific condition aims to decipher how atypical pathways of perception and
cognition can be encoded, empowering machines to actively engage in processing
information from both the body and the environment. The authors attempt to
amalgamate findings and insights from various disciplines, fostering
collaboration between computer science, neuroscience, psychology, and
philosophy.The overarching objective is to construct a comprehensive framework
that elucidates how synesthesia and anomalies in information processing can be
harnessed within HCI, with a particular emphasis on contributing to digital
technologies for medical research and enhancing patients care and comfort. In
this sense, the review endeavors also to fill the gap between theoretical
understanding and practical application.


  In this paper we revisit a discrete spectral problem which was proposed by
Ragnisco and Tu in 1989, as a second discretization of the ZS-AKNS spectral
problem. We show that the spectral problem corresponds to a bidirectional
discretization of the derivative of two wave functions $\phi_{1,x}$ and
$\phi_{2,x}$. As a connection with higher dimensional systems, the spectral
problem and a related hierarchy can be derived from Lax triads of the
differential-difference KP hierarchy via a symmetry constraint. Isospectral and
nonisospectral flows derived from the spectral problem compose a Lie algebra.
By considering its infinite dimensional subalgebras and continuum limit of
recursion operator, three semi-discrete AKNS hierarchies are constructed.


  The two-point Green function of the massive scalar $(3+1)$-quantum field
theory with $\lambda\phi^4$ interaction at finite temperature is evaluated up
to the 2nd order of perturbation theory. The averaging on the vacuum
fluctuations is separated from the averaging on the thermal fluctuations
explicitly. As a result, the temperature dependent part of the propagator is
expressed through the scattering amplitudes. The obtained expression is
generalized for higher orders of perturbation theory.


  A category N of labeled (oriented) trivalent graphs (nets) or ribbon graphs
is extended by new generators called fusing, braiding, twist and switch with
relations which can be called Moore--Seiberg relations. A functor to N is
constructed from the category Surf of oriented surfaces with labeled boundary
and their homeomorphisms. Given an (eventually non-semisimple) k-linear abelian
ribbon braided category C with some finiteness conditions we construct a
functor from a central extension of N with the set of labels ObC to k-vector
spaces. Composing the functors we get a modular functor from a central
extension of Surf to k-vector spaces. This is a mathematical paper which
explains how to get proofs for its hep-th companion paper, which should be read
first. Complete proofs are not given here. (Talk at Second Gauss Simposium,
Munich, August 1993.)


  Context: We present a newly discovered class of low-luminosity, dusty,
evolved objects in the Magellanic Clouds. These objects have dust excesses,
stellar parameters, and spectral energy distributions similar to those of dusty
post-asymptotic giant branch (post-AGB) stars. However, they have lower
luminosities and hence lower masses. We suggest that they have evolved off the
red giant branch (RGB) instead of the AGB as a result of binary interaction.
Aims: In this study we aim to place these objects in an evolutionary context
and establish an evolutionary connection between RGB binaries (such as the
sequence E variables) and our new sample of objects. Methods: We compared the
theoretically predicted birthrates of the progeny of RGB binaries to the
observational birthrates of the new sample of objects. Results: We find that
there is order-of-magnitude agreement between the observed and predicted
birthrates of post-RGB stars. The sources of uncertainty in the birthrates are
discussed; the most important sources are probably the observational
incompleteness factor and the post-RGB evolution rates. We also note that
mergers are relatively common low on the RGB and that stars low on the RGB with
mid-IR excesses may recently have undergone a merger. Conclusions: Our sample
of dusty post-RGB stars most likely provides the first observational evidence
for a newly discovered phase in binary evolution: post-RGB binaries with
circumstellar dust.


  In this paper, we address the problem of recovering complex-valued signals
from a set of complex-valued linear measurements. Approximate message passing
(AMP) is one state-of-the-art algorithm to recover real-valued sparse signals.
However, the extension of AMP to complex-valued case is nontrivial and no
detailed and rigorous derivation has been explicitly presented. To fill this
gap, we extend AMP to complex Bayesian approximate message passing (CB-AMP)
using expectation propagation (EP). This novel perspective leads to a concise
derivation of CB-AMP without sophisticated transformations between the complex
domain and the real domain. In addition, we have derived state evolution
equations to predict the reconstruction performance of CB-AMP. Simulation
results are presented to demonstrate the efficiency of CB-AMP and state
evolution.


  We prove that the weighted KLRW algebras of finite type, and their cyclotomic
quotients, are cellular algebras. The cellular bases are explicitly described
using crystal graphs. As a special case, this proves that the KLR algebras of
finite type are cellular. As one application, we compute the graded
decomposition numbers of the cyclotomic algebras.


  In this paper we derive some new and practical results on testing and
interval estimation problems for the population eigenvalues of a Wishart matrix
based on the asymptotic theory for block-wise infinite dispersion of the
population eigenvalues. This new type of asymptotic theory has been developed
by the present authors in Takemura and Sheena (2005) and Sheena and Takemura
(2007a,b) and in these papers it was applied to point estimation problem of
population covariance matrix in a decision theoretic framework. In this paper
we apply it to some testing and interval estimation problems. We show that the
approximation based on this type of asymptotics is generally much better than
the traditional large-sample asymptotics for the problems.


  The h-index can be used as a predictor of itself. However, the evolution of
the h-index with time is shown in the present investigation to be dominated for
several years by citations to previous publications rather than by new
scientific achievements. This inert behaviour of the h-index raises questions,
whether the h-index can be used profitably in academic appointment processes or
for the allocation of research resources.


  Acoustic word embeddings (AWEs) aims to map a variable-length speech segment
into a fixed-dimensional representation. High-quality AWEs should be invariant
to variations, such as duration, pitch and speaker. In this paper, we introduce
a novel self-supervised method to learn robust AWEs from a large-scale
unlabelled speech corpus. Our model, named Correspondence Transformer Encoder
(CTE), employs a teacher-student learning framework. We train the model based
on the idea that different realisations of the same word should be close in the
underlying embedding space. Specifically, we feed the teacher and student
encoder with different acoustic instances of the same word and pre-train the
model with a word-level loss. Our experiments show that the embeddings
extracted from the proposed CTE model are robust to speech variations, e.g.
speakers and domains. Additionally, when evaluated on Xitsonga, a low-resource
cross-lingual setting, the CTE model achieves new state-of-the-art performance.


  We study the evolution and observability of young, compact star clusters near
the Galactic center, such as the Arches and Quintuplet systems. The clusters
are modeled by integrating the equations of motion of all stars while
accounting for the internal evolution of stars and binaries, as well as the
effect of the Galactic tidal field. We find that clusters within 150 pc of the
Galactic center dissolve within ~55 Myr, but their projected densities drop
below the background density in the direction of the Galactic center within
only a few Myr, effectively making these clusters undetectable after that time.
Detailed observations of the Arches cluster, taken at face value, suggest that
its mass function is unusually flat and that the cluster contains an
overabundance of stars more massive than 20 Msun. Our dynamical analysis,
however, shows that the observed characteristics of the Arches cluster are
consistent with a perfectly normal initial mass function. The observed
anomalies are then caused by a combination of observational selection effects
and the dynamical evolution of the cluster. We calibrate the current parameters
of the Arches cluster using a normal initial mass function and conclude that
the cluster is more massive than 40000 Msun, has a half mass radius of about
0.35 pc and is located between 50 and 90 pc from the Galactic center.


  A locating-dominating set of a graph $G$ is a dominating set of $G$ such that
every vertex of $G$ outside the dominating set is uniquely identified by its
neighborhood within the dominating set. The location-domination number of $G$
is the minimum cardinality of a locating-dominating set in $G$. Let $G_{1}$ and
$G_{2}$ be the disjoint copies of a graph $G$ and $f:V(G_{1})\rightarrow
V(G_{2})$ be a function. A functigraph $F^f_{G}$ consists of the vertex set
$V(G_{1})\cup V(G_{2})$ and the edge set $E(G_{1})\cup E(G_{2})\cup
\{uv:v=f(u)\}$. In this paper, we study the variation of the
location-domination number in passing from $G$ to $F^f_{G}$ and find its sharp
lower and upper bounds. We also study the location-domination number of
functigraphs of the complete graphs for all possible definitions of the
function $f$. We also obtain the location-domination number of functigraphs of
a family of spanning subgraph of the complete graphs.


  Blue Stragglers are stars located in an unexpected region of the
color-magnitude diagram of a stellar population, as they appear bluer and more
luminous than the stars in the turnoff region. They are ubiquitous, since they
have been found among Milky Way field stars, in open and globular clusters, and
also in other galaxies of the Local Group. Here we present a study on the blue
straggler population of the old and metal-rich open cluster Collinder 261,
based on Gaia DR2 data and on a multi-epoch radial velocity survey conducted
with FLAMES@VLT. We also analyze the radial distribution of the blue straggler
population to probe the dynamical status of the cluster. Blue straggler
candidates were identified first with Gaia DR2, according to their position on
the CMD, proper motions, and parallaxes. Their radial distribution was compared
with those of the main sequence, red giant, and red clump stars, to evaluate
mass segregation. Additionally, their radial velocities (and the associated
uncertainties) were compared with the mean radial velocity and the velocity
dispersion of the cluster. When possible, close binaries and long-period
binaries were also identified, based on the radial velocity variations for the
different epochs. We also looked for yellow stragglers, i.e., possible evolved
blue stragglers. We found 53 blue stragglers members of Collinder 261, six of
them already identified in previous catalogs. Among the blue straggler
candidates with radial velocity measurements, we found one long-period binary,
five close-binary systems, three non-variable stars; we also identified one
yellow straggler.


  Reinforcement learning algorithms need exploration to learn. However,
unsupervised exploration prevents the deployment of such algorithms on
safety-critical tasks and limits real-world deployment. In this paper, we
propose a new algorithm called Ensemble Model Predictive Safety Certification
that combines model-based deep reinforcement learning with tube-based model
predictive control to correct the actions taken by a learning agent, keeping
safety constraint violations at a minimum through planning. Our approach aims
to reduce the amount of prior knowledge about the actual system by requiring
only offline data generated by a safe controller. Our results show that we can
achieve significantly fewer constraint violations than comparable reinforcement
learning methods.


  We develop a general approach to Stein's method for approximating a random
process in the path space $D([0,T]\to R^d)$ by a real continuous Gaussian
process. We then use the approach in the context of processes that have a
representation as integrals with respect to anunderlying point process,
deriving a general quantitative Gaussian approximation. The error bound is
expressed in terms of couplings of the original process to processes generated
from the reduced Palm measures associated with the point process. As
applications, we study certain $\text{GI}/\text{GI}/\infty$ queues in the
"heavy traffic" regime.


  Since only recently, cosmological observations are sensitive to hot dark
matter (HDM) admixtures with sub-eV mass, $m_\text{hdm}^\text{eff}$ < eV, that
are not fully-thermalised, $N_\text{eff}$ < 1. We argue that their almost
automatic interpretation as a sterile neutrino species is neither from
theoretical nor practical parsimony principles preferred over HDM formed by
decay products (daughters) of an out-of-equilibrium particle decay. While
daughters mimic sterile neutrinos in $N_\text{eff}$ and
$m_\text{hdm}^\text{eff}$, there are opportunities to assess this possibility
in likelihood analyses. Connecting cosmological parameters and moments of
momentum distribution functions, we show that --also in the case of
mass-degenerate daughters with indistinguishable main physical effects-- the
mimicry breaks down when the next moment, the skewness, is considered.
Predicted differences of order one in the root-mean-squares of absolute momenta
are too small for current sensitivities.


  Ovarian cancer is the most lethal cancer of the female reproductive organs.
There are $5$ major histological subtypes of epithelial ovarian cancer, each
with distinct morphological, genetic, and clinical features. Currently, these
histotypes are determined by a pathologist's microscopic examination of tumor
whole-slide images (WSI). This process has been hampered by poor inter-observer
agreement (Cohen's kappa $0.54$-$0.67$). We utilized a \textit{two}-stage deep
transfer learning algorithm based on convolutional neural networks (CNN) and
progressive resizing for automatic classification of epithelial ovarian
carcinoma WSIs. The proposed algorithm achieved a mean accuracy of $87.54\%$
and Cohen's kappa of $0.8106$ in the slide-level classification of $305$ WSIs;
performing better than a standard CNN and pathologists without
gynecology-specific training.


  Existing Orthogonal Frequency-Division Multiplexing (OFDM) variants based on
cyclic prefix (CP) allow for efficient time synchronization, but suffer from
lower power efficiency compared to zero-padded (ZP)-OFDM. Because of its power
efficiency, ZP-OFDM is considered as an appealing solution for the emerging
low-power wireless systems. However, in the absence of CP, time synchronization
in ZP-OFDM is a very challenging task. In this paper, the non-data-aided (NDA)
maximum-likelihood (ML) time synchronization for ZP-OFDM is analytically
derived. We show that the optimal NDA-ML synchronization algorithm offers a
high lock-in probability and can be efficiently implemented using Monte Carlo
sampling (MCS) technique in combination with golden-section search. To obtain
the optimal NDA-ML time synchronization algorithm, we first derive a
closed-form expression for the joint probability density function (PDF) of the
received ZP-OFDM samples in frequency-selective fading channels. The derived
expression is valid for doubly-selective fading channels with mobile users as
well. The performance of the proposed synchronization algorithm is evaluated
under various practical settings through simulation experiments. It is shown
that the proposed optimal NDA-ML synchronization algorithm and its MCS
implementation substantially outperforms existing algorithms in terms of
lock-in probability.


  Automatic identity recognition from ear images represents an active field of
research within the biometric community. The ability to capture ear images from
a distance and in a covert manner makes the technology an appealing choice for
surveillance and security applications as well as other application domains.
Significant contributions have been made in the field over recent years, but
open research problems still remain and hinder a wider (commercial) deployment
of the technology. This paper presents an overview of the field of automatic
ear recognition (from 2D images) and focuses specifically on the most recent,
descriptor-based methods proposed in this area. Open challenges are discussed
and potential research directions are outlined with the goal of providing the
reader with a point of reference for issues worth examining in the future. In
addition to a comprehensive review on ear recognition technology, the paper
also introduces a new, fully unconstrained dataset of ear images gathered from
the web and a toolbox implementing several state-of-the-art techniques for ear
recognition. The dataset and toolbox are meant to address some of the open
issues in the field and are made publicly available to the research community.


  The associate production of Higgs bosons with W or Z bosons, known as
Higgs-strahlung, is an important search channel for Higgs bosons at the hadron
colliders Tevatron and LHC for low Higgs-boson masses. We refine a previous
calculation of next-to-leading-order electroweak corrections (and recalculate
the QCD corrections) upon including the leptonic decay of the W/Z bosons,
thereby keeping the fully differential information of the 2-lepton + Higgs
final state. The gauge invariance of the W/Z-resonance treatment is ensured by
the use of the complex-mass scheme. The electroweak corrections, which are at
the level of -(5-10)% for total cross sections, further increase in size with
increasing transverse momenta p_T in differential cross sections. For instance,
for p_T,H >~ 200GeV, which is the interesting range at the LHC, the electroweak
corrections to WH production reach about -14% for M_H = 120GeV. The described
corrections are implemented in the HAWK Monte Carlo program, which was
initially designed for the vector-boson-fusion channel, and are discussed for
various distributions in the production channels pp / p \bar p -> H + l nu_l /
l^-l^+ / nu_l \bar nu_l + X.


  A search for a manifestly exotic S=-2 baryon state decaying to Xi- pi-, and
its neutral partner decaying to Xi- pi+, has been performed using 220 pb^(-1)
of pp= collisions at sqrt(s)=1.96 TeV collected by the Collider Detector at
Fermilab. The Xi trajectories were measured in a silicon tracker before their
decay, resulting in a sample with low background and excellent position
resolution. No evidence was found for S=-2 pentaquark candidates in the
invariant mass range of 1600--2100 MeV/c^2 Upper limits on the product of
pentaquark production cross section times its branching fraction to Xi-
pi^{+,-}, relative to the cross section of the well established Xi(1530)
resonance, are presented for neutral and doubly negative candidates with pT>2
GeV/c and |y|<1 as a function of pentaquark mass. At 1862 MeV/c^2, these upper
limits for neutral and doubly negative final states were found to be 3.2% and
1.7% at the 90% confidence level, respectively.


  We propose a method for the dynamical control in three-level open systems and
realize it in the experiment with a superconducting qutrit. Our work
demonstrates that in the Markovian environment for a relatively long time (3
us), the systemic populations or coherence can still strictly follow the preset
evolution paths. This is the first experiment for precisely controlling the
Markovian dynamics of three-level open systems, providing a solid foundation
for the future realization of dynamical control in multiple open systems. An
instant application of the techniques demonstrated in this experiment is to
stabilize the energy of quantum batteries.


  We study theoretically diffusion of one-dimensional Frenkel excitons in
J-aggregates at temperatures that are smaller or of the order of the J-band
width. We consider an aggregate as an open linear chain with uncorrelated
on-site (diagonal) disorder that localizes the exciton at chain segments of
size smaller than the full chain length. The exciton diffusion over the
localization segments is considered as incoherent hopping. The diffusion is
probed by the exciton fluorescence quenching which is due to the presence of
point traps in the aggregate. The rate equation for populations of the
localized exciton states is used to describe the exciton diffusion and
trapping. We show that there exist two regimes of the exciton diffusion at low
temperatures. The first, slower one, involves only the states of the very tail
of the density of states, while the second, much faster one, also involves the
higher states that are close to the bottom of the exciton band. The activation
energy for the first regime of diffusion is of the order of one fifth of the
J-band width, while for the second one it is of the order of the full J-band
width. We discuss also the experimental data on the fast low-temperature
exciton-exciton annihilation reported recently by I. G. Scheblykin {\em et al},
J. Phys. Chem. B {\bf 104}, 10949 (2000).


  We present a study of the 1+1 flavor system of strongly interacting matter in
terms of the Polyakov$-$Nambu$-$Jona-Lasinio model. We find that though the
small isospin symmetry breaking brought in through unequal light quark masses
is too small to affect the thermodynamics of the system in general, it may have
significant effect in baryon-isospin correlations and have a measurable impact
in heavy-ion collision experiments.


  Considering the increasing penetration of renewable energy sources and
electrical vehicles in utility distribution feeders, it is imperative to study
the impacts of the resulting increasing uncertainty on the delivery capability
of a distribution network. In this paper, probabilistic available delivery
capability (ADC) is formulated for a general distribution network integrating
various RES and load variations. To reduce the computational efforts by using
conventional Monte Carlo simulations, we develop and employ a computationally
efficient method to assess the probabilistic ADC, which combines the up-to-date
sparse polynomial chaos expansion (PCE) and the continuation method.
Particularly, the proposed method is able to handle a large number of
correlated random inputs with different marginal distributions. Numerical
examples in the IEEE 13 and IEEE 123 node test feeders are presented, showing
that the proposed method can achieve accuracy and efficiency simultaneously.
Numerical results also demonstrate that the randomness brought about by the RES
and loads indeed leads to a reduction in the delivery capability of a
distribution network.


  In this paper, we propose a new measure for the freshness of information,
which uses the mutual information between the real-time source value and the
delivered samples at the receiver to quantify the freshness of the information
contained in the delivered samples. Hence, the "aging" of the received
information can be interpreted as a procedure that the above mutual information
reduces as the age grows. In addition, we consider a sampling problem, where
samples of a Markov source are taken and sent through a queue to the receiver.
In order to optimize the freshness of information, we study the optimal
sampling policy that maximizes the time-average expected mutual information. We
prove that the optimal sampling policy is a threshold policy and find the
optimal threshold exactly. Specifically, a new sample is taken once a
conditional mutual information term reduces to a threshold, and the threshold
is equal to the optimum value of the time-average expected mutual information
that is being maximized. Numerical results are provided to compare different
sampling policies.


  By using the symmetry improved CJT effective formalism, we study a pion
string of the $O(4)$ linear sigma model at finite temperature in chiral limit.
In terms of the Kibble-Zurek mechanism we reconsider the production and
evolution of the pion string in a thermal bath. Finally, we estimate the pion
string density and its possible signal during the chiral phase transition.


  In this paper, we present an adjustable-equilibrium parallel elastic actuator
(AE-PEA). The actuator consists of a motor, an equilibrium adjusting mechanism,
and a spring arranged into a cylindrical geometry, similar to a motor-gearbox
assembly. The novel component of the actuator is the equilibrium adjusting
mechanism which (i) does not require external energy to maintain the
equilibrium position of the actuator even if the spring is deformed and (ii)
enables equilibrium position control with low energy cost by rotating the
spring while keeping it undeformed. Adjustable equilibrium parallel elastic
actuators resolve the main limitation of parallel elastic actuators (PEAs) by
enabling energy-efficient operation at different equilibrium positions, instead
of being limited to energy-efficient operation at a single equilibrium
position. We foresee the use of AE-PEAs in industrial robots, mobile robots,
exoskeletons, and prostheses, where efficient oscillatory motion and gravity
compensation at different positions are required.


  Developing a universal model that can effectively harness heterogeneous
resources and respond to a wide range of personalized needs has been a
longstanding community aspiration. Our daily choices, especially in domains
like fashion and retail, are substantially shaped by multi-modal data, such as
pictures and textual descriptions. These modalities not only offer intuitive
guidance but also cater to personalized user preferences. However, the
predominant personalization approaches mainly focus on the ID or text-based
recommendation problem, failing to comprehend the information spanning various
tasks or modalities. In this paper, our goal is to establish a Unified paradigm
for Multi-modal Personalization systems (UniMP), which effectively leverages
multi-modal data while eliminating the complexities associated with task- and
modality-specific customization. We argue that the advancements in foundational
generative modeling have provided the flexibility and effectiveness necessary
to achieve the objective. In light of this, we develop a generic and extensible
personalization generative framework, that can handle a wide range of
personalized needs including item recommendation, product search, preference
prediction, explanation generation, and further user-guided image generation.
Our methodology enhances the capabilities of foundational language models for
personalized tasks by seamlessly ingesting interleaved cross-modal user history
information, ensuring a more precise and customized experience for users. To
train and evaluate the proposed multi-modal personalized tasks, we also
introduce a novel and comprehensive benchmark covering a variety of user
requirements. Our experiments on the real-world benchmark showcase the model's
potential, outperforming competitive methods specialized for each task.


  Let $(a_n)_{n \in \mathbb{N}}$ be a Hadamard lacunary sequence. We give upper
bounds for the maximal gap of the set of dilates $\{a_n \alpha\}_{n \leq N}$
modulo 1, in terms of $N$. For any lacunary sequence $(a_n)_{n \in \mathbb{N}}$
we prove the existence of a dilation factor $\alpha$ such that the maximal gap
is of order at most $(\log N)/N$, and we prove that for Lebesgue almost all
$\alpha$ the maximal gap is of order at most $(\log N)^{2+\varepsilon}/N$. The
metric result is generalized to other measures satisfying a certain Fourier
decay assumption. Both upper bounds are optimal up to a factor of logarithmic
order, and the latter result improves a recent result of Chow and Technau.
Finally, we show that our result implies an improved upper bound in the
inhomogeneous version of Littlewood's problem in multiplicative Diophantine
approximation.


  We investigate the role of the Coulomb interaction in strong field processes.
We find that the Coulomb field of the ion makes its presence known even in
highly intense laser fields, in contrast to the assumptions of the strong field
approximation. The dynamics of the electron after ionization is analyzed with
four models for an arbitrary laser polarization: the Hamiltonian model in the
dipole approximation, the strong field approximation, the Coulomb-corrected
strong field approximation and the guiding center. These models illustrate
clearly the Coulomb effects, in particular Coulomb focusing and Coulomb
asymmetry. We show that the Coulomb-corrected strong field approximation and
the guiding center are complementary, in the sense that the Coulomb-corrected
strong field approximation describes well short time scale phenomena (shorter
than a laser cycle) while the guiding center is well suited for describing long
time scale phenomena (longer than a laser cycle) like Coulomb-driven
recollisions and Rydberg state creation.